Comprehensive Geriatric Oncology

Comprehensive Geriatric Oncology 2nd Edition Edited by Lodovico Balducci MD Professor of Medicine and Program Leader S...

Author: Lodovico Balducci | William B. Ershler | Gary H. Lyman | Martine Extermann

38 downloads 1307 Views 15MB Size Report

This content was uploaded by our users and we assume good faith they have the permission to share this book. If you own the copyright to this book and it is wrongfully on our website, we offer a simple DMCA procedure to remove your content from our site. Start by pressing the button below!
Report copyright / DMCA form

DOWNLOAD PDF

Comprehensive Geriatric Oncology 2nd Edition Edited by

Lodovico Balducci MD Professor of Medicine and Program Leader Senior Adult Oncology Program H Lee Moffitt Cancer Center and Research Institute Tampa, FL 33612 USA Gary H Lyman MD MPH Professor of Medicine, Epidemiology and Biostatistics Medical Oncology and Hematology H Lee Moffitt Cancer Center and Research Institute Tampa, FL 33612 USA

William B Ershler MD Director, Institute for Advanced Studies in Aging and Geriatric Medicine 1819 Pennsylvania Avenue NW Washington, DC 20006 USA Martine Extermann MD Senior Adult Oncology Program H Lee Moffitt Cancer Center and Research Institute Tampa, FL 33612 USA

LONDON AND NEW YORK A MARTIN DUNITZ BOOK

© 2004 Taylor & Francis, an imprint of the Taylor & Francis Group First published in the United Kingdom in 2004 by Taylor & Francis, an imprint of the Taylor & Francis Group, 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN Tel: 01235 828600 Fax: 01235 829000 E-mail: [email protected] Website: http://www.dunitz.co.uk/ This edition published in the Taylor & Francis e-Library, 2006. To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to http://www.ebookstore.tandf.co.uk/. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of the publisher or in accordance with the provisions of the Copyright, Designs and Patents Act 1988 or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, 90 Tottenham Court Road, London W1P 0LP. Although every effort has been made to ensure that all owners of copyright material have been acknowledged in this publication, we would be glad to acknowledge in subsequent reprints or editions any omissions brought to our attention. A CIP record for this book is available from the British Library. Library of Congress Cataloging-in-Publication Data Data available on application ISBN 0-203-49451-2 Master e-book ISBN

ISBN 0-203-59590-4 (Adobe e-Reader Format) ISBN 1 84184 296 6 (Print Edition) Distributed in North and South America by Taylor & Francis 2000 NW Corporate Blvd Boca Raton, FL 33431, USA Within Continental USA Tel: 800 272 7737; Fax: 800 374 3401 Outside Continental USA Tel: 561 994 0555; Fax: 561 361 6018 E-mail: [email protected] Distributed in the rest of the world by Thomson Publishing Services Cheriton House North Way Andover, Hampshire SP10 5BE, UK Tel: +44 (0)1264 332424 E-mail: [email protected] Composition by Scribe Design, Gillingham, Kent, UK

Contents List of contributors Preface to the second edition Preface to the first edition

ix xxvii xxx

Part 1— Overview 1. Aging and cancer BJ Kennedy 2. Essentials of clinical decision analysis: A new way to think about cancer and aging Gary H Lyman

2 18

Part 2— Epidemiology 3. Cancer mortality in the elderly, 1960–98: A worldwide approach Carlo La Vecchia, Franca Lucchini, Eva Negri, Fabio Levi 4. Cancer in older persons: Magnitude of the problem and efforts to advance the aging/cancer research interface Rosemary Yancik, Lynn AG Ries 5. Epidemiological research in aging: Perspectives and limitations Marion RS Bain, Jean C Harvey 6. Factors affecting the diagnosis and treatment of older persons with cancer James S Goodwin, Cynthia Osborne

51 63

78 94

Part 3— Biology of aging and cancer 7. Biology of aging and cancer William B Ershler 8. Age as a risk factor in multistage carcinogenesis Vladimir N Anisimov 9. Growth factors, oncogenes, and aging J Alberto Fernandez-Pol

109 123 170

10. Proliferative senescence and cancer Judith Campisi 11. Apoptosis, chemotherapy, and aging David E Fisher 12. Tumor-host interactions, aging, and tumor growth William B Ershler 13. Immunological changes of aging Edith A Burns, James S Goodwin 14. Biologic characteristics of primary breast cancer Maria Grazia Daidone, Rosella Silvestrini, Aurora Costa, Danila Coradini, Gabriele Martelli, Silvia Veneroni 15. Clinical evidence for change in tumor aggressiveness with age: A historical perspective Frederick F Holmes 16. Morbid anatomy of aging Giorgio Stanta 17. Natural history and epidemiology of monoclonal gammopathies Harvey Jay Cohen, Daniel Nikcevich

223 243 261 283 306

322

333 347

Part 4— The influence of aging on prevention, diagnosis and treatment of cancer 18. Physiology of aging: Relevance to symptoms, perceptions, and treatment tolerance Edmund H Duthie, Jr 19. Assessment of the older patient with cancer Lodovico Balducci, Martine Extermann 20. Frailty, cancer cachexia, and near death David Hamerman 21. Practical proposals for clinical protocols in elderly patients with cancer Martine Extermann, Lodovico Balducd 22. Under-representation of elderly patients in cancer clinical trials: Causes and remedial strategies Joseph M Unger, Laura F Hutchins, Kathie S Albain 23. Radiotherapy in the elderly: The achievements of the Geriatric Radiation Oncology Group (GROG) Patrizia Olmi, Giampiero Ausili Cefaro, Anna Marie Cerrotta 24. Quality of life considerations in the older cancer patient Patrida A Ganz 25. Social support and the elderly cancer patient Cleora S Roberts 26. Prognostic evaluation of the older cancer patient Lazzaro Repetto, Antonella Venturino, Walter Gianni

367

398 422 448 464

492

520 538 551

Part 5— Cancer prevention in the aged 27. Nutrition, cancer, and the aging process: A rationale for nutritional practice guidelines Nagi Kumar, Jeanne Hudson, Theresa Crocker, Diane Riccardi, Kathy Allen 28. Chemoprevention of cancer in the older person Lodovico Balducci, Claudia Beghe’ 29. Secondary prevention of cancer in the older person Claudia Beghe’, Lodovico Balducci 30. Barriers to cancer prevention in the older person Sarah A Fox, Richard G Roetzheim

571

618 645 665

Part 6— Management of cancer in the older person 31. Perspectives on training in geriatrics and oncology John M Bennett 32. Management of cancer in the older aged patient Lodovico Balducci, Charles E Cox, Harvey Greenberg, Gary H Lyman, Rafael Miguel, Richard Karl, Peter J Fabri 33. Surgical approaches to the older patient with cancer Peter J Fabri 34. Advances in geriatric surgery Peter J Fabri 35. Perioperative considerations in the geriatric oncology patient Rafael Miguel, Hector Vila 36. Hematopoiesis and aging Lynn C Mosdnski 37. Anemia and aging: Relevance to the management of cancer Lodovico Balducci, Cheryl L Hardy 38. Radiotherapy in the elderly Pierre Scalliet, Thierry Pignon 39. Cancer chemotherapy in the older patient Dario Cova, Lodovico Balducci 40. Hematopoietic stem cell transplantation in the older patient Karen K Fields, Benjamin Djulbegovic 41. Polypharmacy in the senior adult patient Mary E Corcoran, 42. Diagnosis and treatment of cancer in the elderly: Cost-effectiveness considerations Gary H Lyman, Nicole M Kuderer 43. Guidelines for the management of the older cancer patient Lodovico Balducci

685 688

702 715 731 753 782 801 818 864 890 905

933

Lodovico Balducci 44. Oncological emergencies in the elderly Lodovico Balducci, Claudia Beghe’

949

Part 7— Management of specific tumors in older persons 45. Treatment of acute myeloid leukemia in older patients Thomas Buchner 46. Chronic leukemias in the elderly Alexander SD Spiers 47. Hodgkin lymphoma in the elderly Paul Kaesberg 48. Non-Hodgkin lymphomas Bruce Peterson, Stuart Bloom 49. Advances in the treatment of multiple myeloma in the elderly patient Gabriela Ballester, Oscar Ballester, Claudia Corrado, David Vesole 50. Treatment of small cell lung cancer in the elderly Frances A Shepherd, Andrea Bezjak 51. Breast cancer in the older woman: An oncologic perspective Lodovico Balducci, Rebecca A Silliman, Nils Diaz 52. Breast cancer: A geriatric perspective Sarah B Blackman, Rebecca A Silliman, Lodovico Balducci 53. Colorectal cancer Barbara A Neilan 54. Head and neck oncology in the aging patient James N Endicott, Lodovico Balducci 55. Prostate cancer in the elderly Timothy D Moon 56. Transitional cell carcinoma of the bladder in the elderly Julio Pow-Sang, Jay Friedland, Albert Einstein 57. Brain tumors in the older person Alexandra Flowers 58. Gynecologic cancers in the elderly Tate Thigpen 59. Skin cancer in the aging patient Matthew J Reschly, Karen Laszlo Keller, Dan Smith, Neil A Fenske, L Frank Glass

980 995 1074 1094 1133 1150 1169 1244 1255 1267 1279 1312 1324 1363 1388

Part 8— Rehabilitation and supportive care 60. Management of infectious complications in the aged cancer patient John N Greene

1418

61. Symptom management in the older patient Robert Anderson, Walter B Forman 62. Oncological rehabilitation of the elderly Dario Dini, Alberto Gozza 63. Family caregiving issues for older cancer patients William E Haley, Allison M Burton, Laurie A LaMonde, Ronald S Schonwetter 64. Interdisciplinary teams in geriatric oncology Janine Overcash 863 Spirituality and medicine Mary Jane Marsh, Russell Meyer, Lodovico Balducci Index

1435 1467 1492

1509 1526

1532

List of contributors Kathie S Albain MD Professor of Medicine Loyala University Medical Center Cancer Center 2160 South First Avenue Maywood, IL 60153–5589 USA Kathy Allen RD Department of Nutrition H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Robert P Anderson Oncology Pharmacist Veterans Affairs Medical Center Albuquerque, NM USA Vladimir N Anisimov PhD Chief, Laboratory of Experimental Tumors NN Petrov Research Institute of Oncology 68 Leningradskaya St Pesochny—2 St Petersburg Russia Marion RS Bain MB ChB Medical Director Information and Statistics Division National Health Service Scotland Trinity Park House, South Trinity Road Edinburgh EH5 3SQ UK Lodovico Balducci MD Professor of Oncology and Medicine Interdisciplinary Oncology Program

University of Florida College of Medicine and Professor of Medicine and Program Leader Senior Adult Oncology Program H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Gabriela Ballester MD Fellow, Hematology Oncology Medical College of Georgia Augusta, GA 30912 USA Oscar Ballester Director, Stem Cell Transplant Program Medical College of Georgia Augusta, GA 30912 USA Claudia Beghe’ Associate Professor of Medicine University of Florida College of Medicine Tampa, FL and Medical Director Nursing Home Care Unit James A Haley Veterans Hospital Tampa, FL 33612 USA John M Bennett MD Professor of Medicine University of Rochester Cancer Center Rochester, NY 14642 USA Andrea Bezjak MD Department of Radiation Oncology Princess Margaret Hospital Toronto, Ontario M5G 2M9 Canada Sarah B Blackman MPH Health Care Compliance Specialist

University of Virginia 2270 Ivy Road Charlottesville, VA 22903 USA Stuart Bloom MD Medical Oncology, Hematology Hubert H Humphrey Cancer Center Robbinsdale, MN 55422–2900 USA Thomas Büchner MD Professor of Medicine University of Miinster Department of Medicine Hematology and Oncology D48129 Munster Germany Edith A Burns MD Assistant Professor of Medicine Section of Geriatrics Sinai Samaritan Medical Center Milwaukee, WI USA Allison M Burton BA Doctoral Candidate School of Aging Studies University of South Florida 4202 East Fowler Avenue Tampa, FL 33620 USA Judith Campisi PhD Senior Scientist Lawrence Berkeley National Laboratory 1 Cyclotron Road, 84–171 Berkeley, CA 94720 USA Giampiero Ausili Cefaro MD Chief, Radiotherapy Division Policlinico A Gemelli Universita Cattolica Sacro Cuore Largo A Gemelli, 8

Rome Italy Anna Marie Cerrotta MD Professor of Radiation Oncology Department of Radiotherapy National Cancer Institute Milano Italy Harvey Jay Cohen MD Professor of Medicine Chief of Geriatrics and Director, Center on Aging Duke University Medical Center Durham, NC 27710 USA and Director, FRECC, VAMC Durham, NC 27705 USA Danila Coradini PhD Experimental Oncology Department Unit 10—Determinants of Prognosis and Treatment Response Instituto Nazionale Tumori Via Venezian 1 20133 Milan Italy Mary E Corcoran CRPH Clinical Pharmacist H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Drive Tampa, FL 33612 USA Claudia Corrado MD Attending Physician National Academy of Medicine Buenos Aires Argentina Aurora Costa PhD Experimental Oncology Department Unit 10—Determinants of Prognosis and Treatment Response

Instituto Nazionale Tumori Via Venezian 1 20133 Milan Italy Dario Cova MD Chief, Oncology Service Pio Albergo Trivulzio Milano Italy Charles E Cox MD Professor H Lee Moffitt Cancer Center 12902 Magnolia Drive Tampa, FL 33612 USA Theresa Crocker MD, RD Department of Nutrition H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Maria Grazia Daidone PhD Experimental Oncology Department Unit 10—Determinants of Prognosis and Treatment Response Instituto Nazionale Tumori Via Venezian 1 20133 Milan Italy Nils Diaz H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Dario Dini MD Professor of Rehabilitative Medicine Istituto Nazionale per la Ricerca sul Cancro Genova Italy

Benjamin Djulbegovic MD Professor of Oncology and Medicine H Lee Moffitt Cancer Center and Research Institute University of South Florida Department of Interndisciplinary Oncology 12902 Magnolia Drive Tampa, FL 33612 USA Edmund H Duthie, Jr MD Professor of Medicine Chief, Division of Geriatrics and Gerontology Medical College of Wisconsin VA Medical Center Milwaukee Milwaukee, WI 53295 USA Albert B Einstein, Jr MD Executive Director Swedish Cancer Institute Swedish Health Services 1221 Madison Street #500 Seattie, WA 98104 USA James N Endicott MD Professor, Otolaryngology St Petersburg, FL USA William B Ershler MD Director, Institute for Advanced Studies in Aging and Geriatric Medicine Senior Investigator Clinical Research branch National Institute on Aging 1700 Wisconsin Avenue NW Washington, DC 20007 USA Martine Extermann MD Senior Adult Oncology Program H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA

Peter J Fabri MD Professor of Surgery Assistant Dean for Clinical Affairs University of South Florida, College of Medicine Tampa, FL 33620 USA Neil A Fenske MD Professor and Director Division of Dermatology and Cutaneous Surgery University of South Florida College of Medicine 12901 Bruce B Downs Boulevard Tampa, FL 33162 USA J Alberto Fernandez-Pol MD 437 Hunters Hill Drive Chesterfield, MO 63017 USA Karen K Fields Professor of Medicine and Oncology H Lee Moffitt Cancer Center and Research Institute University of South Florida 12902 Magnolia Avenue Tampa, FL 33612 USA David E Fisher MD Associate Professor Harvard Medical Center Dana-Farber Cancer Institute 44 Binney Street, Dana 630 Boston, MA 02115 USA Alexandra Flowers MD Coordinator, Neuro-Oncology Program Hartford Hospital 80 Seymour Street Hartford, CT 06102 USA Walter B Forman MD Professor, Department of Internal Medicine Division of Geriatrics

University of New Mexico Health Sciences Center Albuquerque, NM 87131 USA Sarah A Fox EdD MSPH Professor, Division of General Internal Medicine and Health Services Research Department of Medicine David Geffen School of Medicine University of California at Los Angeles 1100 Glendon Avenue, Suite 2010 Los Angeles, CA 90024-3524 USA Jay Friedland MD Assistant Professor of Radiation Oncology University of Pennsylvania Pennsylvania USA Patricia A Ganz MD Professor, Schools of Medicine and Public Health Division of Cancer Prevention and Control Research Jonsson Comprehensive Cancer Center University of California Los Angeles, CA 90095–6900 USA Walter Gianni U O Oncologia Istituto Nazionale di Riposo e Cura per Anziani (INRCA) Rome Italy L Frank Glass MD Associate Professor Division of Dermatology and Cutaneous Surgery University of South Florida College of Medicine 12901 Bruce B Downs Boulevard Tampa, FL 33162 USA James S Goodwin MD George and Cynthia Mitchell Distinguished Professor

The University of Texas Medical Branch Galveston, TX USA Alberto Gozza MD Associate Professor National Institute of Cancer Research Genova Italy Harvey Greenberg MD Associate Professor Department of Radiation Oncology H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA John N Greene MD Associate Professor Infection Control H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA William E Haley PhD Professor and Director School of Aging Studies University of South Florida 402 East Fowler Avenue Tampa, FL 33620 USA David Hamerman MD Distinguished University Professor and Director Resnick Gerontology Center Albert Einstein College of Medicine Montefiore Medical Center Bronx, NY 10467 USA Cheryl L Hardy MD Division of Hematology University of Mississippi School of Medicine 2500 N State Street

Jackson, MS USA Jean C Harvey BSc (Hons) Scottish Cancer Registry Information and Statistics Division National Health Service Scotland Trinity Park House, South Trinity Road Edinburgh EH5 3SQ UK Frederick F Holmes MD Edward Hasinger Distinguished Professor University of Kansas Medical Center School of Medicine, Department of Internal Medicine Division of General and Geriatric Medicine 3901 Rainbow Boulevard Kansas City, KA 66216-1234 USA Jeanne Hudson RD Department of Nutrition H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Laura F Hutchins MD Professor of Medicine University of Arkansas for Medical Sciences 4301 W Markham Slot 508 Little Rock, AR 72205 USA Paul R Kaesberg MD Clinical Assistant Professor of Medicine Section of Medical Oncology University of Wisconsin School of Medicine c/o William S Middleton Veteran’s Administration Hospital 2500 Overlook Terrace Madison, WI 53705 USA

Richard Karl MD Chief of Surgery and Program Leader Gastrointestinal Tumor Program H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Karen Laszlo Keller MD Resident Division of Dermatology and Cutaneous Surgery University of South Florida College of Medicine 12901 Bruce B Downs Boulevard Tampa, FL 33162 USA BJ Kennedy MD (deceased) Formerly Regents’ Professor of Medicine, Emeritus Masonic Professor of Oncology, Emeritus Division of Hematology, Oncology and Transplantation University of Minnesota Medical School Minneapolis, MN 55455 USA Nicole M Kuderer MD University of South Florida H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Nagi Kumar PhD, RD, FADA Department of Nutrition H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Carlo La Vecchia Instituto di Ricerche Farmacologiche ‘Mario Negri’ Via Eritrea 62 20157 Milan Italy Laurie A LaMonde PhD School of Aging Studies

University of South Florida 4202 East Fowler Avenue Tampa, FL 33620 USA Fabio Levi MD Registre Vaudois des tumeurs Institute Universitaire de Medecine Sociale et Preventive Centre Hospital Universitaire Vaudois 1011 Lausanne Switzerland Franca Lucchini Unite Epidemiologie du Cancer and Registeres Vaudois et Neuchatelois des tumours Institute Universitaire de Medecine Sociale et Preventive Centre Hospital Universitaire Vaudois 1011 Lausanne Switzerland Gary H Lyman MD MPH Director, Cancer Center of Albany Medical College 47 New Scotland Avenue Albany, NY 12208 and Professor of Medicine, Epidemiology and Biostatistics Medical Oncology and Hematology University of South Florida H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Mary Jane Marsh RN Gastrointestinal Tumor Program H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Gabriele Martelli MD Unit of Diagnostic Oncology and Outpatient Clinic Instituto Nazionale Tumori Via Venezian 1 20133 Milan Italy

Russell Meyer MDiv Tampa, FL USA Rafael Miguel MD University of South Florida, College of Medicine H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Timothy D Moon MD Department of Surgery Division of Urology University of Wisconsin Madison, WI 53792 USA Lynn C Moscinski MD Professor, Department of Pathology University of South Florida, College of Medicine H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Eva Negri Instituto di Ricerche Farmacologiche ‘Mario Negri’ Via Eritrea 62 20157 Milan Italy Barbara A Neilan Regional Hematology and Oncology, PA 4701 Ogletown Stanton Road Suite 2100 Newark, DE 19713 USA Daniel Nikcevich MD Division of Hematology/Oncology and Center on Aging Duke University Medical Center Durham, NC 27710 USA

Patrizia Olmi Radiotherapy Division Policlinico A Gemelli Universita Cattolica Sacro Cuore Largo A Gemelli, 8 Rome Italy Cynthia Osborne MD Simmons Comprehensive Cancer Center University of Texas Dallas, TX USA Janine Overcash PhD Assistant Professor University of South Florida College of Nursing Tampa, FL USA Bruce Peterson MD Division of Oncology University of Minnesota School of Medicine 420 Delaware Street SE Minneapolis, MN USA Thierry Pignon MD Department of Radiotherapy Hopital de la Timone Marseille France Julio Pow-Sang MD Associate Professor Department of Surgery H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Lazarro Repetto MD U O Oncologia Istituto Nazionale di Riposo e Cura per Anziani (INRCA) Roma Italy

Matthew J Reschly MD Resident Division of Dermatology and Cutaneous Surgery University of South Florida College of Medicine 12901 Bruce B Downs Boulevard Tampa, FL 33162 USA Diane Riccardi MPH RD Department of Nutrition H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Avenue Tampa, FL 33612 USA Lynn AG Ries MS Cancer Statistics Branch Surveillance Program Division of Cancer Prevention and Control National Cancer Institute Bethesda, MD USA Cleora S Roberts Research Social Worker H Lee Moffitt Cancer Center and Research Institute 12902 Magnolia Drive Tampa, FL 33612 USA Richard Roetzheim MD MSPH Professor, Department of Family Medicine University of South Florida 12901 Bruce B Downs Blvd, MDC 13 Tampa, FL 33612 USA Pierre Scalliet MD Radiation Oncology Cliniques Universitaries St Luc Ave Hippocrate 10 Brussels Belgium Ronald S Schonwetter MD Professor and Director Division of Geriatric Medicine

Department of Internal Medicine University of South Florida College of Medicine and Chief Medical Officer LifePath Hospice and Palliative Care. Inc. Tampa FL 33612 USA Frances A Shepherd MD Scott Taylor Chair in Lung Cancer Research Princess Margaret Hospital Professor of Medicine University of Toronto Toronto, Ontario M5G 2M9 Canada Rebecca A Silliman MD PhD Professor of Medicine and Public Health Chief, Geriatrics Section Boston University School of Medicine Boston, MA 2118 USA Rosella Silvestrini PhD Experimental Oncology Department Unit 10—Determinants of Prognosis and Treatment Response Instituto Nazionale Tumori Via Venezian 1 20133 Milan Italy Dan Smith MD Resident Division of Dermatology and Cutaneous Surgery University of South Florida College of Medicine 12901 Bruce B Downs Boulevard Tampa, FL 33162 USA Alexander SD Spiers MD PhD FRCPE Professor of Medicine Quarry Wood End Gibraltar Lane Cookham

Maidenhead SL6 9TR UK formerly Director, Leukemia and Lymphoma Center H Lee Moffitt Cancer Center and Research Institute University of South Florida Tampa, FL 33612 USA Giorgio Stanta MD International Center for Genetic Engineering and Biotechnology Are Science Park Trieste Italy Tate Thigpen MD Professor of Medicine Director, Division of Oncology Department of Medicine University of Mississippi School of Medicine 2500 North State Street Jackson, MI USA Joseph M Unger MS Biostatistician Southwest Oncology Group Statistical Center Fred Hutchinson Cancer Research Center 1100 Fairview Avenue N PO Box 19024 Seattle, WA 98109-1024 USA Silvia Veneroni PhD Experimental Oncology Department Unit 10—Determinants of Prognosis and Treatment Response Instituto Nazionale Tumori Via Venezian 1 20133 Milan Italy Antonella Venturino U O Oncologia Medica USL 1 Imperiese

Ospedale di Sanremo (IM) Italy David Vesole MD Associate Professor University of Arkansas for Medical Sciences Little Rock, AR USA Hector Vila MD Assistant Professor and Chief of Anesthesiology H Lee Moffitt Cancer Center and Research Institute Department of Interdisciplinary Oncology University of South Florida Tampa, FL 33612 USA Rosemary Yancik PhD Chief, Cancer and Aging Section, Geriatrics Program National Institutes of Health National Institute on Aging Bethesda, MD USA

