Renal Transplantation: Sense and Sensitization

RENAL TRANSPLANTATION: SENSE A N D SENSITIZATION

D E V E L O P M E N T S IN N E P H R O L O G Y

Renal Transplantation: Sense and Sensitization by

SHEILA M: G O R E M R C Biostatistics Unit, Cambridge, U.K. and

BENJAMIN A. B R A D L E Y U.K. Transplant Service, Bristol U.K.

Council of Europe

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STRASBOURG

Kluwer Academic Publishers D O R D R E C H T / BOSTON / LONDON

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Library of Congress