Preface to the second edition The past decade has seen a spate of interest in issues related to cancer in the older person. More and more, the older cancer patient has become representative of the majority of cancer patients and the focus of both research and clinical activities. Some recent milestones in geriatric oncology include the formation of an International Society of Geriatric Oncology (SIOG), the proliferation of training programs in geriatric oncology in major academic centers in the USA, the publication of a curriculum in geriatric oncology by the American Society of Clinical Oncology (ASCO), the institution of task forces in geriatric oncology within the ASCO, the American Association for Cancer Research (AACR), and the European Organization for the Research and Treatment of Cancer (EORTC), the establishment of aging-related committees within the major cooperative groups, the foundation of a Geriatric Oncology Consortium (GOC), and the proliferation of research projects and scientific papers related to cancer and aging. Perhaps the final seal of approval given to this emerging discipline has been the combined NCI/NIA conference held in Bethesda in 2001, involving the directors of all comprehensive cancer centers in the USA. This conference spawned a number of RFPs, both for the Institution of Geriatric Oncology Programs within the Cancer Centers and for individual research projects in cancer and aging, as testimony of the scientific community’s commitment to the pursuance of these issues. As a result of these initiatives, a number of important principles have been established. First, the complex biologic relationship of aging and cancer has been highlighted, with the recognition that some molecular and environmental changes of aging may favor and others may oppose the development of cancer. Second, some interactions of aging and cancer growth have been elucidated, together with the mechanisms that render some tumors more aggressive and others more indolent in the older person. Third, the risks and benefits of cancer treatment in older individuals have been better defined, with the recognition that older individuals tolerate emergency procedures less well than the younger ones, and are more subjected to some complications of chemotherapy, such as myelosuppression, mucositis, and neurotoxicity. Fourth, the instruments for a more uniform evaluation of the older person have been developed: the Comprehensive Geriatric Assessment is still the mainstay of any intervention, providing a nosologic classification of age, an estimate of life-expectancy and tolerance of treatment, and an outline of reversible conditions that may complicate cancer treatment. New screening instruments are being developed to make the geriatric assessment cost-and time-effective and user-friendly, and these have been complemented by new tests of physical performance as well as by laboratory tests. The discovery that circulating levels of interleukin-6 and D-dimer predict functional decline and mortality in an otherwise healthy elderly population may represent a turning point in the assessment of aging. Fifth, knowledge of the field has developed enough to formulate the first guidelines for the management of cancer in the older person. These exciting developments could be

summarized by saying that oncology has kept pace with demographic trends and has become attuned to study and serve the most likely cancer patient of the future, namely the older person. The previous edition of this book has certainly contributed to this surge of interest and activity. One could say that the major role of the previous edition has been to awaken academic, professional, and public awareness to the size of the problem and to the need for more investigations, and to ensure that older individuals benefit fully from recent advances in cancer prevention and cancer treatment. In doing so, it has been necessary to dispel the myth that older individuals are too frail or too short-lived to deserve preventive and therapeutic interventions, and to outline the principles of clinical trials in the elderly, to identify potential subjects of bench-to-bedside translation in the biologic interactions of cancer and age, and to review sparse data regarding cancer prevention and cancer treatment. These goals have largely been accomplished. To remain effective and meaningful, the book needs to adjust its directions to the changing clinical landscape. This new edition of Comprehensive Geriatric Oncology still offers an exhaustive review of the biology of cancer and aging, of the epidemiologic trends in the country and in the world, and of the clinical trials that concern cancer prevention and cancer treatment in the elderly. In addition, this new edition addresses issues of healthcare delivery, including cost and evaluation of utility and outcome, suggests new research approaches to older cancer patients, explores newly emerging problems such as anemia in the elderly and especially in elderly cancer patients, reviews existing guidelines for the prevention and treatment of cancer in the elderly, and studies the effectiveness of training programs in geriatric oncology. In the editors’ plans, Comprehensive Geriatric Oncology will still represent the major reference work for basic, population, and clinical scientists interested in the issue and for practitioners ministering to older cancer patients. In addition, the editors would like to make the book a frame of reference for the ongoing dialogue in the field of geriatric oncology. We do realize that we are no longer the only voice in the field; we hope to become the source that shapes the dialogue, the note to which different notes are attuned. As before, the measure of our accomplishment will be the recognition of our readership. This book is multivocal, as it includes authors from different countries and different continents. This aspect of Comprehensive Geriatric Oncology reflects the universality of the problem and of the interest in the problem, at least in the Western world. At the same time, this worldwide representation is aimed to accommodate different attitudes toward and different interpretations of aging, with the deeply held conviction that different cultures may each teach unique lessons in the approach to the older person and the older patient. The combination of different experiences may indicate the safest and speediest route in sailing uncharted waters. We would like to thank, in addition to the contributors to the books, the scientists and clinicians worldwide who have shared their experience with us during encounters in real and cyberspace, the other healthcare professionals—mainly nurses, social workers, pharmacists, and dieticians—who have worked with us as a team, and above all the patients who have provided the most vital lessons to the development of geriatric oncology. While it is impossible to name everybody, we feel we have to address very special thanks to Rosemary Yancik, PhD, of the National Institute on Aging, who has been the uncontested founder of the field and has remained the most acknowledged

leader, for continuous leadership and inspiration. We also wish to acknowledge the loss of two giants of oncology, who have been among the pioneers of geriatric oncology: BJ Kennedy MD and Paul Carbone MD. Both of them identified the field of cancer and aging as a prime area of intervention and used their world-renowned academic pulpit to spread the word and support our effort. Lodovico Balducci Gary H Lyman William B Ershler Martine Extermann

Preface to the first edition Management of cancer in the older-aged person is an increasingly common problem. The issues of geriatric oncology are as complicated and elusive as the definition of aging/a highly individualized process involving changes in physical, cognitive, emotional, social and economic domains. In epidemiological studies the changes of aging have been well recognized as restricted physiologic reserve, higher prevalence of comorbidity, diminished and delayed processing of new information, enhanced susceptibility to depression, limited social support, de-creased financial resources, and confinement. However, the occurrence, the severity of the interactions, and the overall impact of these changes in the individual person are not predictable from one’s chronologic age. Despite the inability to establish certain chronologic boundaries of senescence, that has handicapped the study of the interactions of aging and disease, in 1992 we endeavored to publish the first treatise of geriatric oncology. Our effort was inspired and supported by the conviction that cancer in older persons may be considered a different disease from cancer in the younger persons, that the biology of the aged tumor host influenced the growth of cancer, that the management of cancer in the older person deserved an individualized approach in terms of prevention and treatment, and that medical decisions involving the older person with cancer involved the knowledge and the awareness of the multidimensional changes of age. This view/which was then a minority view, has been largely vindicated by recent molecular and epidemiologic discoveries, and by recent approaches to cancer treatment. Just to quote a few examples, age is today a well recognized negative prognostic factor for large cell lymphoma and for ovarian cancer, the prevalence of multidrug resistance in leukemic myeloblasts in persons aged 60 and over was found to be as high as 57% (versus 17% in younger patients), and a number of treatment protocols aimed at older persons with special forms of cancer, such as non-Hodgkin’s lymphoma and breast cancer, have been developed. In the introduction to a previous publication we stated that the characteristics of aging are influenced by evolving cultural and environmental factors. Accordingly, we proposed to lay the foundation for a continuing discourse on aging and cancer. We believe the time is ripe for reframing and restating our original propositions in the light of the information accumulated during the last five years. Unquestionably, the issues of cancer and aging have elicited more interest during the past five years than ever before: for example, all major cooperative oncology groups both in the USA and in Europe have included committees devoted to the issues of aging, three international conferences devoted to cancer and age, with multinational support, have been held at biennial intervals in Argentina, Italy and the USA; the National Institute on Aging has issued a RFA for the study of breast cancer in the older woman, and the number of scientific articles, communications, and reviews concerning management of cancer in the older person have increased dramatically. At the same time, the spectacular advances in molecular biology have shed unexpected light on the interactions of aging

and cancer. The flourishing of these diverse activities has yielded a host of new information that will deeply affect the approach to the older person with cancer. Our previous publication highlighted a number of areas where interactions of aging and cancer appeared likely. This book addresses the major areas of cancer biology, cancer prevention and cancer treatment in the light of newly acquired knowledge. Among the major additions to our new book we would like to underline an international epidemiological perspective, an analysis of age-related molecular and immunologic changes, a review of the physiology of aging, an ‘in depth’ analysis of chemoprevention, a guide to the assessment of life-expectancy, comorbidity, and quality of life, new advances in the use of anesthesia in the older person with cancer, and an examination of gastrointestinal and thoracic malignancies in older individuals. In addition, the issues of surgery/ chemotherapy, radiotherapy and nutrition, as well as the chapters related to screening, decision analysis, supportive management, nursing issues, breast cancer, lymphomas and multiple myeloma, have been expanded to accommodate new knowledge and new problems. The aim of this book is threefold. First and foremost, we wish to assist the practitioner in delivering the best possible cancer care to older patients. For this purpose, we provide an extensive review of current information on the effects of age on tolerance of antineoplastic treatments, such as surgery, radiation therapy, cytotoxic chemotherapy, hormonal and biologic therapy and we explore the role of novel interventions, such as bone marrow transplantation, administration of hemopoietic growth factors and endoscopic surgery. We also take a close look at the management of common malignancies in the elderly and we examine the influence of age on treatment choice. A painstaking analysis of major clinical trials is included, whenever possible, to identify data pertinent to older patients. Frequently, when cancer occurs in the very old, supportive care is the most appropriate form of management. Accordingly, we study supportive care of the older-aged person with cancer, focusing on symptom management, rehabilitation, quality of life assessment, and support structures. Information on patients, disease, and treatment has been prefaced by a chapter devoted to decision analysis. We feel that decision analysis represents a valuable clinical tool to plan the most favorable course of action in complex clinical situations, such as those involving elderly cancer patients. The clinical aspects of these situations present the practitioner with complex and often competing forces. Familiarity with decision analysis may guide the practitioner toward the management strategy associated with optimal outcome and may aid health policy decisions in the cost effective utilization of limited resources. Second, we wish to promote cancer prevention in the older-aged person. The incidence of most malignancies increases with age and, therefore, the elderly represent an ideal target for both secondary and tertiary prevention of cancer. Secondary prevention involves reversal of late carcinogenic stages, while tertiary prevention is achievable through screening asymptomatic persons for early cancer. For this reason we will illustrate the biological basis of increased cancer risk with aging, we entertain pharmacologic interventions that may lessen the risk of cancer and we review the results of clinical trials exploring early detection of common cancers in older persons. The data on cervical cancer may represent the first direct demonstration of the life-saving effect of screening in older persons. As in the case of cancer management, decision analysis may

direct the institution of the safest and most cost-effective preventative strategy in individual situations. Third, we wish to highlight emerging issues of geriatric oncology and present a research agenda for geriatric cancer in the older person. We believe that care delivery to the older-aged person with cancer is an area of major controversy and that this issue should be studied directly in the community where the elderly patient receives care. For this purpose, practitioners of oncology and of geriatrics should be ready to participate in community-based clinical trials that will embrace the data provided in this or similar volumes in the future. This book is directed primarily at the practicing oncologist. For this reason, the general principles of cancer treatment and the standard management of specific diseases were streamlined. We hope, however, that the book may also appeal to general surgeons, geriatricians and health professionals who provide primary care to elderly patients. It is possible that biologists may find in this book a rapid and exhaustive review of molecular and cellular interactions of aging and cancer, behavioral and social scientists may find a comprehensive outline of emotional and social problems of the older cancer patients, and clinical epidemiologists and health care planners may find important information related to the incidence of cancer in older patients and cancer care delivery to the older patients around the world. We hope to entice practitioners of various specialities and scientists of different disciplines to reflect on the multidimensional nature of aging and to work together to enhance our understanding of this important subject. The future of this book depends upon the feedback we receive from our interested readership. We do not know of any other clinical area which depends on the contribution of different disciplines and on the input from clinical practice to a higher degree than geriatric oncology. Lodovico Balducci Gary H Lyman William B Ershler

PART I Overview

1 Aging and cancer BJ Kennedy Introduction Aging is a normal process of our lifespan, not a disease. The US population is aging and older persons are living longer. Their future involves significant medical, public health, economic, social, and ethical issues.1 With aging, the incidence of cancer increases, and our expanding older population makes the prevalence of cancer more apparent. Recent reviews of geriatric oncology have characterized the problem in terms of the volume of patients and the diagnosis and treatment of the older person with cancer.1–7 To meet this challenge, there will be more emphasis on physician education in geriatrics, an increase in basic and clinical research on cancer in older persons, and an adjustment in physicians’ methods of care of older persons with cancer. Attitudes towards aging are undergoing a major change. Aging has been perceived as the end of life, with older persons having little potential for growth. Such perceived negative characteristics include cognitive impairment, decreased quality of life, poor prognosis, limited life-expectancy, and decreased social worth. As a result, efforts for maintenance of health of older persons have been impaired. To reverse this negative perception, elimination of the terms ‘senior citizens’, ‘golden age’, ‘elderly’, ‘frail old’, ‘older-old’ has been encouraged. The preferred term is ‘older persons’, which specifies no numerical age limit to the aging process and places more emphasis on the physiologic status of the patient. America is growing older.8,9 The US population over the age of 65 has increased 10fold since 1900. Today, 34.7 million Americans—one in every eight—are over 65 (12.5% of the total US population), compared with only one of every 15 persons in 1930 (Figure 1.1). It is projected that in 2020, one in every five Americans will be over 65.10 In 2010, the first wave of ‘baby boomers’—the 76 million babies born between 1946 and 1965—will reach 65 (Table 1.1). The predicted prolonged longevity and augmented size of this group will trigger a massive increase in the number of persons over 65 (Table 1.2).

Aging and cancer

3

Figure 1.1 Population (in millions) of ages 65 and over from 1960 to 2050. Source: US Bureau of the Census.

Table 1.1 Year and age of baby boomers born between 1945 and 196510 Year

Age

1975

10–30

1990

25–45

2010

45–65

2030

65–85

Comprehensive Geriatric Oncology

4

Table 1.2 Projected number of persons over age 65 in the USA Year

Millions

% of population

1990

31

12.5

2020

53

16.4

2030

70

20.1

Figure 1.2 Population 85 years and over: 1900– 2050 (in millions). Source: US Bureau of the Census, decennial censuses for specified years and population projections of the United States by age, sex, race, and Hispanic origin: 1993 to 2050. Current Population Reports, Series P-25, No. 1104. Washington,

Aging and cancer

5

DC: US Government Printing Office, 1993. Data for 1990 from 1990 Census of Population and Housing, CPH-L-74, modified and actual age, sex, race, and Hispanic origin data. The average length of life continues to increase. Life-expectancy in the USA has increased by 25 years since the start of the 20th century (Table 1.3). Life-expectancy for White women born today is 85 years while for White men born today it is 77 years.9 More impressive is the number of years remaining for older persons (Table 1.4). The maximum lifespan has been projected to be about 120 years. The number of older persons is increasing dramatically. Survival to the age of 80 and beyond has increased in many developed countries.11 Those aged 85 and over are the most rapidly growing group, having represented 2.2% of the population in 1980, and projected to represent 6% in 2010 and 18.9% in 2050 (Figure 1.2). Currently, 21% of all deaths occur in people over 85 years. There were 36000 persons over age 100 in 1990, and this is currently expected to double. Fifty percent of these live in nursing homes.

Table 1.3 Average life-expectancy9 Year (AD)

Length of life (years)

100

22

Middle Ages

33

1776

35

1850

42

1900

47

1950

68

1990

75

2050

85

Table 1.4 Remaining years of White female lifeexpectancy9 Current age

Years remaining

65

19.2

75

11.2

85

6.3


6

Figure 1.3 Percentage of persons aged 65 expected to survive to age 90:1940– 2050. Source: 1940–1980 from National Center for Health Statistics, decennial life tables; 2000 and 2050 from unpublished life tables consistent with population projections of the United States, by age, sex, race, and Hispanic origin: 1993 to 2050. Current Population Reports, Series P-25, No. 1104. Washington, DC: US Government Printing Office, 1993.

Aging and cancer

7

Figure 1.4 Number of men per 100 women by age: 1994. Source: US Bureau of the Census, data consistent with US population estimates by age, sex, race, and Hispanic origin: 1990 to 1993. Population Paper Listing-8 (PPL-8). Washington, DC: US Government Printing Office, 1994. Surviving to age 65 is more common nowadays. The Census Bureau projections imply that by 2050, over 40% of persons aged 65 years can expect to live to at least age 90 (Figure 1.3). Moreover, women are outliving men. The trend in sex ratio illustrates the greater survivorship probabilities of women (Figure 1.4). Progress against infectious diseases during the past 50 and more years has made it possible for people to live longer. Yet, because of fatty diets, cigarette smoking, and sedentary lifestyle, coronary heart disease was the number one killer. In the past 20 years, however, the death rate from coronary heart disease has plunged 48% because of the adoption of healthier lifestyles. With new drugs and treatment strategies, the coronary heart disease death rate is predicted to plummet still further this decade. With the decrease in coronary heart disease and vascular diseases, people are living longer, which has resulted in a new era of degenerative diseases, including Alzheimer’s disease and cancer. Cancer is a disease primarily of older persons (Figure 1.5).12 Over 60% of all cases of cancer are diagnosed after age 65—an age group that constitutes only 12.5% of the current US population. By 2030, 70% of patients with cancer will be over 65. More than 67% of cancer deaths occur in this older group. The risk of persons over 65 years of age developing cancer is 10 times that of those under 65. Up to the age of 50, the incidence of cancer is higher in women. After age 60, there is a remarkable increase in cancer


8

incidence among men. The growth of the older population, especially those over 75, implies that there will be marked increases in the number of incident cancers diagnosed during the next several decades.13 Concomitantly, death rates from cancer in older persons will continue to increase, but perhaps at a slower rate. There are multiple reasons for the greater incidence of cancer in older persons. They have less resistance and longer exposure to carcinogens, a decline in immune competence, alterations of antitumor defenses, decreased DNA repair, defects in tumor suppressor genes, and differences in biologic behavior, including such factors as angiogenesis. Because of the increased incidence and prevalence of cancer in older persons, as well as their higher mortality rate from cancer, it has been implied that no progress has been made in the fight against cancer. The data suggest otherwise (Table 1.5). The higher rates of cure of acute leukemia in children, testicular cancer in men, and Hodgkin lymphoma are responsible for a 23% decrease in cancer mortality in persons under 55 years. However, there has been a 17% increase in cancer mortality in those over 55 years.14

Figure 1.5 Average annual cancer incidence rates by age category: 1992– 1996 (logarithmic scale).12

Aging and cancer

9

Table 1.5 US cancer mortality per 10000014 Year

Age 55

1968

43

775

1985

35

905

−23%

+17%

% change

Physiology of aging The normal process of aging is associated with a progressive age-related reduction in function of many organs, including losses such as renal, pulmonary, immune, cardiac, hematologic, hepatic, muscle, sight, hearing, osseous, and brain functions. Physiologic functions of various organ systems at age 70 may be 50% of those observed at age 30. The volume of the liver decreases and blood flow to the liver decreases about 1% per year with age. A decrease in hepatic clearance and metabolism of drugs by the liver is also apparent. The most consistent physiologic change with aging is a decline in renal function. With a concomitant decrease in muscle mass, the serum creatinine level remains normal, making the creatinine clearance a more reliable indicator of renal function. It has been clearly shown that nephrotoxicity of cisplatin does not worsen with advancing age. Advancing age is associated with a decline in immune competence, as suggested by the higher incidence of cancer in older persons and their greater susceptibility to infections. The diminished immune functions are reflected by lymphocyte response to stimulation, delayed-type sensitivity, and antibody responses. With the involution of the thymus, T-cell deficiency may be a factor. Furthermore, interleukin-2 synthesis decreases with age. Mice with restricted caloric intake have a longer lifespan than those fed ad libitum. This prolonged lifespan is credited to the preservation of immune function. The consequences of these changes with age, added to comorbid diseases, have profound effects on tolerance to treatments of cancer, including surgery, radiotherapy, and chemotherapy. Although such changes should be taken into consideration when treating older patients for cancer, chronologic age alone should not be used as a guide to cancer prevention or therapy. It is the physiologic performance of the patient that is of prime importance.

Table 1.6 Estimated leading sites for cancer incidence: 2001, all ages15 Site Prostate

No. of cases 198100


10

Breast

193700

Lung

169500

Colorectal

135400

Non-Hodgkin lymphoma

63600

Table 1.7 Leading sites for cancer mortality in persons over 60 years of age: 199815 Age 60–79

Age >80

Male

Female

Male

Lung Prostate

Lung Breast

Colorectal Pancreas Non-Hodgkin lymphoma

Female

Ovary

Prostate

Colorectal

Colorectal

Breast

Bladder

Pancreas

Pancreas

Non-Hodgkin

lymphoma

Specific neoplasms The leading sites for the incidence of cancer for all ages (Table 1.6) differ from the leading sites for cancer mortality in older persons (Table 1.7). Most elderly patients benefit from thoughtful consideration of specific, comprehensive management plans to cure, control, or palliate a cancer. Advanced age is not a contraindication to major surgery, providing that comorbid diseases will not influence the potential mortality. Radiotherapy may be an excellent alternative. Chemotherapy is well tolerated when used with appropriate caution. Breast Breast cancer is the most common cancer in women. The incidence increases with age, with approximately 48% of all cases occurring in women older than 65. Older women are less likely to perform self-examination of the breast, have an annual breast examination, or have an annual mammogram. In fact, about two-thirds of women over age 65 in the USA do not have regular mammograms, despite payment by Medicare.16 A greater proportion of older persons has estrogen receptor-positive tumors than the younger population, reflecting a biologic difference of this cancer with age. The tumors are more likely to be well differentiated, have lower proliferative rates, and have more favorable histologic types. The approach to definitive therapy in early stages of the disease is comparable to that in the younger population. In the context of adjuvant therapies for disseminated disease in older persons, the chronologic and physiologic differences result

Aging and cancer

11

in altered hormonal or chemotherapy approaches compared with younger patients. The limited data on treatment efficacy in older women with breast cancer and selection bias in clinical trials have resulted in substantial variations in treatments.17 Treatment of the older patient is often influenced by factors other than the medical condition. Lung cancer Lung cancer is the leading cause of death from cancer in both sexes over age 75. There is a threefold greater risk for lung cancer in men over 65. Lung cancer is probably not a direct result of the aging process, but reflects the period of time necessary for tumor induction due to long-term tobacco use. After age 70, the age-specific incidence of lung cancer decreases, which may reflect a decline in smoking habits as people approach age 50. Of course, those who developed lung cancer earlier have already died. There also is a biologic difference in lung cancer in older persons. There is more squamous cell cancer in patients over 70 (71%) than in those under 50 (58%), which may reflect the less advanced stage of the disease in older patients. Although older persons may have a greater risk of early death after thoracotomy, the likelihood of long-term survival following surgery is not diminished by age alone. Hence, the risk of surgery is well worth the benefit in selected patients. Older patients fare just as well as younger ones with radiotherapy or palliative chemotherapy. Colorectal cancer Colorectal cancer is the third most common malignancy in the USA, and age is a leading risk factor. Over 90% of cases occur in those over 50, and the survival rates decrease with age. Unfortunately, the diagnosis of colorectal cancer is made in the late phase of the disease, because the elderly are less likely to receive routine health examinations. Stage for stage, surgery or chemotherapy should be employed as in younger persons. Adjuvant chemotherapy for stage III cancers is well tolerated.18 Prostate cancer Prostate cancer is the most common tumor in American men, and a major cause of death from cancer—second only to lung. After the age of 80 years, 50% of all men may have stage Al cancer (not clinically apparent). However, when initially diagnosed, nearly 70% of patients will have advanced disease. The introduction of the prostate-specific antigen (PSA) blood test has resulted in a greater number of patients diagnosed in the earlier phase of the disease. Introduction of free PSA may result in fewer ultrasounds and biopsies. Because prostate cancer is a relatively understudied disease among elderly men, data are lacking on the preferred method of management, especially in those over 75. The factors of symptoms, signs of obstructions, PSA level, tumor size, and histologic grade influence the decision-making process. Prostatectomy, radiotherapy, hormonal therapies, and watchful waiting are alternatives to be considered.


12

Pancreatic cancer The incidence of pancreatic cancer is increasing worldwide, and it ranks fourth as a cause of cancer deaths. Because of the aggressiveness of this cancer and its low curability rate, the mortality figures are similar for both sexes. Palliative surgery, radiotherapy for localized disease, and/or chemotherapy are selectively employed. Melanoma The incidence and mortality rate of melanoma are increasing at a faster rate than for any other cancer, except for lung cancer in women, as is the mortality rate.19 With increasing age, there is an increasing incidence of melanoma. Prolonged sun exposure is a factor. Survival can be substantial for these older patients, providing that constraints are not placed on the provision of curative treatment. Cervical cancer Cervical cancer incidence and mortality worldwide are second only to those of breast cancer, and in some countries this disease is the major cause of death in women of reproductive age.20 This disparity is due to a lack of screening programs, in part due to rural and socioeconomic factors. Cervical cancer in women over 65 accounts for 25% of new cases and 41% of deaths from this disease. Increasing age is associated with increased stage at time of presentation, yet in regions where the older women have been aggressively screened, their death rates have declined. Less than 50% of women over 65 years of age have been screened for cervical cancer (Table 1.8). Use of surgery, radiotherapy, or chemotherapy should not be restricted on the basis of age alone.

Table 1.8 Pap screening for cervical cancer Age

% tested

18–39

81

40–59

67

>60

52

Source: US Centers for Disease Control.

Leukemia Chronic lymphocytic leukemia (CLL) is one of the principal hematologic neoplastic diseases of older persons, and its incidence may be greater than reported, since its indolent nature may result in its failure to be registered in tumor registries. Treatment is usually initiated when specific signs or symptoms occur. Chemotherapy in persons over 70 is implied to be of benefit.

Aging and cancer

13

Nearly 60% of patients with acute myeloid leukemia (AML) are older than 60. Treatment in this age group has improved. As each decade has passed, the complete remission rate for those surviving treatment has increased.1 The duration of remission and the survival time of older responders to therapy are comparable to those of younger patients, although the older patient is at a greater risk during induction therapy because of uncontrolled infections during the neutropenic phase. Increasing age is associated with a lower complete response rate, slower neutrophil recovery, and longer hospitalizations than younger adults.21 A common feature of AML in the elderly is myelodysplasia, for which several new drugs are being investigated. For the older patient with AML and good functional status, induction chemotherapy is preferred. Since the use of hematopoietic growth factors in AML has been associated with reduced infection, shortened hospitalization, and improved survival, it has been recommended that hematopoietic growth factors be used routinely in persons aged 70 and over during moderately toxic chemotherapy.22 Nevertheless, for many patients, palliative intervention remains an appropriate option. Hodgkin lymphoma Hodgkin lymphoma has a bimodal age incidence curve, peaking in the late 20s then declining to age 45, after which the incidence increases steadily with age. Age is a major prognostic factor influencing treatment response, duration of response, and survival. In advanced disease, the response rate to chemotherapies was lower in patients over 60 compared with younger persons. In a national pattern-of-care study, as the age of the patient at diagnosis increased, the survival decreased.23 Analysis revealed that both age and stage, independent of each other, are significant prognostic factors for Hodgkin lymphoma. There may be biologic differences in patients at advancing age, resulting in a poorer prognosis. Non-Hodgkin lymphoma The incidence of non-Hodgkin lymphoma (NHL) has dramatically increased over the past decade, and is expected to continue to rise. The disease presentation is the same in younger and older persons. Stage III and IV lymphocytic NHL have an indolent course and are responsive to chemotherapy, yet do not attain complete remissions. Incomplete remission may not require maintenance chemotherapy. A few elderly patients may never require treatment.24 Patients older than 65 have had greater treatment-related toxicity, lower complete response rates, and decreased survival when compared with younger patients. Overall survival is affected by comorbid conditions.25 Treatment considerations An age bias in the management of cancer has been recognized in a number of studies.1 Attitudes toward aging, rather than scientific facts, have affected decisions by physicians. Chronologic age is associated with perceived negative characteristics, including poor prognosis, cognitive impairment, decreased quality of life, limited life expectancy, and


14

decreased social worth. Older patients are discriminated against based on chronologic age. Greater age has been associated with less screening for cancer, less staging of diagnosed cancer, less aggressive therapy, or no treatment at all. Fewer older women have had a Pap test for cancer. Women over 80 have had fewer mammographic screenings for breast cancer, and staging has been less vigorous. Because of older patients’ impaired physiologic reserve and a fear of excessive operative mortality in older patients with cancer, some physicians have been reluctant to recommend curative major surgical procedures and to favor more conservative treatment, thereby losing the potential curability of cancer by surgery. Study of the outcomes of surgery in patients of 90 and older revealed that these extremely old patients fared quite well, and survival at 5 years was comparable to that expected. During the 10-year period of study from 1975 through 1985, operative rates increased in this age group,26 and continue to increase. Advanced age is not a contraindication to major surgery, providing that the presence of comorbid diseases will not influence the potential mortality. Radiotherapy or chemotherapy is often less aggressive as well, and, for some patients, no treatment is administered. The lack of progress against cancer in older patients may be due to failure to apply standard therapy as fully for them as for younger people. The decision on management of cancer in older persons should be based upon the individual needs of a patient and not upon chronologic age alone. Clinical trials Patients over 65–70 are generally under-represented in cancer treatment trials. Data on cooperative group phase III studies have shown a declining entry in the past 5 years of patients over 65. Age restriction is not a valid eligibil-ity criterion for US National Cancer Institute trials. Possible explanations have been suggested.27,28 These include: (i) the presence of comorbidity; (ii) a research focus on aggressive therapy, the toxicity of which is unacceptable to the elderly; (iii) fewer trials being available aimed at older patients; (iv) exclusion of older persons based on criteria for eligibility in a trial; (v) limited expectations for long-term benefit by providers, relatives, and patients; (vi) lack of financial social, and logistic support for participation in trials; and (vii) failure to refer patients to centers where trials are available. Because of the importance of research on the interaction between chronologic age and effectiveness of therapy, older patients should be allowed and encouraged to enroll in clinical trials. The apparent discrimination in not treating older patients as aggressively as younger patients, and in excluding older patients from research trials, is not justified. Costs The rapid growth in the older population and their increased utilization of medical care is a major determinant of increasing healthcare costs in the USA. Medicare expenditures for healthcare services continue to expand, despite efforts to the contrary. Some of the expanding costs are due to the growing fraction of Medicare providers in specialty fields,

Aging and cancer

15

the expansion of technologies that are useful to patients, services that became available for conditions that were untreatable 30 years ago, and the ever-enlarging older population. Currently, there are four working Americans supporting each retiree. In the future, there will be only two per retiree, and there will be fewer sons and daughters to support and care for older persons. As more people live long enough to develop cancer, chronic illnesses, disability, and dependence, more relatives in their 50s and 60s will be facing the concern and expense of caring for them. The government will not be able to meet the cost. Hence, plans need to be developed that allow people to save for their own retirement healthcare needs. As the demand for long-term care facilities increases, longterm care will become the most important healthcare issue. In the next several decades, geriatric and cancer care will become a significant medical, public health, economic, and social challenge. Manpower In the evolution of the subspecialty of medical oncology, the initial definition of the subjects of relevance of this subspecialty included gerontology.29 It was perceived that cancer in the aging population would be a major health problem. The number of certified medical oncologists has grown at an awesome rate since 1973, and is now well over 8100. Yet a surplus of medical oncologists is not anticipated. The need for oncology manpower will surpass that for cardiology. Because of the increased number of visits for their therapy, an expanded need for more oncologists must be anticipated to meet the requirements for care of patients with cancer in the early part of the 21st century.30,31 It is reasonable to assume that primary care physicians will be more responsible for teaching cancer prevention, emphasizing early cancer detection, and administering some of the standard therapies. Moreover, since many cancers are now cured, the overall healthcare of the patient becomes increasingly important as that patient continues to grow older. Conclusions The US population is growing older. Physicians need to be more familiar with the medical needs of older patients and their greater chance of developing cancer. The importance of geriatric oncology was recognized a quarter of a century ago when the subjects of relevance in medical oncology training were specified. Primary care physicians and oncologists need to be prepared for the impending increase in the number of older persons with cancer. References 1. Kennedy BJ. Aging and cancer. J Clin Oncol 1988; 6:1903–11. 2. Proceedings of National Conference on Cancer and the Older Person. Cancer 1994; 74: No. 7. 3. Yancik R, Havlik RJ, Wesley LON et al. Cancer and comorbidity in older patients: a descriptive profile. Ann Epidemiol 1996; 6:399–412. 4. Cohen HJ. Biology of aging as related to cancer. Cancer 1994; 74: 2092–100.


16

5. Balducci L, Hardy CL, Lyman GC. Hematopoietic reserve in the older cancer patient; clinical and economic considerations. Cancer Control 2000; 7:539–47. 6. Goodwin JS, Samet JM, Hunt WC. Determinants of survival in older cancer patients. J Natl Cancer Inst 1996; 88:1031–8. 7. Muss HB, Cohen HJ, Lichtman SM. Clinical research in the older cancer patient. Hematol Oncol Clin North Am 2000; 14:283–91. 8. Spencer G. Projections of the population of the United States, by age, sex, and race: 1988–2080. Current Population Reports, Series P-25, No. 1018. Washington, DC: US Government Printing Office, 1989. 9. US Census Bureau, 1999 Survey. Washington, DC: US Census Bureau, 2000. 10. Tauber CM. Sixty-five plus in America. Revised edition. Current Population Reports, Special Studies. Washington, DC: US Government Printing Office, 1993:23–178 RV. 11. Manton KG, Vaupel JW. Survival after the age of 80 in the United States, Sweden, France, England, and Japan. N Engl J Med 1995; 333: 1232–5. 12. Bushhouse S, Punyko J, Soler J, Cords J. The occurrence of cancer in Minnesota, 1988–1996: incidence, mortality, trends. Minneapolis: Minnesota Cancer Surveillance System, Minnesota Department of Health, August 1999. 13. Polenak AP. Projected number of cancers diagnosed in the US elderly population, 1990 through 2030. Am J Publ Health, 1994; 84:1313–16. 14. Division of Chronic Disease Control. Years of potential life lost due to cancer—United States, 1968–1985. JAMA 1989; 261:209. 15. Greenlee RT, Hill-Harmon MB, Murray T, Thun M. Cancer statistics, 2001. CA Cancer J Clin 2001; 51:15–36. 16. Trontell AE, Franey EW. Use of mammography services by women aged ≥65 years enrolled in Medicare—United States, 1991–1993. JAMA 1995; 274:1420. 17. Silliman RA, Balducci L, Goodwin JS et al. Breast cancer care in old age: what we know, don’t know, and do. J Natl Cancer Inst 1993; 85:190–9. 18. Sargent D, Goldberg R, MacDonald J et al. Adjuvant chemotherapy for colon cancer (cc) is beneficial without significant increased toxicity in elderly patients: results from a 3351 pt. metaanalysis. Proc Am Soc Clin Oncol 2000; 19:241a (Abst 933). 19. Cohen HJ, Cox E, Manton K, Woodbury M. Malignant melanoma in the elderly. J Clin Oncol 1987; 5:100–6. 20. Boffeta P, Parkin DM. Cancer in developing countries. CA Cancer J Clin 1994; 44:81–90. 21. Schiffer CA, Mclntyre OR. Age related changes in adults with acute leukemia. In: The Underlying Molecular, Cellular. and Immunological Factors in Cancer and Aging (Yang SS, Warner HR, eds). New York: Plenum Press, 1993:215–29. 22. Balducci L, Yates J. General guidelines for the management of older patients with cancer. NCCN Proceedings. Oncology 2000; 14:221–7. 23. Kennedy BJ, Fremgren AM, Menck HR. National Cancer Data Base report on Hodgkin’s disease, 1985–1989 and 1990–1994. Cancer 1998; 83:1041–7. 24. Rosenberg SA. Non-Hodgkin’s lymphoma—selection of treatment on the basis of histologic type. N Engl J Med 1979; 301:924–8. 25. Lichtman SM. Lymphoma in the older patient. Semin Oncol 1995; 22(Suppl 1): 25–8. 26. Hosking MP, Warner MA, Lobdell CM et al. Outcomes of surgery in patients 90 years of age and older. JAMA 1989; 261:1909–15. 27. Trimble EL, Carter CL, Cain D et al. Representation of older patients in cancer treatment trials. Cancer 1994; 74:2209–14. 28. Hutchins LF, Unger JM, Crowley JJ et al. Underrepresentation of patients 65 years of age or older in cancer-treatment trials. N Engl J Med 1999; 341:2061–7. 29. Kennedy BJ, Calabresi P, Carbone P et al. Training program in medial oncology. Ann Intern Med 1973; 78:127–30. 30. Kennedy BJ. The origin and evolution of Medical Oncology. Lancet 1999; 354(Suppl): 41.

Aging and cancer

17

31. Kennedy BJ. Aging and cancer. Oncology 2000; 14:1731–40.

2 Essentials of clinical decision analysis: A new way to think about cancer and aging Gary H Lyman Introduction Clinical medicine is fundamentally an effort to make decisions in the setting of what is often considerable uncertainty based on a set of facts and a set of rules that we apply to these facts.1 Medical knowledge may be derived from personal experience as well as systematic research. Our knowledge base represents an enormous collection of facts as well as opinion gathered over years of formal education, training, and experience in both preclinical and clinical settings. On the other hand, our understanding of how to gather information and evaluate it in order to arrive at correct decisions is obtained in a much less direct manner, largely through observation of experienced clinicians and trial and error. It is only in recent years that the discipline of decision analysis has been extended to clinical medicine from other disciplines.2,3 The factual foundation of our clinical knowledge is based upon objective evidence derived from both published and unpublished research. Such evidence will vary substantially over time and from one setting to another, while the rules of reasoning that we use to make decisions based on this information are fundamentally the same regardless of the setting. However, clinical reasoning skills vary greatly from clinician to clinician, and for a physician they vary from subject to subject.4–6 The focus of this chapter is on the application of these methods and the unique features of cancer in the elderly that should be considered in making clinical decisions. In our search for the truth, clinicians often utilize both deductive and inductive reasoning, but, as we shall see, both approaches have their limitations, often leading us to move back and forth between them. Deductive reasoning bases conclusions on the application of a set of rules to a set of presumed true premises. Deduction concludes what would likely be observed if a certain reality exists. For example, hypothesis testing infers the likelihood of certain results under certain conditions being true, such as the null hypothesis of not real treatment difference. Such reasoning assumes a certain falsepositive rate (an alpha or type I error) or false-negative rate (a beta or type II error) and therefore should be considered error-based. While such reasoning is very objective, it cannot be used to expand our understanding and is certainly less useful to clinicians. Inductive reasoning bases conclusions on repeated observation and inferring reality on the basis of these observations, and therefore can be considered evidence-based. Repeated observation is less objective, but can be used to generate new hypotheses. Induction in the form of clinical prediction infers the likelihood of reality based on the data or evidence observed. Neither form of reasoning represents a direct approach to

A new way to think about cancer and aging

19

knowledge or truth. In science and medicine, we often combine these two forms of reasoning to approach the real world. We start off by asking a question or generating a hypothesis, and then generating data by observation or experimentation. Such observations or data analysis allows us to generate new hypotheses, which require further observation and analysis. Even this approach fails to provide any reliable path to definitive answers to our questions about the world, including medical science. Essentials of clinical decision making Decision making in any clinical or public health situation is based on a structuring of the problem, knowledge of the performance of diagnostic tests and therapeutic modalities, and a reasonable understanding of the likelihood and value of various outcomes based on experience or the literature.7,8 The question or decision choice to be made must be explicitly defined. Probabilities and outcomes may be variably derived either from personal judgment based on education and experience or systematic research or from evidence generally derived from the medical literature. In the tradition of evidence-based medicine, the probabilities and outcomes utilized, including clinical, quality of life, and economic measures while considering experience and clinical judgment, should be based on the best evidence available. The randomized controlled trial (RCT) or meta-analyses of RCTs are generally considered among the greatest scientific advances of the 20th century, and results from such trials or reviews represent the best source of evidence when available. Decision making in the elderly patient with cancer requires a specific understanding of the epidemiology and natural history of the disease, as well as the diagnostic, therapeutic, and supportive care strategies available.9 The value of establishing the diagnosis and/or treating elderly patients with cancer may differ from that in younger patients because of such factors as the greater prevalence of cancer and the limited life-expectancy of older patients. The value of early diagnosis of certain cancers as well as the responsiveness to systemic therapy may also differ greatly among cancers afflicting the elderly. Probabilities In the testing situation (screening, diagnostic testing, etc.), the probabilities of interest are the various test performance characteristics as well as the prevalence of the condition in the population under investigation. The major objective of cancer screening and diagnostic testing is to separate those with cancer from those without cancer. Ideally, positive test results should be seen only in those with disease (true positive) and negative test results should be seen only in those without disease (true negative). However, clinical testing is almost always associated with a certain number of false-positive results in those without disease and false-negative results in those with disease. The performance of screening and diagnostic tests is assessed on the basis of several measures (see Appendix 2.2).10–14 The sensitivity of a test is the probability of a positive test result in those with the disease. The specificity of a test is the probability of a negative test result in those without the disease. Of greater interest to clinicians, generally, are the measures of predictive value. The predictive value positive is the probability of the disease in


20

someone with a positive test. Alternatively, the predictive value negative is the probability of being without disease if the test is negative. The predictive value of a test depends not only on the sensitivity and specificity of the test but also on the prevalence of the disease in those being tested. Prevalence represents the probability of disease in the population at a given time. Since the incidence and prevalence of cancer increase dramatically with increasing age, the positive predictive value of a screening or diagnostic test generally increases with increasing age. With increasing disease prevalence, there will be a decreasing proportion of false-positive results, potentially increasing the diagnostic yield per unit cost.15–17 We have observed that physicians frequently overestimate post-test probabilities, particularly when disease prevalence is low in the population.16,17 We believe that healthcare professionals should receive formal training in the proper evaluation of test information.17

Figure 2.1 Graphic representation of the three dimensions of health outcomes: clinical (survival and response), psychological (quality of life and symptoms/toxicity), and economic (costs and charges). Combined measures of outcome include quality-adjusted life-years (QALYs) or the quality-adjusted time without symptoms of disease or toxicity of treatment (Q-TWIST) for the clinical and psychological dimensions, cost-effectiveness (cost per life-year gained) for the clinical


21

and economic dimensions, and costutility (cost per QALY gained) for the clinical, psychological, and economic dimensions. Outcome measures Patient outcomes may be measured in a variety of ways: clinical, quality of life and economic. Perhaps the greatest strength of outcomes analysis is the ability to combine into summary measures clinical, quality of life, and cost outcomes (Figure 2.1). Such combined measures provide powerful and elegant methods for comprehensive comparisons reflecting the impact of cancer and cancer interventions. Clinical outcomes may assess both management benefit and harm.18 Clinical outcomes measured in controlled clinical trials generally refer to treatment efficacy in terms of survival, time to recurrence, or disease-free survival. Outcome measures applied to the population of diseased individuals define treatment effectiveness. Both direct and indirect measures are available. Commonly utilized direct clinical measures of outcome are survival, disease-free survival, and life-expectancy. A survival function represents the cumulative proportion alive or alive and free of disease (disease-free survival) over time. Survival is directly related to the risk of dying over each unit of time (mortality rate). The survival of a group of individuals may be summarized by various measures such as the median (50th percentile) or the proportion alive at certain time points such as 1 or 5 years. Life-expectancy represents the average number of years of life remaining at any given age. In seriously ill patients, including elderly cancer patients, life is relatively short and the mortality rate is approximately constant. When the mortality rate is approximately constant, the relationship between survival and time is described by a declining exponential function. Such an approximation is sufficiently close for almost all decision-making applications. Under the assumption of a declining exponential approximation for life-expectancy (DEALE), life-expectancy is the inverse of the mortality rate. In addition, the total mortality rate may be considered the sum of the agespecific mortality rate and the mortality rates for any disease(s) (see Appendix 2.4). In some clinical settings, the mortality rate may vary over time. In this situation, other models are utilized to estimate life-expectancy. When a patient is likely to experience several different health states over time, a Markov model may be utilized. If the transition probabilities of moving from one health state to another over time are known, lifeexpectancy can be estimated. The Markov model assumes that the transition probability to a new health state is determined by the current health state and not previous states. Quality-of-life considerations can be incorporated by formally assessing patient preferences or utilities for various outcomes and adjusting years of life-expectancy in the form of quality-adjusted life-years (QALYs). A variety of methods are available to adjust clinical outcome measures for the impact on quality of life. Patient willingness to pay to achieve effectiveness or to avoid toxicity can be incorporated into a cost-benefit analysis. Utility analysis attempts to adjust the outcome value based on patient perception of quality of life in different outcome states. After ranking possible outcomes and assigning values of 0 and 1 to those with the lowest and highest quality of life, the intermediate outcomes can be assigned values by means of a standard reference gamble or a time


22

trade-off equating the amount of time in good health to a specified period of time in the disease state. Each of these methods of adjustment has limitations in implementation and interpretation. However, they do begin to address a dimension of management outcome that has not been adequately considered in the past. Costs are generally measured in monetary units such as dollars. Common direct measures of economic impact include costs, charges, and cost-to-charge ratios. Costs represent the product of a measure of activity or resource utilization times the unit costs or cost per unit of activity. Indirect measures of outcome effectiveness include treatment response, duration of response, and time to disease recurrence. Measures of indirect cost include lost income from illness or premature death as well as other costs not directly related to the services provided. Marginal costs as well as marginal effectiveness refer to the differences in these measures between two strategies. In a cost-benefit analysis, benefits must be converted into the common monetary unit. In a cost-effectiveness analysis, the cost for each unit of added effectiveness over time is calculated; this may allow the comparison of different strategies with the same effectiveness measures.

Table 2.1 Clinical decision making: clinical decision models Elements •

The model structure

•

The probabilities

•

Outcome measures (cost and effectiveness)

Strengths •

Evaluation of various choices

•

Threshold and sensitivity analysis

•

Cost-effectiveness and cost-utility analyses

Decision analysis A useful decision model requires three elements (Table 2.1): (i) a structure in the form of a decision tree leading forward from two or more choices at a decision node (represented by a square); (ii) a set of probabilities for each branch in the model leading from a chance node (represented by a circle); and (iii) a value for each possible pathway through the model leading up to a terminal node (represented by an arrow). With each branch that follows a chance event, a probability or probability variable is assigned a baseline value. The baseline value may be derived from the literature or represent personal judgment. Probabilities must be between 0 and 1 and must add up to 1 for the branches of a given chance node. Outcome measures can be formatted in a variety of ways, and often involve either a negative value such as cost or a positive value such as effectiveness. The generation and evaluation of a clinical decision model has a number of important strengths (Table 2.1).


23

The strategy utilized in decision analysis involves determining the decision choice associated with the greatest expected value.7–12 This can be expressed as the greatest expected effectiveness or the least expected cost or cost-effectiveness. Figure 2.2 illustrates a hypothetical decision model or tree for two therapeutic alternatives with uncertainty about the diagnosis of disease. In Figure 2.2(a), the outcome for each treatment/disease pathway is represented as a utility. The benefit of treatment by convention is represented by the difference among treated and untreated individuals with the disease, while the harm or risk of treatment is the difference among treated and untreated individuals without the disease. Similar relations between benefit and risk are illustrated when considering quality of life adjustment (Figure 2.2b) and economic considerations (Figure 2.2c). Once baseline probabilities and outcome values have been assigned, each node can be evaluated by multiplying the outcome value by the probability of each branch and adding the products of the branches from each node together. The expected value therefore represents a weighted sum of the expected values of all possible paths, where the weights are given by the probabilities of the various chance events. The resulting expected value is then utilized as the outcome value for the immediately preceding branch. In this fashion, the model is ‘folded back’, achieving an expected outcome value for each decision choice. The choice associated with the greatest expected value should represent the desired choice for reasonable decision makers. There are times when decisions involve immediate versus delayed effects or costs where decision makers may reasonable differ as to the optimal choice. Confidence limits on the expected value can be estimated if the distribution of the individual probabilities and outcome values are known. Utilizing a Monte Carlo technique, the distribution of expected values can be estimated by sampling the known distributions in the model as the model is evaluated repeatedly.


p, probability of disease; UNN, utility for no treatment and no disease;

24


25

UTN, utility for treatment and no disease; UTD, utility for treatment and disease; UND, utility for no treatment and disease; LE, life-expectancy; LYRX, life-years with treatment; LYC, life-years in control (without treatment); QRX, quality adjustment with treatment; QC, quality adjustment in control (without treatment); QALY, quality-adjusted life-years; QLYG, quality-adjusted life-years gained; QLYL, quality-adjusted life-years lost; CRX, cost associated with treatment; CC, cost associated with control (no treatment).

Figure 2.2 Schematic decision trees for clinical decision making based on utility analysis: model based on choice between treatment and no treatment despite uncertainty concerning diagnosis. The threshold probability of disease (Pthreshold), represents the prevalence of disease at which the expected utility associated with treatment equals that associated with no treatment. This can be found by equating the expected outcomes with and without treatment and then solving for P. (a) Utilities (U) are based on patient preferences for different health states for each pathway through the tree. Benefit is defined as the net positive utility between treatment or no treatment in patients with the disease, while risk represents the net negative utility between treatment or no treatment in individuals without disease. (b) Utilities are based on quality-adjusted life-expectancies associated with different health states and treatment groups. Benefit is defined as the quality-adjusted life-


26

years (QALYs) gained with treatment in those with disease, while risk represents the QALYs lost owing to treatment in individuals without disease. (c) Utilities are based on costs and benefits associated with different health states for each pathway through the tree. Benefit is defined as the gain in life-years with treatment among those with disease, while risk represents the marginal cost associated with treatment in those without disease. One of the most powerful features of decision modeling is the ability to conduct a sensitivity analysis. In a simple (one-way) sensitivity analysis, the baseline value of a variable is varied over the range of possible values. As the value of a variable is varied, the expected outcome value of each choice varies, giving a functional relationship or curve relating the variable and the associated outcome value from the model. The value of the variable at which the curves associated with two choices intersect represents the threshold where the outcome values for two strategies are equal. The threshold is the value of any variable for which the expected values of any two choices are equal. The threshold probability can be calculated by equating the expected values and solving the resulting equation, and is equal to the proportion of the total difference in utilities with treatment observed in patients without disease or the ratio of risk to risk plus benefit (Figure 2.2a). The outcomes can be expressed in more familiar terms such as survival or life-expectancy. However, to solve the equation in order to estimate a threshold, the risk or cost must be expressed in similar terms of reduced life-expectancy or survival. This is most readily accomplished by incorporating utilities in the form of QALYs and considering both the impact of disease and treatment on quality of life (Figure 2.2b). Solving this equation, the threshold represents the proportion of the total change in lifeyears (or QALYs) among both patients with disease and those without disease (benefit plus cost) represented by the loss in life-years or QALYs among those without disease (cost). The threshold is represented as the proportion surviving. Above and below the threshold, one or the other choice is favored on the basis of having the greatest expected value. The values of two variables may be varied simultaneously, generating a threshold function. Obviously, any combination of values of the two variables that do not lie on the threshold curve will result in expected values favoring one strategy or the other. Likewise, the values of three variables may be varied simultaneously, yielding a family of threshold curves. In theory, any number of variables may be varied simultaneously, although such an analysis is limited by the ability to conceptualize and graphically depict such relationships.


27

The application of decision-analytic techniques to clinical medicine in general and the management of the elderly cancer patient in particular have many potential benefits. These strategies force the clinician to explicitly state the question being asked, the data and assumptions to be utilized, and how these will be analyzed to formulate a decision. Different clinicians utilizing the same data and the same logic should arrive at the same conclusion. The ability to assess the effect of variations in the assumptions on the optimal choice in a sensitivity analysis is a major strength of this approach. These techniques should be most helpful clinically in the most complex cases with the greatest degree of uncertainty. Decision analysis should also be a useful aid to teaching students and resident physicians how to utilize clinical data even relatively early in their clinical experience. Decision analysis may also facilitate research into the process of clinical reasoning. Finally, these techniques may be applied to health outcomes and health policy research and facilitate the development of reasonable clinical practice guidelines for management of the elderly cancer patient. Aging and cancer Increasing age represents the single most important risk factor for cancer. As shown in Figure 2.3, the number of cancer deaths in the USA peaks between the ages of 65 and 75 and then decreases owing to competing risks for mortality in the declining population at risk. Cancer incidence and mortality rates, however, continue to increase throughout life, at least up to age 80–85 (Figure 2.4). As shown in Table 2.2, cancer mortality rates

Figure 2.3 Graphic display of cancer incidence rates and the number of new cases for the US population by 5-year


28

age group for the period 1973–98. The cancer incidence rate per 100000 individuals per year is displayed as a line graph while the numbers of new cases (×100) are represented by the vertical bars.

Figure 2.4 Graphic display of cancer mortality and cancer incidence rates for the US population by 5-year age group for the period 1973–98. The cancer mortality rate in deaths per 100000 per year is displayed as solid diamonds. The cancer incidence rate in cases per 100000 per year is displayed as solid squares. The differences in cancer incidence rates and cancer mortality rates by 5-year age group are displayed as vertical bars.


29

Table 2.2 Cancer mortality rates (deaths per 100000 individuals per year)19 Age group

Total

Males

Females

0–4

2.7

2.9

2.5

5–9

2.7

3.0

2.4

10–14

2.7

3.0

2.3

15–19

3.8

4.4

3.1

20–24

5.4

6.5)

4.4

25–29

8.5

8.9

8.0

30–34

14.9

14.0

15.7

35–39

27.4

23.9

30.8

40–44

52.3

48.1

56.4

45–19

100.4

98.3

102.3

50–54

186.2

195.9

176.9

55–59

315.7

353.7

280.6

60–64

506.9

600.0

424.0

65–69

731.1

904.8

586.0

70–74

1001.2

1273.6

791.0

75–79

1231.0

1612.8

965.5

80–85

1518.9

2113.3

1177.1

85+

1776.0

2680.9

1412.0

increase with age more dramatically for males than for females, with a nearly twofold difference in those over the age of 85.19 Cancer incidence and mortality rates have increased considerably over the past several decades in the USA.20,21 Although age-adjusted cancer mortality rates have also increased, most of this increase is attributable to increasing cancer mortality in individuals over the age of 65. Age-specific cancer mortality rates have actually decreased substantially in younger age groups over the past two decades, while they have increased in those 65 and over (Table 2.3). Most of the increase in cancer mortality rates in those 65 and over has been due to lung cancer, with lesser contributions from genitourinary cancer and the hematologic malignancies.


30

Table 2.3 Changes in cancer mortality rates (1950– 98)19 Age group

Mortality rates/100 000/year 1950

1975

Percentage change 1950–98

1998

0–4

11.1

5.2

2.3

−77.5

5–14

6.6

4.7

2.6

−59.6

15–24

8.5

6.6

4.5

−48.2

25–34

19.8

14.6

10.9

−43.6

35–44

64.2

53.9

38.9

−38.4

45–54

175.2

179.2

134.2

−22.6

55–64

394.0

423.2

385.9

−0.7

65–74

700.0

769.8

830.2

19.4

75–84

1160.9

1156.0

1320.3

14.7

85+

1450.7

1437.9

1751.4

21.5

158.1

162.3

161.5

3.1

All ages

The increase in cancer mortality rates among the elderly appears to be related, at least in part, to increasing cancer incidence rates. For some types of cancer, old age represents a poor prognostic factor. This observation most likely relates to the biology of the disease, delays in diagnosis resulting in more advanced stage of disease at presentation, complicating comorbid conditions, and poor tolerance of or poor compliance with potentially effective treatment programs. Older patients are often treated less aggressively based on chronologic age without consideration of functional status and comorbid conditions.22 Elderly patients with cancer appear to do nearly as well as younger patients after adjusting for the type of cancer, tumor stage, comorbid conditions, and treatment.2,23 The outcome of certain malignancies actually appears to favor the elderly, perhaps because of biologic differences in tumor behavior. Table 2.4 illustrates the incidence, mortality, and relative survival of the 10 leading sites of invasive cancer among the elderly. The specialized needs of the elderly cancer patient suggest that attention should be directed toward a better understanding of clinical decision making in this population. Full attention to quality of life and cost, in addition to measures of survival or longevity, is of paramount importance in the elderly cancer patient.3,24 In addition, a better understanding is needed of those factors that influence a clinician’s decisions when caring for elderly cancer patients.25 Optimal decision making in the elderly requires knowledge of the life-expectancy associated with different age groups. Figure 2.5 reveals the relationship between


31

Table 2.4 Cancer incidence, mortality, and survival rates for the 10 leading sites of invasive cancer in those aged 65 and over for the period 1973–9819 Incidencea All sites (invasive)

Mortalitya

5-year relative survival (%)

2151

1068

58.2

Colon/rectum

288

119

61

Lung

349

314

13

Prostate (males)

966

217

97

Breast

262

70.5

87

Bladder

112

26

77

Lymphomas

79

44

47

Pancreas

59

57

3

Uterus (females)

97

22

79

Stomach

44

27

21

Leukemia

52

39

34

a

Per 100000 population per year, age-adjusted to the 1970 US standard population.

Figure 2.5 Graphic display of US population and life-expectancy by 5-year age group. The age-specific US population (×106)


32

for the year 2000 is displayed as shaded vertical bars. Life-expectancy in years for the US population from birth and for 5-year age-specific groups is displayed as solid squares. increasing age and decreasing life-expectancy.19 It is important to note that although lifeexpectancy from birth has increased dramatically since the turn of the 20th century, there has been little increase in the life-expectancy of those aged 65 and over or of the total lifespan (Table 2.5).26 Decision making in the elderly must consider both the increase in cancer mortality and the decrease in life-expectancy with increasing age. Figure 2.6 illustrates this complex relationship by displaying the age-specific loss in life-expectancy due to cancer with age. Clearly, the greatest impact of cancer on years of productive life is in the range of 50–80 years of age. The relative importance of prolonging survival and the acceptability of certain types of discomfort or costs

Table 2.5 Life-expectancy (years)19 From birth

From age 65

Year

Males

Females

Males

Females

1900

46

48

11

12

1910

48

52

11

12

1920

54

55

12

13

1930

58

62

12

13

1940

61

65

12

14

1950

66

71

13

15

1960

67

73

13

16

1970

67

75

13

17

1980

70

78

14

18

1990

72

79

15

19

1999

74

79

16

19


33

Figure 2.6 Graphic display of the annual loss in age-specific lifeexpectancy from cancer (years (×103) for the US population for the year 2000 by 5-year age groups. Also illustrated by darker bars is the proportion of life-expectancy lost from cancer among those aged 65 and over. vary among individuals. Physicians must be aware that such factors as age, race, sex, and socioeconomic status may influence treatment decisions in a subtle and often unrecognized manner. Where feasible, the patient’s values should be incorporated into any decision analysis that is performed.27–29 Appropriate adjustment of survival by the anticipated impact on quality of life is particularly important in decision making in the elderly. This chapter illustrates the usefulness of decision analysis in improving our understanding of those factors important in medical and public health decisions in the elderly. Clinical decision models can be utilized to evaluate virtually any clinical scenario, including screening, prevention, treatment, and supportive care. In screening and prevention strategies, it is assumed that the intervention has the potential to reduce the occurrence or risk of disease, while in treatment and supportive care strategies, it is assumed that it has the potential to reduce the consequences of disease or its treatment. Such decision models can be utilized to evaluate not only complex clinical problems and guide choices but also the impacts of quality of life and cost.30 If differences in clinical or quality-adjusted clinical outcomes are possible, a cost-effectiveness or cost-utility analysis is most commonly employed to evaluate the economic impact of a disease and its treatment. When no difference in clinical or adjusted outcome is anticipated, a costminimization analysis may be the most valuable approach to economic analyses to


34

identify the strategy associated with the lowest costs. The issues related to clinical decision making in elderly patients with cancer will be illustrated with regard to both cancer screening and treatment.

Figure 2.7 Decision tree for a hypothetical cancer screening test. The decision node is illustrated as a rectangle leading to the choice whether or not to screen a population or individual. Patients may or may not have cancer, which is unknown at the time of the decision whether or not to screen. Screening can accurately reflect those with or without disease or may provide false-negative or falsepositive results. The outcomes of interest include both estimated cost and life-expectancy, each of which varies with the pathway through the tree. Cancer screening The ideal test for screening for disease at any age would have perfect sensitivity and specificity and would detect disease early with no cost or toxicity. In addition, when considering screening tests, the disease being sought should be treatable when diagnosed early and yet cause morbidity or even mortality if not detected early. In reality, clinical


35

tests have less than perfect sensitivity and specificity. Tests are often costly, and may be associated with significant morbidity and mortality due either to the testing procedure or to the evaluation of individuals with positive test results. A diagnostic test or treatment associated with only a modest probability of enhancing the beneficial outcome may be justified if it is associated with little or no harmful effect or cost. In contrast, a procedure associated with frequent morbidity or mortality is only justified if it is associated with a high probability of improved patient survival. The impact of any screening test or strategy must ultimately be evaluated in the population to be screened. However, to illustrate issues related to aging and cancer screening, a hypothetical screening test for cancer is presented (Figure 2.7). It is assumed that this test is capable of detecting a cancer earlier than in those not screened. It is also assumed that earlier detection for this cancer can improve survival. The impact of age on the value of this screening test will be assessed with regard to both cost and effectiveness.

Figure 2.8 Graphic displays of sensitivity analyses of life-expectancy for screened and unscreened populations for hypothetical cancer screening test. In (a), life-expectancy in years is displayed on the vertical axis and cancer prevalence with increasing age on the horizontal axis. Changes in life-expectancy for the screened population are displayed as a solid line, whereas those for the unscreened population are shown as a dashed line. The impact of screening on life-expectancy is seen to increase with increasing disease prevalence and age. In (b), marginal cost-effectiveness in cost in dollars per year of lifeexpectancy extended is displayed on


36

the vertical axis and cancer prevalence with increasing age on the horizontal axis. The cost for each life-year extended is seen to decrease with increasing disease prevalence and age. When considering a malignancy for which there is effective treatment when diagnosed early, screening is associated with the greatest expected value for most reasonable assumptions. However, since disease prevalence and thus the positive predictive value increase while life-expectancy decreases with advancing age, the net effectiveness of screening in the elderly is a complex function. The annual incidence of cancer in the general US population over the age of 65 is approximately 2%. Cancer prevalence at any given time in an unscreened population is considerably greater than its incidence because of the accumulation of cases in proportion to the average duration between screen-detected disease and non-screened diagnosed disease. In addition, cancer prevalence varies considerably between the various cancers considered for screening. As shown in Figure 2.8(a), life-expectancy decreases with increasing disease prevalence and therefore increasing age in both screened and unscreened populations. The fall in life-expectancy with increasing cancer prevalence, however, is less rapid in the screened population than in the unscreened population. Therefore, the comparative effectiveness of such screening is greater with increasing age and increasing disease prevalence. Figure 2.8(b) demonstrates that the cost-effectiveness (i.e. cost per life-year gained) of screening improves with increasing disease prevalence and age. Table 2.6 illustrates the effect of age on the cost-effectiveness of screening for a hypothetical malignancy. In this example, it is assumed that the 5-year survival of patients diagnosed routinely at the time of symptom onset is 50%, whereas the survival of those detected by screening while asymptomatic is 90%. Under these assumptions, the optimal effectiveness and cost-effectiveness of screening are observed in individuals 65– 75 years of age. This observation is the result of the increasing positive predictive

Table 2.6 Age and screening test performance Age group Life-expectancy (years) Prevalencea Years gainedb Cost per year ($)c 25–35

50

0.004

540

36919

35–45

41

0.0014

1670

11978

45–55

32

0.0053

5240

3783

55–65

24

0.0132

10290

1899

65–75

16

0.0248

13010

1471

75–85

10

0.0372

11350

1647

85+

6

0.0480

7380

2481

a

Based on a preclinical duration of disease of 24 months.


37

b

Per 100000 individuals screened. Based on a cost of screening of $100 and a cost of diagnosis of $1000.

c

value associated with increasing disease prevalence but a corresponding fall in lifeexpectancy with increasing age. The effectiveness and cost-effectiveness of cancer screening increase as the magnitude of the absolute difference in survival between unscreened and screened individuals increases. Test sensitivity and specificity have noticeably less impact on the calculated expected value. Although cost estimates affect the measured cost-effectiveness, they do not alter the basic relationships and conclusions of the model. Therefore, screening for a malignancy in which early intervention is beneficial can be effectively and costeffectively applied in the elderly. Cancer treatment For cancer treatment decisions, the diagnosis must already be established. Therefore, disease prevalence is no longer an issue in cost-effectiveness analysis. Alternatively, issues related to cost and quality of life often take on even greater importance than with screening. A variety of factors must be considered, including the type, stage, and grade of tumor, the patient’s functional status, the presence of any complicating medical conditions, and a number of psychological and socioeconomic factors. The clinician should consider the age-specific life-expectancy of the individual before committing the patient to treatment associated with considerable morbidity. The types of malignancies that afflict the elderly appear in general to be less responsive to systemic therapy than the malignancies found in younger individuals. Alternatively, many malignancies found in elderly patients are most effectively treated by surgical resection when early diagnosis is possible. When palliation with little impact on longevity is the most likely outcome, the limited life-expectancy of the elderly and quality of life issues may favor no treatment. When highly treatable and potentially curable disorders are involved, the greatest expected value will almost always favor the decision to treat regardless of age. However, since both treatment response and toxicity correlate directly with treatment intensity, the clinician is often faced with very difficult clinician decisions.31 These points can be illustrated by reference to a hypothetical treatment program for advanced cancer shown in Figure 2.9. In this example, we assume that responding patients with a certain malignancy experience a doubling in median survival, although with some risk (5%) of early mortality. Outcome is assessed in terms of both treatment cost and effectiveness. Marginal cost-effectiveness is shown in Figure 2.10 for both unadjusted effectiveness measured in terms of life-expectancy and for quality-adjusted life-expectancy where both non-response and treatment are each associated with a 25% reduction in the quality of life. Often, a utility analysis with formal assessment of patient preferences is required for objective and valid adjustment. The average quality-adjusted


38

Figure 2.9 Decision tree for a hypothetical cancer treatment program. The decision node is illustrated as a rectangle leading to the choice whether or not to treat a population or individual. All patients are assumed to actually have cancer. Whether patients will survive or respond to treatment is unknown at the time of treatment. The outcomes of interest include both estimated cost and life-expectancy, each of which varies with the pathway through the tree. life-expectancy and cost-effectiveness associated with treatment increase as the treatment mortality decreases, the response rate increases, or the impact of treatment on median survival increases (Figure 2.10a). Treatment appears to become reasonably cost-effective above response rates of 30%. Based on initial conditions for individuals over age 65, including a median survival of 1 year untreated, a 5% risk of treatment mortality, and a 50% decrease in the hazard for mortality among responders, the threshold response rate favoring treatment without quality adjustment is 6%. With quality adjustment for both non-response and treatment toxicity as outlined above, a threshold response rate of 22% is estimated above which treatment provides greater quality-adjusted life-expectancy than no treatment. Looking alternatively at the hazard ratio threshold, the ratio below which treatment is favored is 0.84 without quality adjustment and 0.60 with quality adjustment. The impact of the hazard ratio associated with treatment response on cost-effectiveness is


39

illustrated in Figure 2.10(b) for unadjusted conditions as well as with quality-of-life adjustment. Treatment appears to become reasonably cost-effective when the hazard ratio is 0.50 or less. The estimated patient mortality rate includes the disease-specific mortality rate as well as the age-specific mortality rate. Therefore, the response threshold for treatment increases with increasing age owing to a decrease in age-specific life-expectancy. Under the hypothetical conditions illustrated here, treatment of an individual aged 85 or more is favored only when a response rate more than 31% is likely. Likewise, the unadjusted and adjusted hazard ratio thresholds for individuals age 85 and over decrease to 0.81 and 0.49, respectively. As illustrated in Figure 2.10(c), the cost-effectiveness of cancer treatment under these conditions increases with decreased age-specific life-expectancy, rising dramatically after age 75, particularly when quality of life is considered. Clearly, the conditions under which treatment is favored in this treatment model become more restrictive with increasing age. While the treatment response threshold increases with increasing age, treatment may still be favored in responsive malignancies under a wide variety of assumptions. It should be mentioned that available supportive care measures appears to be valuable in elderly patients receiving cancer treatment. In fact, the benefit from such measures appears to be as great as, if not greater than, when applied to younger patients.32 The risk and severity of neutropenic complications, including febrile neutropenia, are greater among the elderly.33,34 The use of hematopoietic growth factors is a good example of the value of supportive measures in elderly patients receiving systemic chemotherapy for moderately aggressive but responsive malignancies. The colony-stimulating factors such as granulocyte colony-stimulating factor (G-CSF) have been shown to reduce the severity and duration of neutropenia as well as the incidence of febrile neutropenia and documented infections associated with various systemic cancer chemotherapy regimens for a variety of malignancies.35 The effectiveness of the colony-stimulating factors has been studied in elderly patients with lymphomas and acute leukemia and has been found to be at least as effective as in younger patients. In a recent meta-analysis of eight trials of elderly patients with non-Hodgkin lymphoma (NHL) receiving CHOP-like regimens, the summary risks of severe neutropenia and febrile neutropenia are 66% and 25%, respectively, across these trials.36 In a series of 577 patients with intermediate-grade NHL, older patients experienced significantly more febrile neutropenia.37 In addition, older patients received significantly fewer courses of CHOP and, in a multivariate analysis, received significantly lower dose intensity than younger patients. A recent study of nearly 80000 episodes of febrile neutropenia at 115 academic medical centers demonstrated that patients 65 years of age


40

Figure 2.10 Graphic displays of two-way sensitivity analyses for a hypothetical cancer treatment program with and without quality of life adjustment. In each plot, cost-effectiveness with treatment is shown on the vertical axis.


41

In (a), the response rate as the proportion responding is displayed on the horizontal axis. The cost per lifeyear extended with treatment is seen to decrease with increasing rate of response to the treatment. The impact of treatment on cost-effectiveness when the impact on quality of life is considered is seen to be less, and only at higher response rates than when unadjusted life-expectancy alone is considered. Treatment appears to become reasonably cost-effective above a response rate of 30%. In (b), the hazard ratio for mortality between treated and untreated patients is displayed on the horizontal axis. The cost per life-year extended with treatment is seen to decrease with decreasing hazard ratio as an indicator of increasing treatment effect. The impact of treatment on costeffectiveness when the impact on quality of life is considered is seen to be less, and only at lower hazard ratios than when unadjusted life-expectancy alone is considered. Treatment appears to become cost-effective when associated with a hazard ratio of 0.50 or less. In (c), the age-specific lifeexpectancy associated with increasing age groups is displayed on the horizontal axis. The cost per life-year extended with treatment is seen to increase with decreasing age-specific life-expectancy associated with increasing age. The impact of treatment on cost-effectiveness when the impact on quality of life is


42

considered is less, and is lost at a younger age than when unadjusted life-expectancy alone is considered. or older who develop febrile neutropenia experience nearly twice the risk of death of younger patients.38 The meta-analysis of three RCTs of older patients receiving CHOPlike chemotherapy without and with G-CSF support demonstrated risks of 82% and 50%, respectively, for grade IV neutropenia and 40% and 25%, respectively, for febrile neutropenia.36 Thus, G-CSF appears to be as effective in the elderly as in younger patients. In fact, the National Comprehensive Cancer Network (NCCN) Guidelines Advisory Panel for the management of older individuals has recommended routine primary prophylaxis with G-CSF in patients aged 70 and more receiving chemotherapy intensity-equivalent to CHOP. They have also recommended that hemoglobin levels in such patients be kept at or above 12g/dl, utilizing recombinant erythropoietin if necessary.39 Discussion Managing the elderly cancer patient involves decisions based on a wide variety of factors aimed at providing the patient with the optimal duration and quality of life.40 Careful attention to the entire patient situation, familiarity with advances in cancer diagnosis and treatment, and an understanding of the rational use of clinical data and measured outcomes should assist physicians in making the appropriate clinical decision for each patient. The risk of most cancers increases progressively with increasing age. Based on the observed natural history of many cancers affecting the elderly and the availability of effective treatment modalities when tumors are localized, early and accurate detection appears to offer the best opportunity for improving cancer survival in the elderly. Several available cancer screening strategies have been shown to be cost-effective when applied to an elderly population. Current recommendations for cancer screening among individuals aged 50 and more are presented in Table 2.7. Similarly, increasing attention is being focused on methods of cancer prevention. The application of such methods, often associated with lower levels of toxicity than active treatment, to a higher-risk subgroup such as the elderly offers tremendous opportunities. Tamoxifen chemotherapy among others may represent the beginning of a very promising method of cancer control in the susceptible elderly population. The value of available treatment strategies in treating elderly patients with malignancy is perhaps less clear, and depends greatly upon the type of cancer involved and the treatment strategy utilized, with its associated toxicity. Malignancies affecting the elderly are often considered less responsive to treatment than those more commonly seen in younger patients. In addition, elderly patients with their more frequent comorbidities appear to represent a more vulnerable population for the adverse consequences of cancer treatment. However, several studies have demonstrated that elderly patients selected on the basis of underlying risk factors tolerate definitive cancer treatment, including surgery, radiation therapy, and chemotherapy.23,24


43

The only potential for cure in most elderly patients with malignancy is provided by early and complete surgical removal. The clinician must recognize, however, that major surgery is associated with greater risk in the elderly than in younger patients, largely due to the increased frequency of comorbid medical disorders.41 The greater operative risk among the elderly is most problematic when palliation is the goal, rather than when curative resection is undertaken.42 Several malignancies may be cured or controlled effectively by the application of radiation therapy. This is often effective in relieving tumor symptoms related to compression and obstruction in patients with advanced disease. The therapeutic ratio of normal tissue tolerance to tumor lethal dose falls with increasing age.43 Systemic chemotherapy is capable of prolonging the survival of patients with a variety of advanced malignancies, with cure being possible in such disorders as lymphomas, breast cancer, and small cell lung cancer. The magnitude and duration of treatment response often depend directly on treatment intensity. The greater the impact of treatment on prolonging patient survival, the greater is the toxicity that is generally considered acceptable. On the other hand, the more that quality of life is compromised by treatment, the less important mere prolongation of survival becomes. When chemotherapy is administered with the intention of prolonging survival, dose reduction may significantly compromise disease control.44 The toxicity of chemotherapy in the elderly may be increased by the associated physiologic and pathologic changes that occur with aging.

Table 2.7 Recommendations for cancer screening over the age of 5047 Cancer

Procedure

Recommended frequency

Cervix

Papanicolaou test

Yearly until 3 consecutive negative tests, then every 3 years

Breast

Self-examination

Monthly

Physical examination

Yearly

Mammography

Yearly

Colon/rectum Digital rectal examination

Yearly

Fecal occult blood test

Yearly

Sigmoidoscopy

Every 3–5 years

Digital rectal examination

Yearly

Prostate-specific antigen

Yearly

Uterus

Endometrial sample

Once at menopause

Ovary

Pelvic examination

Yearly

Multiple

General physical examination

Yearly

Prostate

chemotherapy on proliferating normal elements, such as hematopoietic stem cells, appear to occur more frequently or severely among the elderly owing to age-related decreases in


44

The acute toxic effects of hematopoietic stem cell reserves. These effects may also be increased in patients exposed to previous treatment and in those with reduced functional and nutritional status that limits tolerable treatment intensity. It should be remembered that hormonal manipulation may produce tumor regression with acceptable toxicity in a variety of malignancies, including breast, prostate, and uterine cancers.45 Elderly cancer patients should be considered potential subjects for approved clinical trials, with the exception of those with serious complicating medical conditions and those incapable of informed consent. Elderly patients eligible for prospective multi-institutional clinical trials have been found to experience no increase in the frequency or severity of chemotherapy toxicity.46 In addition, elderly patients in these studies did not differ in important risk factors or compliance with treatment dosage and had equivalent response rates to younger patients. Although the tumor response and toxicity associated with systemic treatment depend more on physiologic factors than on actual age, experimental drugs should generally be avoided in the very elderly. The malignancies afflicting the elderly are less likely to be those that respond to new treatment modalities. In addition, unusual and potentially life-threatening toxicities must be anticipated in this group. If experimental treatment is undertaken, it should be performed as a part of a well-designed, controlled clinical trial with fully informed consent. When aggressive treatment approaches are not a reasonable consideration, much may still be offered to the aged cancer patient, including the control of pain and other symptoms of the underlying malignancy. Aggressive psychosocial support is essential in managing the elderly cancer patient. Owing to the limitations on life-expectancy and frequent comorbid conditions in the elderly, quality of life must be a primary concern of the treating clinician. Decisions to limit treatment in the elderly cancer patient with untreatable or refractory disease must also eventually be considered. Decision analysis provides both a framework for thinking about healthcare in the elderly and a fertile area for methodologic and healthcare outcomes research. Decision analysis is particularly suited to assessing the usefulness of prevention and earlydetection strategies in complex settings with mixed outcomes, as exemplified in the elderly. Such an approach is particularly valuable in situations where a decision based on simple survival is incomplete or unsatisfactory. In healthcare planning for the elderly, any useful medical and public health strategy must consider performance outcome in terms of both benefits and risks, including costs. Decision analysis is ideally suited for assessing the value of new therapeutic strategies, as well as technologies aimed at reducing disease and treatment-related toxicity. Finally, it provides a usefiil framework for continuous objective evaluation of rapidly evolving clinical strategies in an era of increasing health awareness and cost containment. The application of decision analytical methods to healthcare in the elderly should not only improve our understanding of this rapidly expanding field but also result in improved quality of care and quality of life for the elderly patient with cancer. References 1. Kahneman D, Slovic P, Tversky A. Judgement under Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press, 1982. 2. Pauker SG, Kassirer JP. Decision analysis. N Engl J Med 1987; 316: 250–8.


45

3. Kassirer JP, Moskowitz AJ, Lau J, Pauker SG. Decision analysis: a progress report. Ann Intern Med 1987; 106:275–91. 4. Albert DA, Munson R, Resnik MD. Reasoning in Medicine: An Introduction to Clinical Inference. Baltimore: John Hopkins University Press, 1988. 5. Sox HC, Blatt MA, Higgins MC, Maston KI. Medical Decision Making. Boston: Butterworth, 1988. 6. Kassirer JP, Gorry GA. Clinical problem solving: a behavioral analysis. Ann Intern Med 1978; 89:245–55. 7. Weinstein MC, Fineberg HV. Clinical Decision Analysis. Philadelphia: WB Saunders, 1980. 8. Kong A, Barnett GO, Mosteller F, Youtz C. How medical professionals evaluate expressions of probability. N Engl J Med 1986; 315: 740–4. 9. Balducci L, Lyman GH. Cancer in the elderly. Epidemiologic and clinical implications. Clin Geriatr Med 1997; 13:1–14. 10. Wasson JH, Sox HC, Goldman L, Neff RK. Clinical prediction rules: applications and methodological standards. N Engl J Med 1985; 313: 793–799. 11. Schwartz S, Griffin T. Medical Thinking: The Psychology of Medical Judgement and Dedsion Making. New York: Springer-Verlag, 1986. 12. Schwartz WB, Gorry GA, Kassirer JP, Essig A. A decision analysis and clinical judgment. Am J Med 55:459–72. 13. Mushlin AI. Diagnostic tests in breast cancer: clinical strategies based on diagnostic probabilities. Ann Intern Med 1985; 103:79–85. 14. Rembold CM, Watson D. Posttest probability calculation by weights: a simple form of Bayes theorem. Ann Intern Med 1988; 108:115–20. 15. Sox HC. Probability theory in the use of diagnostic tests: an introduction to critical study of the literature. Ann Intern Med 1986; 104: 60–6. 16. Griner PF, Mayewski RJ, Mushllin AI, Greenland P. Selection and interpretation of diagnostic tests and procedures: principles and applications. Ann Intern Med 1981; 94:553–600. 17. Health and Public Policy Committee. American College of Physicians. The use of diagnostic tests for screening and evaluating breast lesions. Ann Intern Med 1985; 103:147–51. 18. Djulbegovic B, Cantor A, Lyman GH, Ruckdeschel JC. Understanding treatment benefits and harms. Evidence-Based Oncol 2000; 1: 66–8. 19. Vital Statistics of the United States 1950–2000. Washington, DC: US Government Printing Office, 2001. 20. Cancer in Florida, 1981–1983. Tallahassee, FL: Health Program Office, Epidemiology Program, Department of Health and Rehabilitative Services, 1986. 21. SEER Cancer Statistics Review 1973–1998. Washington, DC: US Government Printing Office, 2000. 22. Greenfield S, Blanco DM, Elashoff RM, Gaaz PA. Patterns of care related to age of breast cancer patients. JAMA 1987; 251:2766–70. 23. Peterson BA, Kennedy BJ. Aging and cancer management. Part 1: Clinical observations. Cancer 1979; 29:322–32. 24. Butler RN, Gastel B. Aging and cancer management: research perspectives. Cancer 1979; 29:322–32. 25. Beghe’ C, Balducci L. Geriatric oncology: perspectives from decision analysis. A review. Arch Gerontol Geriatr 1990; 10:141–62. 26. Miller BA, Ries LAG, Hankey BF et al (eds). SEER Cancer Statistics Review 1973–1990. Bethesda, MA: National Cancer Institute, NIH Publication 93–2789, 1993. 27. Brody DS. The patient’s role in clinical decision making. Ann Intern Med 1980; 93:718–22. 28. Lo B, Jonsen AR. Clinical decisions to limit treatment. Ann Intern Med 1980; 93:764–8. 29. Beck Jr, Kassirer JP, Parker SG. A convenient approximation of life expectancy (the DEALE). 1. Validation of the method. Am J Med 1982; 72:883–8.


46

30. Lyman GH, Kuderer N, Balducci L. Cancer care in the elderly: cost and quality of life considerations. Cancer Control 1998; 5:347–54. 31. Extermann M, Balducci L, Lyman GH. What threshold for adjuvant therapy in older breast cancer patients? J Clin Oncol 2000; 18: 1709–17. 32. Balducci L, Hardy CL, Lyman GH. Hematopoietic growth factors in the older cancer patient. Curr Opin Hematol 2001; 8:170–87. 33. Lyman GH, Lyman C, Ogboola Y. Risk models for the prediction of chemotherapy-induced neutropenia. Neutropenia Oncol 2001; 1:2–7. 34. Intragumtornchai T, Sutheesophon J, Sutcharitchan P et al. Leuk Lymphoma 2000; 37:351–30. 35. Lyman GH, Kuderer NM, Djulbegovic B. Prophylactic granulocyte colony-stimulating factor in patients receiving dose intensive cancer chemotherapy: a meta-analysis. Am J Med 2002; 112:406–11 36. Lyman GH, Balducci L, Agboola Y. Use of hematopoietic growth factors in the older cancer patient. Oncol Spectrum 2001; 2:414–21. 37. Morrison VA, Picozzi V, Scott S et al. Clin Lymphoma 2001; 2:47–56. 38. Lyman GH, Kuderer NM, Agboola O et al. Blood 2001; 98:432a. 39. Balducci L, Lyman GH. Patients aged >70 are at high risk for neutropenic infection and should receive hemopoietic growth factors when treated with moderately toxic chemotherapy. J Clin Oncol 2001; 19:1583–5. 40. Balducci L, Lyman GH, Fabri PJ. Management of cancer in the aged. Comp Therap 1996; 22:88–93. 41. Sherman S, Suidot CE. The feasibility of thoracotomy for lung cancer in the elderly. JAMA 1987; 258:927–30. 42. Lewis AAM, Khoury GA. Resection for colorectal cancer in the very old: Are the risks too high? BMJ 1988; 296:459–61. 43. Samet J, Hunt WC, Key C et al. Choice of cancer therapy varies with age of patient. JAMA 1986; 225:3385–90. 44. Frei E III, Canellos GP. Dose: a critical factor in cancer chemotherapy. Am J Med 1980; 69:585–94. 45. Extermann M, Balducci L, Lyman GH. Optimal duration of adjuvant tamoxifen treatment in elderly breast cancer patients: influence of age, comorbidities and various effectiveness hypotheses on life expectancy and cost. Breast Dis, 1996; 9:327–39. 46. Begg CB, Cohen JL, Ellerton J. Are the elderly predisposed to toxicity from cancer chemotherapy? Cancer Clin Trials 1980; 3:369–74. 47. Smith RA, Mettlin CJ, Davis KJ, Eyre H. American Cancer Society guidelines for the early detection of cancer. CA Cancer J Clin 2000; 50:34–9. 48. Lyman GH, Kuderer NM. Diagnosis and treatment of cancer in the elderly: cost-effectiveness considerations. In: Comprehensive Geriatric Oncology, 2nd edn (Balducci L, Lyman GH, Ershler WB, Extermann M, eds). London: Martin Dunitz, 2004:510–24.

Appendix 2.1: Glossary Probability A number between 0 and 1 representing the likelihood of an event. Odds The ratio of the probability that an event occurs divided by the probability that the event does not occur. Conditional probability The probability of an event given the occurrence of another event. Prior probability The pretest probability of an event or the prevalence.


47

Posterior probability The conditional probability of an event given that another event or a specific test outcome has occurred. True-positive rate The probability of a positive test result in diseased individuals (sensitivity). False-positive rate The probability of a positive test result in those without disease. True-negative rate The probability of a negative test result in those without disease (specificity). False-negative rate The probability of a negative test result in those without disease. Predictive value positive The probability of disease in those with a positive test result. Predictive value negative The probability of no disease in those with negative test results. Sensitivity analysis A study of changes in outcome measures with changes in probabilities, value outcomes, or decision assumptions. Life-expectancy The average life remaining for individuals of a given age. Expected value The average outcome value over possible outcome paths, with the value of each path being weighted by the probability of the path. Cost-effectiveness The cost for each unit of outcome value gained, such as years of additional life-expectancy. Appendix 2.2: Test performance The following summarizes test performance characteristics useful in decision analysis based on probability theory. Here P(X) is defined as the probability of an event X. P(X|Y) represents the conditional probability of event X given that event Y has occurred. The odds of X is defined as P(X)/[1−P(X)]. Sensitivity=P(positive test|disease) Specificity=P(negative test|no disease) Predictive value positive=P(disease|positive test) Predictive value negative=P(disease|negative test)


48

Appendix 2.3: Expressions for Bayes’ Theorem •

•

• ln(post-test odds)=ln(pretest odds)+ln(LR) where ln indicates the natural logarithm

S=S0 e−mt

Appendix 2.4: Declining exponential approximation for lifeexpectancy (DEALE)

where S0=number of patients alive at time 0 S=number of patients alive at time t e=base of natural logarithms m=mortality rate:

See also Appendix 42.1 in Chapter 42 of this volume.48


49

PART 2 Epidemiology

3 Cancer mortality in the elderly, 1960–98: A worldwide approach Carlo La Vecchia, Franca Lucchini, Eva Negri, Fabio Levi Introduction Between the 1950s and the early 1990s, there was a general tendency towards rising cancer mortality, and towards leveling of differences in certified cancer mortality in the elderly population in various areas of the world.1,2 These trends were interpreted by some authors as indicators of an ongoing generalized cancer epidemic.3,4 However, there were substantial limitations and uncertainties in the reliability and validity of cancer death certification and their trends in the elderly, and changes in certified mortality for several sites may well reflect improved ascertainment, increased use of screening and diagnostic techniques in the elderly, and, in greater generality, changes in medical practice. Still, there was no widespread and generalized rise in cancer mortality in the elderly, with the major exception of lung and other tobacco-related neoplasms. Some decline in overall cancer mortality from the late 1970s onwards has been reported from the USA5–7 and Western Europe.8–10 However, trends in the elderly population up to the early 1990s tended systematically to be less favorable.2–4,11 This may be due to a different cohort pattern of cancer mortality across various generations and hence age groups,12 to more substantial changes in diagnosis and certification accuracy in the elderly,2,13 to a lower impact of earlier diagnosis and improved treatment in the elderly,14,15 or to contributions from various factors. Given also their particular health relevance, it is therefore important that recent trends in cancer mortality in the elderly be monitored. Along this line, we considered mortality from six major cancer sites plus total cancer mortality at age 65–84 in Europe, the USA, and Japan up to 1998. Materials and methods Official death certification numbers for 22 European countries (the 15 countries of the European Union, EU, plus 7 others), excluding Albania and a few countries with a population of less than 1 million (i.e. Andorra and Liechtenstein), the USA, and Japan were derived from the World Health Organization (WHO) database. During the calendar period considered (1960–1998), three different Revisions of the International Classification of Diseases (ICD) were used.16–18 Classification of cancer deaths were thus recoded, for all the calendar periods, according to the 9th Revision (ICD-9).17 To improve


52

comparability of data throughout different countries and calendar periods, we have pooled together all intestinal sites, including the rectum. Estimates of the resident population, generally based on official censuses, were obtained from the same WHO databank. From the matrices of certified deaths and resident populations, age-specific rates for each 5-year age group considered (65–69 to 80–84) and calendar period were computed. Age-standardized rates were based on the World Standard Population.19 Results Figure 3.1 gives trends in age-standardized mortality at age 65–84 from all cancers and selected cancer sites in the EU, other European countries, the USA, and Japan over the period 1960–97. Most of the following comments, however, refer to the trends observed over the last decade, i.e. between 1985–89 and 1995–98. After earlier rises, total cancer mortality at age 65–84 has been declining in the EU (from 1457/100000 in 1985–89 to 1378/100000 males in 1995–98, −5.5%; from 712 to 690/100000 females, −4.5%), in US males (from 1266 to 1237/100000, −2.3%), but not females (from 732 to 764/100000, +4.5%), and in Japanese females (from 557 to 526/100000, −5.6%), but not males (from 1218 to 1295/100000, +6.3%). Cancer mortality in the elderly rose for both sexes in Eastern Europe, from 1294 to 1359/100000 for males, +5.1%; from 669 to 688/100000 for females, +2.7%. Gastric cancer mortality steadily declined in all the areas considered, and the fall over the last decade was proportionally larger in the EU (about 30% in both sexes) as compared with eastern Europe (−23%), the US (−20% in males and −17% in females), or Japan (−19% in males and −31% in females). Rates in Japan, moreover, were six to eight times higher than in the USA, and were intermediate in Europe. Colorectal cancer rates in the elderly, after earlier rises, declined over the last decade in both sexes in the EU (−11% for males and −20% for females), and the USA (−16% for males and −18% for females), but rose in Eastern Europe (+16% in males and +4% in females), and in Japan, mostly in males (+23% for males and +4% for females). In 1995– 98, intestinal cancer rates for Japanese males (135/100000) were higher than in the USA (124/100000), while the rate in the EU was 152/100000, and that in Eastern Europe was 175/100000. After substantial rises between 1960 and 1985, lung cancer rates at age 65–84 for the first time declined over the last decade by 8.5% in males in the EU, and by 0.9% while they rose from 80 to 90/100000 in Eastern Europe, and from 19 to 24/100000 in Japan.

Cancer mortality in the elderly, 1960-98

53

Figure 3.1 Trends in age-standardized (at age 65–84, World Standard) death certification rates per 100000 population from selected cancers or groups of cancers in the EU, selected Eastern European countries (E Europe), the USA, and Japan: 1960– 97.


54

in the USA. Rates were still upwards in Eastern European (+6%) and Japanese (+12%) males and in females in all areas (+16% in the EU, +24% in Eastern Europe, +36% in the USA, but only +1.2% in Japan). While in elderly men the differences in lung cancer rates across broad geographic areas were relatively limited, in women an approximately threefold difference was still evident between the rates of 67–77/100000 in Japan and Europe, and the rates of 212/100000 in the USA. Again after earlier rises in most areas, breast cancer mortality in women aged 65–84 declined by 8% in the USA and by 3% in the EU, to reach 106/100000 in both areas, Prostate cancer mortality in males aged 65–84 declined by 4% in the EU and 6% in the USA, to reach the same value of 149/100000 for both areas. In Eastern Europe, prostate cancer mortality rose from 113 to 127/100000


55

(+13%). In Japan, prostate cancer mortality over the last decade rose by 33%, from 36 to 48/100000. Mortality from myeloma at age 65–84 steadily rose by 10–20% in both sexes in all geographic areas considered over the last decade, continuing a long-term and substantial upward trend, which had already been evident since the early 1960s. Tables 3.1 (for males) and 3.2 (for females) give mortality rates from total cancer mortality and selected cancer sites in different European countries, besides the EU, the USA, and Japan. Declines (though to a different degree) were observed in France, Germany, Italy, and the UK for total cancer mortality in both sexes, whereas rates were upwards in most of Eastern Europe, and showed no consistent pattern in Southern Europe. Lung cancer trends were appreciably different across countries in elderly males,


56

with a 25% fall in the UK, but not in other major European countries, and were generally upwards (though to a different degree) for elderly females. A substantial decline in breast cancer mortality (−14%) was observed in the UK, where rates were originally higher, but not in other major European countries. Prostate cancer rates were downwards in France and Italy, but upwards in most other countries. Mortality from myeloma was consistently upwards in most European countries, except the UK, Finland, the Netherlands, and Norway. The Russian Federation had the highest total cancer mortality (1532/100000) in elderly males, and some of the highest rates for most sites, except breast and prostate. Over the last decade, cancer mortality rates increased in elderly Russians by 7.4% in males and 5.5% in females.

Discussion The main finding of this updated analysis of cancer mortality in the elderly is the observation of a change of trends for males in the USA and for both sexes in the EU, with the consequent end of a long-term rise and the beginning of a measurable fall in males. Some decline in total cancer mortality was observed also for females in Japan. This is an innovative observation, since declines in total cancer mortality have been registered in young20,21 and middle age, as well as in overall age-standardized rates,5–10 but rates in the elderly had been rising for longer, and have been described as a particular unfavorable indicator of cancer mortality.3,4,11 In all geographic areas considered, a component of the fall has been the steady decline in gastric cancer.22 However, in the EU, and mostly the USA, gastric cancer rates were already low in the 1980s, and consequently this was a relatively minor component of the global trends.


57

Of major relevance are the changing trends in lung and other tobacco-related neoplasms—in both sexes and various geographic areas. Thus, lung cancer mortality rates in elderly males have started leveling off in the EU (and substantially in the UK23) and in the USA.3 This reflects the decreased smoking prevalence in subsequent generations of elderly males,24,25 and the increased rates of stopping smoking, mostly for males in the USA and Northern Europe. Lung cancer rates, in contrast, have increased by 36% in US females, reaching a rate of over 210/100000, i.e. twice that of breast cancer. The rise was 16% in the EU, with a rate of 77/100000. These unfavorable trends reflect the increased prevalence of smoking in elderly women in the USA6 and, to a lesser degree, Europe. Within Europe, female rates in Denmark, Iceland, and the UK approached 200/100000, too.26 An 8% fall in breast cancer mortality for elderly women was registered in the USA, and a 3% fall in the EU. These favorable trends reflect advancements in screening, early diagnosis, and treatment of breast cancer,27–30 although the falls are smaller than the 15– 20% reported for younger women (aged 50–70),31 thus raising the question of modifying diagnostic and treatment approaches to breast cancer in elderly women. A similar line of reasoning applies to prostate cancer in the EU and USA.32,33 In any case, the first observation of favorable changes in trends in mortality from these common cancers in the elderly is extremely encouraging. Mortality from breast and prostate cancer in the elderly was still rising in Japan, but absolute rates remained comparatively low.34

Table 3.1 Trends in age-standardized (65–84 years, World Standard) death certification rates per 100000 men from five major cancers plus total mortality in various countries between 1985–89 and 1995–98 (unless otherwise mentioned in parentheses) Stomach Country

Intestines % 1985– change 89

lung

1995– 98

% 1985– change 89

Prostate 1995– 98

% 1985– change 89

Myeloma

1995– 98

% 1985– change 89

Total all sites

1985– 89

1995– 98

1995– 98

% 1985– change 89

1995– 98

% change

Austria

162.1

103.9

−35.9

195.5

178.6

−8.6

353.8

321.2

−9.2

165.9

157.3

−5.2

13.2

17.0

28.8

Bulgaria

163.0

117.9

−27.7

119.0

140.5

18.1

219.4

211.8

−3.5

81.0

91.6

13.1

2.8

2.1

−25.0

1373.0

1263.8

−8.0

870.7

884.4

Czech Republic

170.7

111.6

−34.6

305.5

292.8

−4.2

520.9

468.1

−10.1

162.9

166.9

2.5

15.2

18.9

1.6

24.3

1749.2

1674.8

−4.3

Denmark (95–96)

70.1

49.5

−29.4

202.4

198.9

−1.7

464.8

440.4

−5.2

182.7

209.1

14.4

21.7

26.3

21.2

1500.9

1516.5

1.0

Finland (95–96)

124.2

78.9

−36.5

113.0

101.1

−10.5

457.3

385.9

−15.6

162.7

181.1

11.3

25.6

20.5

−19.9

1330.0

1234.0

−7.2

France (95–97)

81.9

56.2

−31.4

187.5

143.6

−23.4

323.6

326.6

0.9

170.1

142.3

−16.3

17.2

17.7

2.9

1479.2

1370.2

−7.4

Germany

137.7

95.2

−30.9

187.9

175.9

−6.4

387.4

368.0

−5.0

158.5

155.9

−1.6

16.4

19.6

19.5

Greece (95–97)

78.4

66.5

−15.2

72.4

71.5

−1.2

381.6

392.3

2.8

81.8

96.5

18.0

10.4

12.1

16.3

1420.1

1345.3

−5.3

1128.7

1160.0

2.8

Hungary

204.4

156.6

−23.4

229.6

293.3

27.7

460.6

543.3

16.0

164.5

177.5

7.9

11.2

15.6

39.3

1636.8

1835.1

12.1

Ireland (95–96)

117.2

84.5

−27.9

209.4

188.9

−9.8

424.7

389.3

−8.3

176.0

197.3

12.1

27.1

27.0

−0.4

1434.2

1427.4

−0.5


58

Italy (95– 96)

163.0

113.0

−30.7

160.6

137.3

−14.5

439.2

441.0

0.4

121.2

107.2

−11.6

16.2

18.1

11.7

1498.5

1437.9

−4.0

Nether lands (95– 97)

119.9

81.8

−31.8

175.1

161.5

−7.8

678.1

548.4

−19.1

168.8

177.4

5.1

25.2

25.4

0.8

1679.9

1535.9

−8.6

Norway (95–96)

104.0

76.8

−26.2

169.1

168.6

−0.3

251.2

278.6

10.9

218.7

229.9

5.1

31.7

28.8

−9.1

1230.2

1251.6

1.7

Poland (95–96)

205.2

151.9

−26.0

115.2

143.4

24.5

435.5

508.9

16.9

102.3

120.8

18.1

1380.5

1511.6

9.5

Portugal

197.1

159.8

−18.9

143.7

156.3

8.8

178.2

217.3

21.9

137.5

172.7

25.6

1035.4

1171.9

13.2

Romania

143.5

123.7

−13.8

72.6

96.0

32.2

175.9

226.5

28.8

76.8

91.2

18.8

792.8

917.7

15.8

Russian Federation (95–97)

309.2

247.9

−19.8

135.5

153.1

13.2

445.3

457.3

2.7

66.1

78.0

18.0

1426.5

1531.6

7.4

Spain (95–97)

123.8

95.3

−23.0

119.7

139.1

16.2

328.6

365.6

11.2

131.5

131.5

0.0

13.4

17.2

28.4

1258.1

1306.7

3.9

Sweden (95–96)

84.7

55.8

−34.1

131.4

123.4

−6.1

199.2

191.8

−3.7

199.4

221.1

10.9

22.1

23.2

5.0

1082.3

1051.6

−2.8

Switzer land (90– 94)

88.3

73.6

−16.6

167.4

154.8

−7.5

384.3

358.2

−6.8

217.4

220.7

1.5

21.7

24.8

14.3

1434.8

1365.2

−4.9

United Kingdom (95–97)

122.2

80.5

−34.1

178.6

151.7

−15.1

550.8

414.5

−24.7

160.6

161.5

0.6

21.8

21.1

−3.2

1536.5

1375.3

−10.5

European Union (95–97)

126.9

90.1

−29.0

170.5

151.7

−11.0

423.8

387.6

−8.5

155.1

149.5

−3.6

17.8

19.6

10.1

1457.2

1377.5

−5.5

USA (95– 97)

40.6

32.7

−19.5

147.8

123.9

−16.2

440.6

436.7

−0.9

158.4

148.9

−6.0

21.8

23.9

9.6

1265.6

1236.7

−2.3

304.5

245.9

−19.2

109.6

135.1

23.3

273.4

305.2

11.6

36.3

48.1

32.5

10.2

12.5

22.5

1218.0

1294.7

6.3

Japan (95–97)

9.7

15.8

62.9

Table 3.2 Trends in age-standardized (65–84 years, World Standard) death certification rates per 100000 women from five major cancers plus total mortality in various countries between 1985–89 and 1995–98 (unless otherwise mentioned in parentheses) Stomach Country

Intestines

1995– 1995– 89 98

% 1985– change 89

lung

1995– % 1985– 98 change 89

Breast 1995– 98

% 1985– change 89

Myeloma 1995– 98

% 1985– change 89

Total all sites

1995– 98

% 1985– change 89

1995– 98

% change

Austria

91.4

61.2

−33.0

119.1

98.3

−17.5

60.6

70.5

16.3

117.0

106.5

−9.0

11.1

14.7

32.4

762.7

687.0

−9.9

Bulgaria

91.3

62.9

−31.1

76.3

84.1

10.2

42.6

41.9

−1.6

66.9

71.3

6.6

1.5

1.7

13.3

497.1

492.9

−0.8

Czech Republic

81.4

52.8

−35.1

167.8

140.9

−16.0

54.9

78.4

42.8

115.3

116.6

1.1

11.7

12.9

10.3

871.9

851.5

−2.3

Denmark (95–96)

32.4

21.4

−34.0

140.9

131.0

−7.0

137.3

197.9

44.1

139.5

151.5

8.6

14.7

16.5

12.2

906.3

980.4

8.2

Finland (95–96)

63.3

40.4

−36.2

78.0

67.6

−13.3

50.2

54.5

8.6

84.8

79.1

−6.7

17.4

19.3

10.9

654.1

611.6

−6.5

France (95– 97)

32.0

20.1

−37.2

101.1

74.6

−26.2

32.4

41.0

26.5

99.0

98.9

−0.1

12.2

12.3

0.8

602.7

567.2

−5.9


59

Germany

66.0

45.9

−30.5

135.9

113.3

−16.6

50.3

66.8

32.8

109.5

110.3

0.7

11.0

13.8

25.5

767.4

722.5

−5.9

Greece (95–97)

43.0

34.4

−20.0

59.7

48.7

−18.4

48.5

51.1

5.4

69.3

83.5

20.5

7.9

8.8

11.4

521.7

535.4

2.6

Hungary

86.0

65.8

−23.5

151.3

154.9

2.4

80.3

113.7

41.6

111.7

122.5

9.7

9.3

11.9

28.0

855.3

900.7

5.3

Ireland (95–96)

52.5

37.9

−27.8

128.4

103.1

−19.7

144.0

160.4

11.4

122.8

129.7

5.6

18.4

16.8

−8.7

839.3

853.5

1.7

Italy (95– 96)

74.3

54.9

−26.1

102.4

75.5

−26.3

52.7

60.8

15.4

100.2

100.0

−0.2

11.7

13.0

11.1

682.3

646.2

−5.3

Netherlands (95–97)

44.0

30.3

−31.1

119.3

103.3

−13.7

50.7

89.3

76.1

136.1

133.4

−2.0

16.2

17.0

4.9

724.1

729.9

0.8

Norway (95–96)

43.9

32.8

−25.3

110.9

113.5

2.3

57.5

95.6

66.3

99.7

98.8

−0.9

19.0

18.4

−3.2

667.8

709.7

6.3

Poland (95–96)

74.3

56.9

−23.4

79.6

92.3

16.0

57.2

71.8

25.5

70.3

77.8

10.7

674.7

706.2

4.7

Portugal

95.2

71.4

−25.0

91.5

79.8

−12.8

26.6

28.5

7.1

71.9

81.9

13.9

531.6

544.9

2.5

Romania

7.3

11.9

63.0

60.7

51.4

−15.3

53.6

61.8

15.3

35.7

45.2

26.6

59.9

70.9

18.4

460.3

497.9

8.2

Russian Federation (95–97)

141.8

108.4

−23.6

87.2

94.9

8.8

52.3

49.3

−5.7

50.0

67.7

35.4

605.7

639.3

5.5

Spain (95– 97)

58.8

40.0

−32.0

78.3

74.9

−4.3

25.5

25.7

0.8

71.7

77.3

7.8

9.8

12.8

30.6

540.9

522.0

−3.5

Sweden (95–96)

37.6

26.4

−29.8

89.0

83.5

−6.2

60.0

82.9

38.2

93.1

89.0

−4.4

15.7

17.2

9.6

673.5

685.9

1.8

Switzerland (90–94)

37.3

30.1

−19.3

94.2

85.0

−9.8

45.8

53.9

17.7

138.0

131.1

−5.0

15.4

15.7

1.9

695.0

669.4

−3.7

United Kingdom (95–97)

48.7

31.7

−34.9

117.1

91.7

−21.7

158.1

180.7

14.3

144.0

123.4

−14.3

14.9

14.5

−2.7

850.9

835.7

−1.8

European Union (95– 97)

57.0

39.2

−31.2

112.0

89.9

−19.7

66.5

77.4

16.4

109.6

106.0

−3.3

12.3

13.9

13.0

712.2

680.0

−4.5

USA (95– 97)

17.7

14.7

−16.9

98.6

80.7

−18.2

155.1

211.6

36.4

115.7

106.2

−8.2

14.9

16.5

10.7

731.8

764.1

4.4

Japan (95– 97)

118.3

81.3

−31.3

67.9

70.4

3.7

66.3

67.1

1.2

19.0

24.4

28.4

7.2

8.5

18.1

557.2

525.9

−5.6

It is more difficult to explain the leveling trends and the declines in colorectal cancer mortality, particularly for elderly women. These too may be due, at least in part, to earlier diagnosis, but a more favorable pattern of risk factor exposure (including diet and perhaps hormones for women)35,36 has probably also played some role. Mortality from myeloma, in contrast, has been steadily rising in most countries considered, with the sole exception of some Northern European countries. Diagnostic improvements and changes in classification still partly or largely account for these trends, but it is also possible that some real increases have occurred in the incidence and mortality for myelomas,37 as well as for lymphomas,38 which have also increased in most areas—in the absence, however, of obvious explanations, and of consistent patterns. Liver and brain cancers are other sites for which the incidence has been rising in the elderly, but the WHO database was inadequate to understand and evaluate their trends in various countries.13,39–41


60

In greater generality, it is important to stress the limitations and uncertainties of cancer death certification for the elderly and their trends over time. Although the exact influence of changed certification accuracy on trends in cancer rates is undefined, almost certainly this has implied some systematic upward trends over time, following generalized improvements in diagnosis and certification of selected cancers, including particularly prostate cancer and myeloma.2,13,39 Within Europe, a substantial variation in mortality from several major cancer sites was still observed in the elderly, although for other neoplasms (such as breast or prostate) tendencies towards leveling of trends were also apparent.42 Most trends remain unfavorable for elderly populations of both sexes in Eastern Europe, reflecting both rising trends in underlying incidence—due to unfavorable patterns in smoking, the characteristics of diet and other risk factor exposure, and to systematic delays in the adoption of improved diagnosis and treatment approaches.43 Thus, while stomach cancer rates remain high in these areas of the continent, lung cancer rates in males have reached some of the highest rates observed (over 500/100000 in Hungary and Poland), and trends for breast or prostate cancer rates were still upwards. Comprehensive intervention for cancer control among the elderly in all areas of the world, but particularly in Eastern Europe, is therefore a public health priority.44–47 Acknowledgements This study was made possible by a core grant from the Swiss League Against Cancer. Support was also received from the Italian Association for Cancer Research. References 1. La Vecchia C, Levi F, Lucchini F, Negri E. International perspectives of cancer and aging. In: Comprehensive Geriatric Oncology, 1st edn (Balducci L, Lyman GH, Erschler WB, eds). Amsterdam: Harwood Academic Publishers, 1998:19–93. 2. Levi F, La Vecchia C, Lucchini F, Negri E. Worldwide trends in cancer mortality in the elderly, 1955–1992. Eur J Cancer 1996; 32A: 652–72. 3. Hoel DG, Davis DL, Miller AB et al. Trends in cancer mortality in 15 industrialized countries, 1969–1986. J Natl Cancer Inst 1992; 84: 313–20. 4. Davis DL, Hoel D, Fox J, Lopez A. International trends in cancer mortality in France, West Germany, Italy, Japan, England and Wales, and the USA. Lancet 1990; 336:474–81. 5. Cole P, Rodu B. Declining cancer mortality in the United States. Cancer 1996; 78:2045–8. 6. Wingo PA, Ries LAG, Giovino GA et al. Annual report to the Nation on the status of cancer, 1973–1996, with a special section on lung cancer and tobacco smoking. J Natl Cancer Inst 1999; 91:675–90. 7. Ries LAG, Wingo PA, Miller DS et al. The annual report to the Nation on the status of cancer, 1973–1997, with a special section on colorectal cancer. Cancer 2000; 88:2398–424. 8. Levi F, La Vecchia C, Negri E, Lucchini F. Declining cancer mortality in European Union. Lancet 1997; 349:508–9. 9. Levi F, Lucchini F, Negri E, Boyle P. Cancer mortality in Europe and an overview of trends from 1955 to 1994. Eur J Cancer 1999; 35: 1477–516.


61

10. Levi F, Lucchini F, La Vecchia C, Negri E. Trends in mortality from cancer in the European Union, 1955–94. Lancet 1999; 354:742–3. 11. Davis DL, Dinse GE, Hoel DG. Decreasing cardiovascular disease and increasing cancer among whites in the United States from 1973 through 1987. Good news and bad news. JAMA 1994; 271:431–7. 12. La Vecchia C, Negri E, Levi F et al. Cancer mortality in Europe: effects of age, cohort of birth and period of death. Eur J Cancer 1998; 34:118–41. 13. Doll R, Peto R. The causes of cancer: quantitative estimates of avoidable risks of cancer in the United States today. J Natl Cancer Inst 1981; 66:1191–308. 14. Monfardini S, Aapro M, Ferrucci L et al. Commission of the European Communities ‘Europe Against Cancer’ Programme European School of Oncology Advisory Report. Cancer Treatment in the Elderly. Eur J Cancer 1993; 29A: 2325–30. 15. Balducci L. Geriatric oncology: challenges for the new century. Eur J Cancer 2000; 36:1741– 54. 16. World Health Organization. International Classification of Diseases: 8th Revision. Geneva: WHO, 1967. 17. World Health Organization. International Classification of Diseases: 9th Revision. Geneva: WHO, 1977. 18. World Health Organization. International Statistical Classification of Diseases and Related Health Problems: 10th Revision. Geneva: WHO, 1992. 19. Doll R, Smith PG. Comparison between registries: age-standardized rates. In: Cancer Incidence in Five Continents, Vol IV (Waterhouse JAH, Muir CS, Shanmugaratnam K et al, eds). Lyon: IARC Press, 1982:671–5. 20. Doll R. Are we winning the fight against cancer? An epidemiological assessment. Eur J Cancer 1990; 26:500–8. 21. Franceschi S, Levi F, Lucchini F et al. Trends in cancer mortality in young adults in Europe, 1955–1989. Eur J Cancer 1994; 30:2096–118. 22. La Vecchia C, Franceschi S. Nutrition and gastric cancer with a focus on Europe. Eur J Cancer Prev 2000; 9:291–5. 23. Peto R, Darby S, Deo H et al. Smoking, smoking cessation, and lung cancer in the UK since 1950: combination of national statistics with two case-control studies. BMJ 2000; 321:323–9. 24. Franceschi S, Naett C. Trends in smoking in Europe. Eur J Cancer Prev 1995; 4:271–84. 25. World Health Organization. Tobacco or Health: A Global Status Report. Geneva: WHO, 1997. 26. Levi F, La Vecchia C, Lucchini F, Negri E. Lung cancer in Icelandic women. Eur J Cancer Prev 1999; 8:369. 27. Cuzick J. Screening for cancer: future potential. Eur J Cancer 1999; 35:685–92. 28. Early Breast Cancer Trialists’ Collaborative Group. Polychemiotherapy for early breast cancer: an overview of the randomized trial. Lancet 1998; 352:930–42. 29. Early Breast Cancer Trialists’ Coilaborative Group. Tamoxifen for early breast cancer: an overview of the randomized trial. Lancet 1998; 351:1451–87. 30. Fisher B, Costantino JP, Wickerman DL et al. Tamoxifen for prevention of breast cancer: report of the National Surgical Adjuvant Breast Project P-2 Study. J Natl Cancer Inst 1998; 90:1371– 88. 31. Peto R, Boreham J, Clarke M et al. UK and USA breast cancer deaths down 25% in year 2000 at ages 20–69 years. Lancet 2000; 355:1822. 32. Levi F, Lucchini F, Negri E, La Vecchia C. Recent trends in prostate cancer mortality in the European Union. Epidemiology 2000; 11:612. 33. Tarone RE, Chu KC, Brawley OW. Implications of stage-specific survival rates in assessing recent declines in prostate cancer mortality rates. Epidemiology 2000; 11:167–70. 34. Boyle P, Levi F, Lucchini F, La Vecchia C. Trends in diet-related cancers in Japan. A conundrum? Lancet 1993; 342:752 35. Boyle P, Langman JS. Epidemiology. BMJ 2000; 321:805–8.


62

36. Franceschi S, La Vecchia C. Colorectal cancer and hormone replacement therapy: an unexpected finding. Eur J Cancer Prev 1998; 7: 427–38. 37. Cuzick J. Multiple myeloma. Cancer Surv 1994; 19/20:455–74. 38. Levi F, La Vecchia C, Lucchini F et al. Mortality from Hodgkin’s disease and other lymphomas in Europe, 1960–1990. Oncology 1995; 52:93–6. 39. Boyle P, Maisonneuve P, Saracci R, Muir CS. Is the increased incidence of primary malignant brain tumours in the elderly real? J Natl Cancer Inst 1990; 82:1594–6. 40. Modan B, Wagener DK, Feldman JJ et al. Increased mortality from brain tumours: a combined outcome of diagnostic technology and change in attitude toward the elderly. Am J Epidemiol 1992; 135:1349–57. 41. La Vecchia C, Lucchini F, Franceschi S et al. Trends in mortality from primary liver cancer in Europe. Eur J Cancer 2000; 36:909–15. 42. Levi F, Lucchini F, Boyle P et al. Cancer incidence and mortality in Europe, 1988–92. J Epidemiol Biostatist 1998; 3:295–373. 43. Levi F. Cancer prevention: epidemiology and perspectives. Eur J Cancer 1999; 35:1046–58. 44. Boyle P. Epidemiology in central and eastern Europe. Epidemiology 1992; 3:391–4. 45. Boyle P. Tobacco and cancer, the European perspective. Ann Oncol 1995; 6:435–7. 46. La Vecchia C, Levi F, Franceschi S. Epidemiology of cancer with a focus on Europe. J Epidemiol Biostatist 2000; 5:31–47. 47. Levi F, Lucchini F, Negri E et al. Changed trends of cancer mortality in the elderly. Ann Oncol 2001; 12:1467–77.

4 Cancer in older persons: Magnitude of the problem and efforts to advance the aging/cancer research interface Rosemary Yancik, Lynn AG Ries Introduction Persons 65 years and older bear the brunt of the cancer burden. Incidence data from the US National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) program for 1995–99 clearly indicate that aging is a high risk factor for cancer.1 The incidence rate for those aged 65 or more is 2208.1 per 100000 persons, as compared with 229.2 per 100000 for those younger than 65—a dramatic 10-fold difference in overall cancer incidence rates (i.e. the number of newly diagnosed cases occurring per 100000 persons during a given time). This chapter updates recent cancer statistics information and cites steps being taken to advance the aging/cancer research interface. Incidence of selected tumors Approximately 60% of all cancers occur in the elderly subgroup of the population. The impact of aging is made even more clear and apparent when specific tumors are considered. Table 4.1 lists the American Cancer Society’s (ACS) estimate of the number of new cancer cases for 2002 and the SEER estimates for individuals 65 and older to illustrate the scope of the problem of cancer in the elderly by individual tumors. Proportions for the elderly are derived from calculations using the SEER incidence by age.2 For the major sites of malignancies common to both men and women—lung, colon, rectum, stomach, pancreas, and urinary bladder—two-thirds to three-quarters occur in the elderly. The percentages of lung and bronchial cancers that occur in individuals aged 65 and older are 68% and 69% for men and women, respectively. These percentages have increased within the last several years as the US population has aged and the smoking exposure-time effects on birth cohorts has become more apparent, reflecting the high rates of smoking behavior of persons now in their late 60s and early 70s. As to the gender-specific malignancies, prostate cancer, with 69% occurring in this age group, is a predominant


64

Table 4.1 2002 estimates of cancer cases: men and women, all ages, and proportion 65 years of age and older Men Cancer site

Women

All ages

65+

All ages

65+

Lung

90200

61 336 (68%)

79200

54 648 (69%)

Colon

50000

35 000 (70%)

57300

43 548 (76%)

Rectum

22600

13 560 (60%)

18400

11 960 (65%)

Urinary bladder

41 500

29465 (71%)

15000

11 100 (74%)

Stomach

13300

8 778 (66%)

8300

5 976 (72%)

Pancreas

14700

9 555 (65%)

15600

12012 (77%)

Breast (female)

—

—

203 500

91 575 (45%)

Ovary

—

—

23300

10252 (44%)

189000

130 410 (69%)

—

—

Prostate

Data from Cancer Facts and Figures—2002. Atlanta: American Cancer Society, 2002. Number of persons 65 years and older diagnosed with cancer are estimated from National Cancer Institute SEER Program Data, 1995–99 and applied to American Cancer Society estimates.

Figure 4.1 Cancer incidence rates: (a) men; (b) women. health problem. Both breast cancer and ovarian cancer are special problems for older women. These two malignancies generally have been considered early postmenopausal rather than late postmenopausal tumors. In most discussions and research reports on prevention and treatment, a perimenopausal age-break of 50 years is generally used, with no reference to the actuality that 45% of breast cancers and 44% of ovarian cancers occur in women aged 65 and older.

Magnitude of the problem and efforts to advance the aging/cancer research interface

65

Incidence curves emphasize the escalation of increased cancer rates with advancing age and show contrasts by 5-year age groups beginning at 35 years of age. It is important to illustrate the increase in cancer incidence rates with advancing age. Incidence differentials are delineated by age for the selected tumors for men and women in Figure 4.1.1 The curves, based on incidence rates per 100000 persons (shown on the vertical axis), portray the gradients for selected tumors as they rise with advancing age (shown on the horizontal axis). Rates are per 100000 and age-adjusted to the year 2000 US population. The highest incidences and greatest numbers of cancer for men (Figure 4.1a) are associated with three tumor types: prostate cancer, lung cancer, and colon cancer. The scale shown for men reaches to a high of 1200 per 100000 to accommodate the high incidence rates for prostate cancer in the age-specific groups for men after the age of 65. Two other malignancies also have extremely high incidence rates in men: colon cancer rates range from 159.1 per 100000 for the 65–69 age group to 408.4 for those aged 85 and older. Lung cancer rates escalate to peak rates between 503.1 and 554.6 in the 70–84 age group. Unfortunately, as the population-based tumor registry data reveal, old age is the ‘normal time’ at which cancer develops. The numbers shown in Table 4.1 suggest the urgent need to address the problems unique to persons aged 65 and older. Compared with the rest of the population, these individuals suffer disproportionately from the morbidity, adversity, and hardship brought on by these malignancies. This age group, however, has been under-represented historically in clinical studies that generate knowledge about cancer treatment.3,4 Urinary bladder cancer rates crest at 300.4 for men aged 85 and older. Incidence rates for tumors of the rectum, stomach, and pancreas do not reach the elevated levels of the preceding three cancers, but all rates increase with advancing age to more than 100.0 per 100000 population. Eight malignancies that are most common in women are shown in Figure 4.1(b). The vertical axis scale extends to 500 per 100000 persons. Breast cancer has the highest incidence rates of all tumors affecting women. All age groups older than 65 have rates exceeding 400.0 per 100 000 persons. Two specific age groups, 75–79 (500.9) and 80–84 (487.7), show the highest rates per 100000 population. It should be noted here (and as discussed in detail in the literature) that less emphasis has been placed on knowledge of the need for regular mammograms in older age groups, even though cancer incidence is extremely high for older women. There has been a continuing debate in recent years regarding the effectiveness of breast cancer screening for women aged 40–49 years.5 Incidence rates of 118.2 and 200.5 per 100000 for women aged 40–44 and 45–49, respectively, are one-third to less than one-half the rates shown for women aged 65 and older. Even though rates are highest in the older age groups, especially those 70 and older, there has been no special emphasis on early detection for elderly women. Lung cancer incidence rates peak in the 70–84 age groups, with rates between 293.3 and 302.9 per 100000 persons. Colon cancer rates are highest for all women aged 65 and older, and are highest for women 80 and older, with rates of 380.5 and 408.4 per 100000 persons as indicated. Incidence rates for the next five tumors shown—pancreas, ovarian, rectum, urinary bladder, and stomach—have rates at similar levels. For these latter five


66

malignancies, all rates are under 100.0 per 100000 female population, with the highest rates being in women aged 65 and older. The unique SEER population-based data furnish the statistical framework to describe the magnitude of the cancer problem for older persons.1 The SEER program used for the analysis covers approximately 14% of the US population. Incidence, mortality, and stage of disease at initial diagnosis and age contrasts are made with SEER program data for selected cancer sites.1 Comprehensive descriptions of the SEER program and its procedures are available in several publications.1,5,6 Mortality data from the National Center for Health Statistics for 1999 and demographic data from the US Bureau of the Census complete the picture.7–11 Mortality Seventy-one percent of all deaths due to cancer in the USA occur in individuals in the 65 and older age group.1 Mortality rates have increased for the population aged 65 and older in numbers and proportion. Approximately a decade or so ago, the percentage of cancer deaths for persons in this age group was about 60%. The nine malignancies addressed in particular in this chapter represent approximately 63% of cancer mortality in the USA during 1999. In that year, 549829 cancer deaths occurred.2 This is a high proportion of the approximately 66 different categories of tumor registration on which SEER reports routinely.1,5,6 Figure 4.2 shows the numbers of cancer deaths and the percentages of those that occurred in individuals younger than 65 and those 65 and older for the nine tumors discussed in this chapter. First distinguishing the tumors common to men and women (colon/rectum, urinary bladder, stomach, and pancreas), the percentages of those aged 65 and older range from 68% (for pancreatic and stomach cancer deaths in men) to 88% (for urinary bladder deaths in women). For lung and bronchial cancer, 72% of cancer mortality is in older women; 70% is in older men. For the gender-specific malignancies, 93% of deaths due to prostate cancer occur in men aged 65 and older. The percentage proportion of deaths is 60% for breast cancer and 66% for ovarian cancers, for women aged 65 and older.


67

Figure 4.2 Mortality rates for selected cancer sites (1999): (a) lung/bronchus, pancreas, stomach, colon/rectum, and urinary bladder; (b) breast, ovary, and prostate. Stage distribution by age As with most tumors, anatomic staging of the extent of tumor progression at initial diagnosis is extremely important. Staging governs prognosis and treatment. Early diagnosis of cancer is more likely to have positive consequences for the length and quality of survival and cure potential. The SEER data on the extent of disease at initial diagnosis—localized, regional, distant (metastatic), or stage unknown or not recorded— are stratified by age groups for selected tumors to illustrate the relationships between stage and age. The question for each age group is: What is the stage distribution? The progression of stage severity and stage-unknown categories for breast, ovarian, and


68

prostate cancer are shown in Figure 4.3(a–c). Stage distributions for colon and rectal cancers for both men and women are shown in Figure 4.3(d, e). Breast There is wide variation in breast cancer stage distribution for localized and regional disease. More than half of each age group is diagnosed with localized disease. An ascending pattern from younger to older age is noted for this disease stage. This is in contrast to a descending age profile difference in the regional-disease stage. The percentage of distant disease is similar across age groups. Women in the oldest age category, 75 and older, have a threefold higher percentage of stage-unknown disease. Ovary Differences in stage distribution are striking by age. The younger than 55 age group has the highest proportion of localized disease, whereas the older age groups have more

Figure 4.3 Stage distribution by age: (a) breast; (b) ovary; (c) prostate; (d) colon/rectum (men); (e) colon/rectum (women).


69

distant disease. In addition, the oldest age group has the highest proportion of unstaged disease. The stage/age distribution for this cohort is consistent with reports on ovarian cancer in the elderly. Prostate Prostate cancer is diagnosed in the localized/regional stages for 90–92% for men in the age categories up to and including 74 for the patient cohort illustrated in Figure 4.3(c). Male patients aged 75 and older are diagnosed in this more favorable combination of stages to a much lesser extent (77%). In the distant-disease category, the high proportion shown (8%) for males aged 75 and older represents close to half of all individuals diagnosed with this tumor stage (n=6276). Similarly, in the stage-unknown category, the percentage for individuals aged 75 and older (15%) represents more than half of all individuals (n=9445) whose stage was unknown. Colon/rectum: men and women The distribution of colorectal cancer cases by disease stage, including those for which the stage was unknown, are shown for both genders. Once again, we see that the percentage in the stage-unknown category for the 75 and older age group is quite large. For both sexes, there is a consistency in the disease stage distribution across age groups. There is little variation in stage distribution by age for these malignancies. Age/stage relationship There does not appear to be an age/stage relationship in breast and colorectal cancers. In ovarian cancer, age does appear to be related to disease stage. In prostate cancer, of patients diagnosed initially with distant stage, the oldest patients comprise the greater proportion. Without classifying information on the patients in the stage-unknown category, it is difficult to make concrete statements. Because of the preponderance of percentages in the stage-unknown category for the older age group, one analytic interpretation derived from these data is that cancer in the older person’s disease stage cannot be labeled as ‘less often metastatic’ or ‘less aggressive’. Another interpretation is an inference that older cancer patients are receiving less than full workups (i.e. the greater proportion of older persons in the stage-unknown categories), resulting in less than complete staging procedures. Our aging nation The elderly population (i.e. persons aged 65 and older) in the USA is estimated at 35 million, constituting 12.4% of the total US population.11 The cancer control needs for this age group should receive prompt and systematic attention. Currently, there are 8.9 million individuals with a history of cancer or who have been newly diagnosed with a


70

malignancy according to the Annual Report to the Nation on Cancer.6 It is indicated that approximately 60% of these survivors are aged 65 or older. If the overall cancer rates remain the same, because of the aging of the population, the absolute number of cancers occurring in persons in the age group 65 and older is expected to double by 2030. Of cancer patients in 2030, 70% will be aged 65 or older. In preparation for the forthcoming dramatic expansion of this age group in the next 30 years, we should be anticipating the greater need for healthcare resources. Figure 4.4 describes the recent past and near future in a 10-decade comparison of population estimates and projections with data from the US Bureau of the Census.9–11 The total US population was estimated to have increased from 22.8 million in 1930 to 270.3 million in 1998. The proportion of the population aged 65 and older has almost doubled, from 1 in 15 of the population in the 1930s to 1 in 8 in the 1990s. Looking forward 30 years, 1 in 5 persons will be aged 65 or older in 2030.

Figure 4.4 US population growth: 10decade comparison, total population/age, 65 segments.


71

Figure 4.5 Population by age and sex: (a) 1975; (b) 1990; (c) 2010; (d) 2030. From Taeuber CM. Sixty-Five Plus in America, revised edn. Washington, DC: US Government Printing Office, Current Population Reports, Special Studies, P23–178RV, 1993. Not only is the US population aging, the age structure is changing over time. More older people are living longer. There are and will continue to be more older-old persons (i.e. aged 75–84 and 85 and older) in the older-age segment of the population.11 Low fertility, elimination of certain infectious diseases, and longer life-expectancies are contributing to the US demographic imperative.12 Age pyramids, depicting age structure, are often featured in US Bureau of the Census publications. They portray the changes that have occurred and will occur. Figure 4.5 describes age-specific changes for selected years.8 The first age pyramid (Figure 4.5a) depicts the post-World War 2 ‘baby boom’ as it was in 1975, when the cohort was between 10 and 30 years of age. Changes over time for selected decades show the shifting age structure in the USA. The configurations seen in Figure 4.5(b–d) reflect the changes that will occur as the US population advances toward 2030. The age structure pyramid will become rectangular in shape. Figure 4.5(b) represents this cohort (the cohort now aged between 25 and 45) as it was in 1990. The first wave of the ‘baby boomers’ will become 65 in 2010, as indicated in Figure 4.5(c). By 2030, the entire cohort will be 65 or older (Figure 4.5d).


72

As the postwar baby-boom cohorts reach age 65, not only will the numbers of older persons rapidly increase, there will also be significant age shifts in the population, resulting in even more persons in the oldest-age category (i.e. 85 and older), as shown in Figure 4.5(d). The old will get older between now and the peak year of population growth (2030).

Table 4.2 Life-expectancy in 1900, 1950, and 1997: average number of years of life remaining at birth, at 65, and at 85, by sex Year/sex

At birth

At age 65

At age 85

Men

73.6

15.9

5.5

Women

79.4

19.2

6.5

Men

65.5

12.7

4.4

Women

71.0

15.0

4.9

Men

47.9

11.5

3.8

Women

50.7

12.2

4.1

1997:

1950:

1900:

Source: Federal Interagency Forum on Aging-Related Statistics. Older Amerkans 2000: Key Indicators of Well-Being. Washington, DC: US Government Printing Office, 2000.

Life-expectancy There have been vast improvements in life-expectancy at birth (i.e. the average number of years a person will live given the age-specific mortality rates of a particular year), which has increased from 47.9 and 50.7 years for men and women, respectively, in 1900 to 73.6 and 79.4 for men and women, respectively, in 1997. Table 4.2 shows average lifeexpectancy at birth, at 65, and at 85 for three selected years at approximate 50-year intervals in the 20th century. As indicated, there have been remarkable increases in lifeexpectancy even since 1950.10 We have been referring to the aged (or the elderly) using the traditional cut-off of 65 years. As we have emphasized elsewhere, definitions of old age for clinical purposes should be flexible and dependent on criteria other than calendar age.13,14 Persons aged 65 and older include the young old (i.e. 65–74), the older old (i.e. 75–84), and the oldest old (i.e. 85 and older). This subdivision into age cohorts is meant to reflect the heterogeneity of age within the older population, but to sharpen the focus on the unique problems that may be present in older persons in need of information on cancer prevention or those who have been newly diagnosed with cancer, we first must acknowledge the greater variability in health and age-related declines in functioning—the categorization does not


73

do this. The pace of aging varies from individual to individual. It has been suggested that no two individuals accumulate identical environmental or other types of insults alike. It is preferable to ask which patients would benefit from which treatments. The use of chronologic age as a guide for cancer prevention and therapy is not a good strategy for the elderly.14 Further, with respect to cancer detection, there may be a non-specific presentation of a malignancy (sometimes unique to the aged) that requires clinicians to be alert to masked symptomatology or to look for subtle signs of additional adverse conditions in the presence of the presenting complaint.14–18 For many older cancer patients, there may be competing concurrent chronic conditions (i.e. comorbidity) and decreased physical and physiologic functioning.15 When cancer is linked with the other chronic conditions acquired over a lifetime, there is a high probability that the residual consequences of previous illnesses and the effects of the normal and pathologic processes of aging, including frailty, will be present. There are differences in drug metabolism and changing levels of absorption, distribution, metabolism, and excretion that predominate in older persons.16 Cancer treatment strategies are challenged also by the potential for secondary complications of disease and treatment and the development of unrelated conditions during the course of cancer therapy. Other relevant concerns are comprehension deficits, diminished social support, and limited financial resources.17 These are several examples of the multiplicity of agerelated conditions that may exist concurrently with cancer management for the elderly. Implications for research and practice Cancer is not inevitable for all older persons, but persons in the older age groups appear to be more vulnerable to malignancies. Cancer in the elderly is a major healthcare concern that is beginning to generate interest and attention. The stark and concise summary statistics on cancer and aging indicate that the older segment of the US population is an important target group for cancer research and control activities. Studies using the SEER information database, with documentation presented by descriptive analyses such as those presented in this chapter, are capable of stratifying large amounts of patient data to raise issues for targeting clinical trials, cancer control, and biologic and epidemiologic investigations. They tell us where we should concentrate our efforts. Advancing the aging/cancer research interface The scientific approach to cancer treatment has begun to introduce the complexities of older persons who have been afflicted with cancer. Many changes within the several years since the publication of the first edition of this book are cited in other chapters in this second edition. Special efforts have been initiated in the private and federal sectors: (i) there has been a focus on screening and early detection for malignancies that could be prevented or diagnosed in the early stages (e.g. breast cancer in older women and colon cancer in older persons); (ii) attempts have been made to heighten and increase the awareness of oncologists, primary care physicians, and geriatricians about masked signs of


74

malignancies and/or altered presentation of signs and symptoms of cancer in the elderly; (iii) the presence of concomitant diseases, illnesses, and the normal processes of aging and how they affect the treatment of cancers in older persons is receiving greater attention;15 (iv) the differences and sensitivities of older cancer patients with regard to conventional forms of treatment are more widely acknowledged and under study; (iv) quality of life issues for care of the elderly are increasingly being linked with the psychological and social support that older persons need to cope with cancer and its treatment;19 (vi) the American Society of Clinical Oncology (ASCO) has devoted prime time to the topic of aging and cancer in annual educational symposia and has supported cancer/aging symposia and interdisciplinary clinical training initiatives that include geriatricians, medical oncologists, social scientists, and other healthcare professionals; (vii) stimulating conferences and workshops have been held, and their proceedings, several review articles, and more research published; (viii) the Annual Report to the Nation on Cancer in 2002 featured the implications of age and aging on the US Cancer Burden;6 (ix) the US National Institute on Aging (NIA) and NCI have been collaborating on research initiatives at the aging/cancer interface. Some specific examples from the NIA/NCI partnership are provided below. NIA/NCI research pmmotion activities The NIA formally established an extramural research focus on aging and cancer in September 1996. In consultation with an advisory group, an excellent plan was developed shortly after the official formation of the NIA Geriatrics Program Cancer Section.18 The following selected research areas for extramural initiatives were recommended: (i) agerelated factors in development of tumors in older persons; (ii) time and its importance in developing cancer in a person’s lifespan; (iii) aggressive tumor behavior in the aged patient; (iv) pharmacology of aging and cancer– antitumor drug alterations; (v) prognostic indicators for patient evaluation and workup; (vi) comorbidity, previous illnesses, and disabilities in older cancer patients; (vii) occurrence of multiple primary tumors in elderly patients; (viii) cancer survivorship—the need for long-term data on older survivors; (ix) access issues relevant to older patients, their families, and physicians; (x) generic age-related issues in selected tumors that predominate in older persons (e.g. breast, prostate, and colorectal tumors).18 Ten research solicitation requests for applications (RFA) and program announcements (PA) relevant to cancer in older persons have been initiated since the inception of the NIA extramural research program focusing on cancer in older persons:20 1. NIA RFA-AG-02–003: Aging, Race and Ethnicity in Prostate Cancer, August 2001 2. NCI/NIA RFA 99–015: Diagnostic Imaging and Guided Therapy in Prostate Cancer, August 1999 3. NCI/NIA RFA 98–018: Interdisciplinary Studies in Genetic Epidemiology of Cancer, August 1998 4. NIA/NCI/NINR PA 00–001: Aging Women and Breast Cancer, October 1999 5. NIA/NIDCR PA 99–030: Aging and Age as Risk Factors for Multiple Primary Tumors, December 1998 6. NIA/NCI Letter RFA: Limited Competition, Studies on Older Cancer Patients in the NCI Clinical Trials Cooperative Groups, October 1998


75

7. NIA/NCI PA 98–069: Cancer Pharmacology and Treatment in Older Patients, May 1998 8. NCI RFA 97–018: Long-Term Cancer Survivors: Research Initiatives, September 1997 9. NIA/NCI/NIEHS PA 97–019: Aging, Race, and Ethnicity in Prostate Cancer, December 1996 10. NIA/NCI/NINR/NIMH PA 96–034: Aging Women and Breast Cancer, April 1996. The NIA collaborates with the NCI in most efforts on cancer in the elderly. NIA or NCI takes the leadership role in the partnerships, depending on the topic. Some efforts are large-scale projects and/or co-sponsored workshops on research areas chosen to address knowledge gaps on discrete topics identified by the NIA; others involve establishing working relationships with individual NCI staff to develop key questions for research in common interest areas. An example of the former is the NIA/NCI partnership established under a cooperative agreement with the NCI by a memorandum of understanding. The NIA is sponsoring peer-reviewed research designed by the NCI Cooperative Groups with a focus on older-aged cancer patients. An example of the latter is demonstrated with the program announcements issued on breast cancer, prostate cancer, and pharmacology of aging and cancer. Comorbidity assessment of older cancer patients Cancer is diagnosed in bodies already rife with comorbid conditions. Therefore, there are competing diseases for treatment. There may be poor physical functioning due to ageassociated disabilities. It is not known to what extent concurrent health problems complicate cancer management in the older person or if non-specific signs and symptoms are masked by multiple pathology or frailty in the older person. The term ‘comorbidity’ in the NIA/NCI Workshop on Comorbidity Assessment referred to the concomitant age-related health problems (i.e. multiple pathology) often present in older persons. This topic continues as a needy area for research, and was the topic of a multidisciplinary working group initiated by the NIA and co-sponsored with the NCI in July 1999. A synopsis of the deliberations and specific issues has been published.15 The guiding questions were: • How do already-compromised older patients tolerate the stress of cancer and its treatment? • How do age-related conditions influence cancer treatment course and recovery? • How are the serious comorbid conditions managed in the presence of cancer?


76

Exploring the role of cancer centers for integrating aging and cancer research A major research initiative is in development. The NIA and NCI held an interdisciplinary workshop to discuss the evolution of research efforts in NCI-designated cancer centers. The workshop, Exploring the Role of Cancer Centers to Integrate Aging and Cancer Research, was held on the NIH Campus, Bethesda, MD in June 2001. The meeting provided a forum for the views of prominent cancer center directors, scientists, administrators, health professionals, and patient advocates on how to promote innovative studies within the cancer centers directed at cancer in the elderly. The final report from this workshop is available at http://nia.nih.gov/health/nianci.19 The NIA/NCI cancer centers’ objectives were to: 1. Identify promising scientific areas that could be pursued in the cancer centers with their unique resources and expertise. 2. Consider various strategies and approaches for implementation of integrating aging and cancer research. 3. Invite the input of investigators in the cancer centers by convening a workshop with cancer center representatives on the NIH Campus.

Final comments Oncology practice includes older cancer patients. Cancer prevention and early detection apply to older persons. The strong epidemiologic and demographic data are more than sufficient to urge us to go beyond mere description of cancer in the older population. The insights gained from this information help expand and direct the focus on the age segment of the US population that experiences the magnitude of the cancer problem. Acknowledgements This is an update of a paper, originally published in Cancer 1994; 74:1995–2003, © 1994 American Cancer Society, that was reprinted with permission of JB Lippincott Company, Philadelphia, PA in the 1st edition of this book. Demographic and cancer data have been updated; the chapter revision includes efforts made in recent years to advance the aging/cancer research interface. References 1. Ries LAG, Eisner, MP, Kosary CL et al (eds). SEER Cancer Statistics Review: 1973–1999. Bethesda, MD: National Cancer Institute. http://seer.cancer.gov/csr/1973_1999/,2002. 2. Cancer Facts and Figures—2002. Atlanta: American Cancer Society. http://www.cancer.org/downloads/STT/CancerFacts&Figures2002TM.pdf.


77

3. Trimble EL, Carter CL, Cain D et al. Representation of older patients in cancer treatment trials, Cancer 1994:74:2208–14. 4. Hutchins LF, Unger JM, Crowley JJ et al. Underrepresentation of patients 65 years of age or older in cancer treatment trials. N Engl J Med 1999:341:2061–7. 5. National Institutes of Health Consensus Development Panel. National Institutes of Health Consensus Development Conference statement: breast cancer screening for women ages 40–49, January 21–23, 1997. J Natl Cancer Inst 1997; 89:1015–26. 6. Edwards BK, Howe HL, Ries LAG et al. Annual Report to the Nation on the Status of Cancer, 1973–1999, Featuring Implications of Age and Aging on US Cancer Burden. Cancer 2002; 94:2766–92. 7. Vital Statistics ofthe United States 1950–1999. Vol 2: Mortality, Parts A and B. Hyattsville, MD: National Center for Health Statistics. 8. Taeuber CM. Sixty-Five Plus in America, revised edn. Washington, DC: US Government Printing Office, Current Population Reports, Special Studies, P23–178RV, 1993. 9. US Bureau of the Census. 65+ in the United States. Washington, DC: US Government Printing Office, Current Population Reports, Special Studies, P23–190, 1996. 10. Federal Interagency Forum on Aging-Related Statistics. Older Americans 2000: Key Indicators of Well-Being. Washington, DC: US Government Printing Office, 2000. 11. US Census Bureau. Population Estimates Program. Washington, DC: Population Division, August 2002. 12. Yancik R, Ries LG, Yates JW. Ovarian cancer in the elderly: an analysis of Surveillance, Epidemiology, and End Results program data. Am J Obstet Gynecol 1986; 154:639–47. 13. National Institute on Aging/National Cancer Institute/American Cancer Society. Perspectives on ovarian cancer in older-aged women: current knowledge and recommendations for research. Cancer 1993; 71 (Suppl): 513–660. 14. Yancik R, Ries LAG. Cancer burden in the aged: an epidemiologic and demographic overview. Cancer 1997; 80:1273–83. 15. Yancik R, Ganz PA, Varricchio CG, Conley B. Perspectives on comorbidity and cancer in older patients: approaches to expand the knowledge base. J Clin Oncol 2001; 19:1147–51. 16. Yancik R, Wesley MN, Ries LAG et al. Effect of age and comorbidity on treatment and early mortality in postmenopausal breast cancer patients aged 55 years and older, JAMA 2001; 285:885–92. 17. Yancik R, Wesley MN, Ries LAG et al. Comorbidity and age as predictors of risk for early mortality of male and female colon carcinoma patients: a population-based study, Cancer 1998; 82:2123–34. 18. Yancik R, Integration of aging and cancer research in geriatric medicine. J Gerontol Med Sci 1997; 52:329–32. 19. NIA/NCI Workshop Report: Exploring the Role of Cancer Centers to Integrate Aging and Cancer Research. http://nia.nih.gov/health/nianci. 20. NIH Archives Website. http://grants1.nih.gov/grants/guide/index.html

5 Epidemiological research in aging: Perspectives and limitations Marion RS Bain, Jean C Harvey Introduction Improved standards of living, improved nutrition, and better prevention and healthcare have led to increased life-expectancy in many parts of the world. The birth rate has also declined substantially in many countries. The consequence of these changes is an increasing average age in many populations. United Nations population predictions suggest that globally the number of people aged over 60 years will more than triple, to reach nearly two billion by 2050. For the oldest old, those aged 80 and over, the predictions are even more marked. A fivefold increase to 379 million is estimated.1 As the risk of most epithelial cancers increases with age, numbers of people with cancers can also be expected to grow. The World Health Report2 predicts that cancer will remain one of the leading causes of death worldwide. However, the report also suggests that over the next 25 years, the risk of cancer will stabilize or decline in industrialized countries. In developing countries, the risk will continue to increase. Sources of information on cancer in a population The two main sources of information on cancer in a population are mortality (derived from death certificates) and incidence (collected by cancer registries). Populationbased survival data can be calculated when these two sources are available for the population as a whole. Mortality data The accuracy of mortality data has generally been assessed in studies by one of two methods: • comparison of the clinical diagnosis with autopsy findings; • comparison between the clinical diagnosis recorded in case notes and the death certificate diagnosis. Studies from several countries have compared clinical diagnoses with autopsy findings.3–8 These studies vary in the source of cases and the percentage of deaths autopsied.

Epidemiological research in aging: Perspectives and limitations

79

However, in general, cancer uncovered at autopsy had been diagnosed clinically in 80– 90% of cases. Within this group, in 10–25%, the cancer site was either not known or attributed to the wrong site. The cancers that were most often missed or wrongly assigned clinically were lung, liver, and pancreatic cancers. Missed clinical diagnoses of cancer were commonly attributed to vascular or respiratory causes. A high percentage of clinical diagnoses of cancer were confirmed by autopsy (80– 90%), although again up to one-quarter had an incorrect or unknown site. Clinically, over-diagnosed cancers were commonly large-bowel cancers and pancreatic cancers. Vascular causes were the most common autopsy-detected cause of death in incorrect clinical diagnoses of cancer. Incorrect diagnoses occur more frequently with increasing age. In one study looking at routine autopsies (25% of all deaths) in Edinburgh Royal Infirmary, less than 50% of all clinical diagnoses were confirmed in those over 74.5 This low confirmation rate probably reflects greater diagnostic uncertainty in cases undergoing routine autopsy. A further study,9 with a higher percentage of deaths being subjected to autopsy (65%), showed higher confirmation rates, but a similar pattern of increasing diagnostic inaccuracy with increasing age (Table 5.1). Therefore, death certificates completed before or without

Table 5.1 Percentage of clinical diagnoses of cancer confirmed by autopsy in different age groups9 Age

% confirmed

75

75

Table 5.2 Comparison of detection and confirmation rates for selected cancer sites12 High detection rates and high confirmation rates (>80%)

Low detection rates and low confirmation rates (2 cm or ER-negative. dHazard ratio (95% confidence interval in parentheses).

Table 14.4 Six-year relapse-free survival rate (RFS) as a function of pathobiologic variables in patients aged 65 or more subjected to surgery and adjuvant hormonal therapy Univariate analysis Variable

No. of cases RFS (%) HR

a

Multivariate analysis

P

HRa

P

Patient age: 65–69 years 213

75

1.0

—

1.0

—

70–79 years 383

69

1.36 (0.96–1.94)

0.08

1.45 (1.00–2.10)

0.05

≥80 years

141

65

1.41 (0.89–2.24)

0.14

1.86 (1.11–3.13)

0.019

≤1 cm

41

84

1.0

—

1.0

—

1–2 cm

333

76

1.67 (0.67–4.14)

0.27

1.56 (0.62–3.88)

0.34

>2 cm

363

63

2.92 (1.19–7.17)

0.019

2.17 (0.88–5.37)

0.09

Tumor size:

Positive axillary lymph nodes 0

83

84

1.0

—

1.0

—

1–3

227

80

1.22(0.63–2.38)

0.56

1.57(0.80–3.09)

0.19

>3

167

47

3.88 (2.06–7.31)

0.0001 4.57 (2.40–8.69)

0.0001

nab

260

72

1.68 (0–88–3.22)

0.12

0.06

1.88(0.97–3.66)


316

ER status: positive

670

72

1.0

—

1.0

—

negative

67

53

2.20 (1.48–3.28)

0.0001 1.86 (1.18–2.94)

0.008

positive

511

73

1.0

—

1.0

—

negative

266

63

1.65 (1.22–2.23)

0.001

1.37 (0.98–1.93)

0.07

≤3%

391

74

1.0

—

1.0

—

>3%

346

66

1.44 (1.07–1.94)

0.016

1.38(1.02–1.87)

0.04

PgR status:

TLI:

a

b

Hazard ratio (95% confidence interval in parentheses). Not assessed.

In the subset of 755 patients subjected to radical or conservative surgery plus radiotherapy without any systemic treatment until relapse, 580 had histologically assessed lymph node-negative resectable breast cancers, with a prevalence of tumors 2 cm or less in diameter (65%; >80% with 1–2 cm tumors). The majority of these cases were ER-positive (83%) and from patients aged 65–69 (58%). A classification of these cases based on conventional pathobiologic factors (tumor size and ER) allowed the identification of low-risk (tumor size ≤1 cm), intermediate-risk (ER-positive tumors 1–2 cm in diameter), and high-risk (tumor size >2 cm or ER-negative) patients, exhibiting a 6-year probability of relapse of 16%, 25%, and 30%, respectively (Table 14.3), with an overall of 115 locoregional or distant relapses. Patient age and proliferative activity, singly, did not provide prognostic information. Conversely, proliferative activity was able to further segregate patients with favorable or unfavorable prognosis within the low- and intermediate-risk categories (Table 14.3). With regard to clinical outcome following systemic treatment, the predictive role of conventional clinical and pathobiologic features, including patient age, pathologic tumor size and lymph node involvement, ER and PgR, and proliferative activity, could be investigated, singly and in association, in 737 of the 808 patients previously identified, treated with endocrine therapy, mainly tamoxifen (20 or 30 mg/day) for at least 1 year, and with a median follow-up of 6 years (177 unfavorable events within 6 years from diagnosis). In univariate analysis, tumor size, lymph node involvement, ER, PgR, and TLI identified patients at low or high risk of relapse, and this predictive role was maintained for all these variables in a multivariate analysis in which patient age also acquired an independent prognostic significance (Table 14.4). Among biologic variables, ER showed the strongest predictive role for response to endocrine treatment, in agreement with the outcome of meta-analyses by the Early Breast Cancer Trialists’ Collaborative Group,14 even in elderly patients. Besides conventional pathobiologic features, an altered expression of p53 or of Bcl-2 also contributed to improve the prognostic resolution for patients treated with adjuvant hormonal therapy. Information on these biomolecular markers was available on a series of 145 patients aged over 70 (median age 74; range 70–88) with node-positive resectable tumors already characterized in terms of ER, PgR, and TLI, treated with tamoxifen (20 or

Biologic characteristics of primary breast cancer

317

30 mg/day) for at least 1 year and with a median follow-up of 7 years.15 In univariate analysis, the probability of relapse was unaffected by tumor size, whereas it was significantly related to the number of involved axillary lymph nodes, ER, TLI, p53, and Bcl-2, although with different discriminating powers. In particular, the hazard ratio (HR) for relapse for patients with ER-negative tumors or for patients with p53-overexpressing tumors was 3.4- and 4.4-fold that of patients with ER-positive or p53-negative tumors, respectively. In addition, the HR for patients with rapidly proliferating or Bcl-2-negative tumors was about 2-fold that of patients with slowly proliferating tumors or those with Bcl-2-overexpressing tumors. The absence of ER or p53 overexpression was associated with the most unfavorable prognosis (80% of patients relapsing within 7 years of diagnosis), whereas a low proliferation rate identified the lowest-risk subgroup of patients (with only 30% of patients relapsing at 7 years). These results held true when adjusted for tamoxifen treatment duration and ER status, and were paralleled by similar findings on overall survival. In a multivariate analysis carried out in the subset of ER-positive tumors, cell proliferation and p53 and Bcl-2 expression maintained their predictive significance. The integration of pathologic and biologic variables significantly improved the predictive resolution of each variable, considered singly, for the identification of either the low-

Figure 14.6 Relapse curves for patients with ER-positive tumors


318

treated with tamoxifen as a function of the risk profile defined by axillary lymph node involvement, TLI, and p53 and Bcl-2 expression. Low-risk: presence of only one unfavorable factor (>3 positive lymph nodes, high TLI, p53 overexpression, or Bcl-2 absent/weak expression). Intermediate risk: presence of two unfavorable factors. High-risk: presence of three unfavorable factors. risk or the high-risk patients. In fact, within the ER-positive subset (i.e. in women traditionally considered responsive to endocrine treatment and who benefit markedly from adjuvant tamoxifen), the favorable biologic profile, characterized by the presence of only one unfavorable factor (rapid proliferation or p53 overexpression, absent or weak Bcl-2 expression, or more than three involved axillary lymph nodes) allowed the identification of patients with a low probability to relapse at 7 years after starting adjuvant treatment (Figure 14.6). Conversely, an aggressive pathobiologic profile, characterized by the presence of two or three of the four unfavorable factors, identified patients who partially (in 50% of the cases) or totally (in 90% of the cases) escaped tamoxifen control, notwithstanding the presence of ER. The low-risk group includes about 50% of cases, the high-risk group accounts for about 20%, and the remaining 30% were included in the intermediate-risk subset. Although this analysis is exploratory and the data are hypothesis-generating and need to be validated by retrospective or prospective studies on independent series of patients, it could represent a preliminary framework for a biologically tailored therapy even for elderly breast cancer patients. Discussion and conclusions In the past, the interest of clinicians in designing innovative therapeutic protocols has only rarely focused on breast cancer patients aged over 65 or 70. This attitude was due to the exclusion of elderly patients from randomized clinical trials because of comorbid conditions and to spare them from the toxic side-effects of systemic treatment.16 This latter attitude also derived from the common, although still controversial, belief that elderly patients generally develop indolent disease, characterized by a lower responsiveness to treatment. However, against these statements, some reports showed a worse survival rate for elderly patients than for younger patients with metastatic disease,17 and a significant benefit of disease-free survival after treatments using drugs with limited side-effects, such as tamoxifen.18 In considering these demonstrated or only hypothesized findings, there is a case for a renewal of scientific interest in the biologic characterization of breast cancers from elderly patients. In fact, as has already occurred for cancers in younger patients, biologic


319

information on this subset of tumors could actually contribute to a better comprehension of the natural history of the disease in elderly patients, and possibly provide prognostic information and guidelines for treatment.19 Overall, in our study, tumors in patients aged 65 or more showed a tendency towards a lower proliferative rate, a lower frequency of p53 expression, a higher ER content, and a slightly more frequent Bcl-2 expression or presence of diploid clones than tumors from younger patients. The PgR positivity in tumors from patients over 65, although higher than that observed in tumors from patients under 35, did not differ from the PgR positivity observed in tumors from patients aged 50–64. It should be investigated whether the pronounced increase in PgR content in patients older than 75 is ascribable only to the presence of free receptors or represents a peculiar feature of very old patients. p53 and Bcl-2 expression were respectively inversely and directly associated with patient age, and their pattern of association, which has an implication for tumor progression and treatment response in younger patients, was maintained even in elderly patients. In general, the relationships between the different biomarkers and the weak or even absent association with clinicopathologic factors observed in tumors from elderly patients are in keeping with results from similar analyses on tumors from younger patients. The absence of steroid receptors, the presence of aneuploid clones, p53 overexpression, and weak or absent Bcl-2 expression were associated with rapid proliferation, and indirectly these findings should indicate that biologic aggressiveness could be defined on the basis of such features, even for tumors from elderly patients. It is worth mentioning that cancers from elderly patients are associated with a more favorable pathobiologic phenotype compared with those from younger patients.6,7 In fact, only 30% of elderly patients presented at diagnosis with three or more unfavorable factors (including the presence of tumors larger than 2 cm, steroid receptor-negative, rapidly proliferating, overexpressing p53, or with absent or weak Bcl-2 expression), compared with about 50% of patients aged 34 or less, and with about 40% of patients aged 35–64. Steroid receptors, proliferation, and apoptosis-related markers proved to be indicators of long-term clinical outcome, following either local regional or hormonal therapy, although their clinical impact was mainly evident for the latter treatment, and we have now validated their predictive role, already assessed in tumors from younger patients subjected to different treatment modalities,9,20–24 including local regional and adjuvant chemotherapy. It should be stressed that the present data were mainly obtained on elderly patients subjected to endocrine treatment, which is known to provide the highest benefit for tumors with hormone receptors14 and low cell proliferation.15,20,25 However, a separate analysis on the subset of ER-positive tumors, conventionally considered hormoneresponsive, again showed that the best prognosis was identified by low TLI, absent or weak p53 expression, or Bcl-2 overexpression in association with a small number of positive nodes.15 Whether these biomolecular markers can be considered to be specifically responsible for a benefit from hormonal therapy or to be only favorable prognostic indicators, associated with a differentiated phenotype, is still an open question. All these data have been derived from retrospective analyses, and need to be prospectively confirmed. For elderly patients, for whom the cost-benefit of treatment should be carefully assessed, it would seem reasonable to use biologic findings as a complement to clinicopathologic features in a ‘risk factor profile system’ for treatment planning. However, this hypothesis should be assessed and validated in prospective


320

studies, with an associated high level of evidence, even when considering the observation derived from the San Antonio breast cancer database in favor of a decreased impact of breast cancer on survival as patient age increases.7 Notwith-standing the possible limitations and bias of the study, also emphasized by the authors,7 the presence of biologic features characterizing an indolent disease and the favorable outcome of elderly patients regardless of disease status should be taken into consideration when making clinical decisions. References 1. Baranofsky A, Myers MH. Cancer incidence and survival in patients 65 years of age and older. Cancer 1986; 36:26–41. 2. Surveillance, Epidemiology, and End Results (SEER) Program. Public use CD-ROM (1973– 1995). Bethesda, MD: Cancer Statistics Branch, National Cancer Institute, 1998. 3. Bast RC, Ravdin P, Hayes DF et al. 2000 Update of recommendations for the use of tumor markers in breast and colorectal cancer: clinical practice guidelines of the American Society of Clinical Oncology. J Clin Oncol 2001; 19:1865–78. 4. National Institutes of Health Consensus Development Conference Statement. Adjuvant Therapy for Breast Cancer, November 1–3, 2000. J Natl Cancer Inst 2001; 93:979–89. 5. Goldhirsch A, Glick JH, Gelber RD et al. Meeting Highlights: International Consensus Panel on the Treatment of Primary Breast Cancer. J Clin Oncol 2001; 19:3817–27. 6. Valentinis B, Silvestrini R, Daidone MG et al. 3H-thymidine labeling index, hormone receptors, and ploidy in breast cancers in elderly patients. Breast Cancer Res Treat 1991; 20:19–24. 7. Diab SG, Elledge RM, Clark GM. Tumor characteristics and clinical outcome of elderly women with breast cancer. J Natl Cancer Inst 2000; 92:550–6. 8. Anderson WF, Chu KC, Chatterjee N et al. Tumor variants by hormone receptor expression in white patients with node-negative breast cancer from the Surveillance, Epidemiology, and End Results database. J Clin Oncol 2001; 19:18–27. 9. Silvestrini R, Daidone MG, Luisi A et al. Biologic and clinicopathologic factors as indicators of specific relapse types in node-negative breast cancer. J Clin Oncol 1995; 13:697–704. 10. Silvestrini R, Daidone MG, Del Bino G et al. Prognostic significance of proliferative activity and ploidy in node-negative breast cancers. Ann Oncol 1993; 4:213–19. 11. Silvestrini R, Benini E, Daidone MG et al. The bcl-2 protein: a prognostic indicator strongly related to p53 protein in lymph node-negative breast cancer patients. J Natl Cancer Inst 1994; 86:499–504. 12. McGuire WL. Breast cancer prognostic factors: evaluation guidelines (editorial, comment). J Natl Cancer Inst 1991; 83:154–5. 13. Hayes DF, Trock B, Harris AL. Assessing the clinical impact of prognostic factors: when is ‘statistically significant’ clinically useful? Breast Cancer Res Treat 1998; 52:305–19. 14. Early Breast Cancer Trialists’ Collaborative Group. Tamoxifen for early breast cancer: an overview of the randomised trials. Lancet 1998; 351:1451–67. 15. Daidone MG, Luisi A, Martelli G et al. Biomarkers and outcome after tamoxifen treatment in node-positive breast cancers from elderly women. Br J Cancer 2000; 82:270–7. 16. Balducci L, Extermann M, Fentiman I et al. Should adjuvant chemotherapy be used to treat breast cancer patients (≥70 years of age)? Eur J Cancer 1997; 33:1720–4. 17. Yancik R, Ries LG, Yates JW. Breast cancer in aging women. A population-based study of contrasts in stage, surgery and survival. Cancer 1989; 63:976–81.


321

18. Castiglione M, Gelber RD, Goldhirsch A. Adjuvant systemic therapy for breast cancer in the elderly: completing causes of mortality. International Study Group. J Clin Oncol 1990; 8:519– 26. 19. Silliman RA, Balducci L, Goodwin JS et al. Breast cancer care in old age: what we know, don’t know, and do. J Natl Cancer Inst 1993; 85: 190–9. 20. Daidone MG, Silvestrini R. Prognostic and predictive role of proliferation indices. J Natl Cancer Inst Monogr 2001; 30:27–35. 21. Thor AD, Berry DA, Budman DR et al. ErbB-2, p53 and efficacy of adjuvant therapy in lymph node-positive breast cancer. J Natl Cancer Inst 1998; 90:1346–60. 22. Silvestrini R, Luisi A, Zambetti M et al. Cell proliferation and outcome following doxorubicin plus CMF regimens in node-positive breast cancer. Int J Cancer 2000; 87:405–11. 23. Elledge RM, Green S, Howes L et al. bcl-2, p53, and response to tamoxifen in estrogen receptor-positive metastatic breast cancer: a Southwest Oncology Group study. J Clin Oncol 1997; 15: 1916–22. 24. Daidone MG, Luisi A, Veneroni S et al. Clinical studies of Bcl-2 and treatment benefit in breast cancer patients. Endocrine Rel Cancer 1999; 6:61–8. 25. Scarpi E, De Paola F, Sarti M et al. Biomarker prediction of clinical outcome in operable breast cancer patients treated with tamoxifen. Breast Cancer Res Treat 2001; 68:101–10.

15 Clinical evidence for change in tumor aggressiveness with age: A historical perspective Frederick F Holmes Introduction Age is the most important risk factor for cancer. Cancer incidence at age 80 is nearly 250 times as great as at age 8. While it is trite to say that a group of 80-year-olds is much more diverse than a group of 8-year-olds, nonetheless, uniformity is a characteristic of youth and diversity a characteristic of old age. On this basis alone, it is likely that there is diversity among cancers afflicting the elderly. A critical question, for which there is no answer at present, is whether or not old people have old tumors. Some neoplastic cell lines are immortal, seemingly having escaped aging altogether. Whether or not tumors age, hosts do age, particularly in regard to immunocompetence. Tumor growth is obviously a product of intrinsic cellular factors as well as host factors, some of which may be humoral and thus affect tumors directly. To confound matters, it is difficult to separate the intrinsic properties of any cancer from the defenses of its host. More than 80 years ago, Sistrunk and McCarty1 studied the contributions of cellular differentiation, hyalinization, fibrosis, and lymphocytic infiltration to prolonged survival in breast cancer. They thought that lymphocytic infiltration was not the most important factor but rather cellular differentiation and hyalinization. Even those who have attempted to focus specifically on host factors influencing the growth of tumors in humans have found that the degree of differentiation of tumors is intimately related to expression of host factors.2 Ershler3 has characterized host factors as the ‘soil’ and the tumor itself as the ‘seed’. Let us see if an old seed germinates differently than a young seed. To do this, one can view the tumor in terms of stage and growth, intrinsic aspects of histology, and survival of the host. Stage and growth The relationship between age and cancer stage at the time of diagnosis was described in 1981 by Holmes and Hearne.4 They found increasing age to be significantly related to increased stage at diagnosis in cancers primary to breast, cervix, endometrium, ovary, and urinary bladder, and less significantly related in cancers primary to kidney and stomach. In colorectal cancer, there was no relationship, and in lung cancer, there was a significant

Clinical evidence for change in tumor aggressiveness with age

323

inverse relationship of stage to age. In 1986, Goodwin et al5 studied 15 varieties of cancer, and found melanoma and cancers of breast, cervix, endometrium, ovary, thyroid, and urinary bladder more likely to be diagnosed at an advanced stage with increasing age, with no trend of stage with age for colon, gallbladder/liver, kidney, or prostate cancers. For cancers primary to lung, pancreas, rectum, and stomach, there was an inverse trend, with lung being highly significant. The data for these two studies are shown in Table 15.1. The methods of analysis were not the same, but the results are generally concordant. Another view of the relationship of stage to age may be obtained by reviewing large autopsy studies. An early study cataloged locations of metastases in 1000 consecu-

Table 15.1 Relationship of stage at diagnosis of common cancers to increasing patient age: studies by Holmes and Hearne4 and Goodwin et al5 Site

Holmes and Hearne

Goodwin et al

Breast

Increase

Increase

Cervix

Increase

Increase

Colon

—

Neutral

Colorectum

Neutral

—

Endometrium

Increase

Increase

Gallbladder/liver

—

Neutral

Kidney

Increase

Neutral

Lung

Decrease

Decrease

Melanoma

—

Increase

Ovary

Increase

Increase

Pancreas

—

Decrease

Prostate

—

Neutral

Rectum

—

Decrease

Stomach

—

Decrease

Thyroid

—

Increase

Urinary bladder

Increase

Increase

tive cancer cases in a large metropolitan hospital without more than a general reference to age as a potential factor influencing numbers and distributions of metastases.6 In an autopsy series of 3535 patients aged over 65, Suen et al7 noted that cancer tended to metastasize less frequently in the elderly. They found this in cancers primary to breast, colon, kidney, lung, pancreas, prostate, rectum, stomach, urinary bladder, and uterus. The numbers of cases were small in the oldest age groups and no statistical analysis was reported. Another finding of note from their study was that the number of cancers newly


324

diagnosed at autopsy increased as a percentage of all cancers by age, from 20.7% in the 66–75 age group to 36.2% in those 86 and older. Studying gastric cancer in Japan, Esaki et al8 found peritoneal involvement to be less in older patients, but no difference in hepatic involvement between the elderly and those younger. More recent studies from Japan have shown that early gastric carcinomas in the very old tend to be well differentiated when compared with the middle-aged, but these cancers do become less differentiated as they grow, eventually matching those of the middle-aged patients.9 This raises the possibility that many cancers in the elderly may be relatively indolent and not cause symptoms during the life of the patient. McFarlane et al10 make this point in their autopsy study. Studying cancers found at autopsy in patients from ages 75 to 106, researchers in Trieste, Italy, found that cancer prevalence declined after age 90, as did mortality from cancer.11 Some think that these autopsy-discovered cancers tend to be more differentiated than those diagnosed during life. In focusing on particular cancers, an autopsy study of 1828 renal adenocarcinomas in Japan found a considerable decrease in the number of metastases with age generally and in organs usually bearing metastases specifically.12 Much the same phenomenon was demonstrated by Ershler et al13 in lung cancer. The magnitude of the trend of decreasing stage with increasing age in lung cancer is considerable. A study of 22 874 lung cancer cases showed local-stage disease in 13.9% of those less than 54 years of age, 19.2% in those aged 55–64, 21.4% in those aged 65–74, and 25.4% in those aged 75 and older.14 Quite apart from other considerations, this makes routine screening for curable lung cancer in the elderly a much more attractive possibility than in the middle-aged. At least part of the reason for the stage-to-age trend in lung cancer is the changing balance of histologies with age shown in a study of 9062 histologically confirmed lung cancer cases by Teeter et al.15 Squamous cell carcinoma increased from 26% to 40% of the total cases between ages 40 and 80, and adenocarcinoma and small cell carcinoma declined proportionately, with large cell carcinoma unchanged. The proportion of staged cases with local disease increased from 27% to 54% for squamous cell carcinoma between ages 40 and 80, with smaller but statistically significant increases for all other histologies except large cell carcinoma. Yancik et al16 focused on data for 125000 women with breast cancer from the US National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) program, in order to study the relationship of age to stage and survival. They found that women presenting with distant disease or unstaged disease were more likely to be elderly. Growth rates for breast cancer are highly variable. Spratt et al17 found an inverse relationship between patient age and tumor size at mammographic diagnosis. Mean tumor diameter for those younger than 70 was 13 mm, while for those older it was 9 mm. There were no age differences in doubling times or growth rates. None of the observations by Spratt et al reached statistical significance. Other studies have shown age-related lead time differences, and Pelikan and Moskowitz18 have created mathematical models to study mammographic screening using numbers that presume slower tumor doubling in older women. One other factor of stage-to-age relationships deserves mention. Where a cancer arises in a particular organ may be of importance. In 1977, Rhodes et al19 described a shift from distal to proximal subsite origin of colorectal cancer during the preceding three decades. In 1985, Butcher et al,20 from this same group, identified increasing age and female

Clinical evidence for change in tumor aggressiveness with age

325

gender as two factors that are at least partly responsible for this interesting phenomenon. In this vein, elderly women are more likely to have medial and central breast cancers than younger women.21 Right-sided colon cancers cause symptoms later than those near the rectum, and medial breast cancers are more likely to spread to lymph nodes within the chest than lateral cancers. Intrinsic aspects of histology Scrutiny of chemically stained small pieces of tumor tissue under the microscope has been common practice for over a hundred years. Yet, even the most clever pathologist cannot determine the age of the patient by microscopic examination of his or her cancer. The relationships of cancer histology to age have not received much attention over the years. In 1949, Lees and Park22 surveyed the extant literature and studied hundreds of cases of their own. They concluded that histologic indicators of cancer aggressiveness or indolence did not appear to be a function of patient age, with the possible exception of carcinoma of the lung. On the other hand, indolent cancers may be more common in the young than the old at sites such as the ovary.23 Carcinoma of the cervix and its precursor states are uniquely available to histologic study through exfoliative cytology. An atypical Papanicolaou cervical smear in a woman aged over 60 is 16 times more likely to lead to a diagnosis of invasive cancer than one in a woman younger than 30.24 Some think that in situ carcinoma of the cervix often has a distinctive cytologic appearance in the elderly, characterized by a large number of keratinizing cancer cells with a variable admixture of lesser numbers of third-type cells of Graham.25 In addition, there is evidence for a slowly evolving cervical cancer in young women and a more rapidly evolving one in older women.26,27 Much of the study of the relationship of cancer histology to age has been pursued with breast cancer. The distributions of the various histologic types of breast cancer are different when older women are compared with middle-aged and younger women.28 Most breast cancers, regardless of age, are infiltrating ductal carcinomas. A higher histologic grade is most common in the youngest breast cancer patients, as are inflammatory and medullary breast cancers. Infiltrating lobular and colloid carcinomas were found to be especially common among the elderly.21,29 Breast cancers in elderly women are more likely to be diploid, and thus relatively slowly growing.30 The very large study of 125000 women with breast cancer conducted by Yancik et al16 found medullary carcinoma to decrease and mucinous carcinoma to increase with age. Other histologies changed little with aging. Identifying cellular components by methods other than microscopy has been a burgeoning field in the past several decades. Perhaps the best example of the utility of these techniques in neoplasia is the quantification of estrogen and progesterone receptors (ER and PgR) in breast cancer cells. Repeatedly, an increasing likelihood of the presence of ER protein has been correlated with increasing age, and the mean concentration increases with age as well. This association is independent of all of the other breast cancer risk factors.31,32 The same seems to be true for PgR, and a higher survival rate in patients with ER and PgR positivity has been demonstrated.33 It seems likely that, at least in part, this phenomenon is related to cellular differentiation.


326

For many years, it has been known that there is a relationship between histologic grade and survival in cancer.1,34 People with higher-grade cancers (i.e. cancers that are less differentiated) have shorter survivals than those with lower-grade cancers. This has no particular relationship to the size of the primary tumor, but it has great prognostic value when the issues of screening and likelihood of cancer cure are addressed.35 Using unpublished data from the Cancer Data Service, the regional cancer registry for Kansas and western Missouri, it is possible to compare distributions by age for differentiated and undifferentiated histologies for common carcinomas. The results of this simple chi-square analysis are shown in Table 15.2. The numbers of cases are large, so the differences may have more apparent significance than clinical significance. Nonetheless, there does seem to be a trend towards less differentiation with increasing age for

Table 15.2 Relationship of increasing age to increasing histologic grade for common carcinomas: Cancer Data Service, 1982–87 Type of carcinoma

Number

Significance of increasing age/grade trenda

Breast

2303

NS

Colon/rectum

5140

p

Comprehensive Geriatric Oncology

Practical Geriatric Oncology (Cambridge Medicine)

Practical Geriatric Oncology (Cambridge Medicine)

Geriatric Rheumatology: A Comprehensive Approach

Geriatric Oncology: Treatment, Assessment and Management

Pediatric Oncology A Comprehensive Guide

Comprehensive Textbook of Genitourinary Oncology 3rd Edition

Pediatric Oncology: A Comprehensive Guide, 2nd Edition

Biological Basis of Geriatric Oncology (Cancer Treatment and Research)

Canine and Feline Geriatric Oncology: Honoring the Human-Animal Bond

Biological Basis Of Geriatric Oncology Cancer Treatment And Research

Geriatric Diabetes

Geriatric Otolaryngology

Geriatric Medicine

Geriatric Medicine

Geriatric Otolaryngology

Geriatric Psychiatry

Biotherapy: A Comprehensive Overview (Jones and Bartlett Series in Oncology)

Geriatric Anesthesiology, 2nd Edition

Geriatric Physical Therapy, 3e

Geriatric Palliative Care

Surgical Oncology

Nutritional Oncology

Urological Oncology

Gynecologic Oncology

Urological Oncology

Surgical Oncology

Oncology: An Evidence-Based Approach (Chang, Oncology)

Urologic Oncology

Challenges in Acute Geriatric Care

Geriatric Sleep Medicine (Sleep Disorders)

Comprehensive Geriatric Oncology

Practical Geriatric Oncology (Cambridge Medicine)

Practical Geriatric Oncology (Cambridge Medicine)

Geriatric Rheumatology: A Comprehensive Approach

Geriatric Oncology: Treatment, Assessment and Management

Pediatric Oncology A Comprehensive Guide

Comprehensive Textbook of Genitourinary Oncology 3rd Edition

Pediatric Oncology: A Comprehensive Guide, 2nd Edition

Biological Basis of Geriatric Oncology (Cancer Treatment and Research)

Canine and Feline Geriatric Oncology: Honoring the Human-Animal Bond

Biological Basis Of Geriatric Oncology Cancer Treatment And Research

Geriatric Diabetes

Geriatric Otolaryngology

Geriatric Medicine

Geriatric Medicine

Geriatric Otolaryngology

Geriatric Psychiatry

Biotherapy: A Comprehensive Overview (Jones and Bartlett Series in Oncology)

Geriatric Anesthesiology, 2nd Edition

Geriatric Physical Therapy, 3e

Geriatric Palliative Care

Surgical Oncology

Nutritional Oncology

Urological Oncology

Gynecologic Oncology

Urological Oncology

Surgical Oncology

Oncology: An Evidence-Based Approach (Chang, Oncology)

Urologic Oncology

Challenges in Acute Geriatric Care

Geriatric Sleep Medicine (Sleep Disorders)

Recommend Documents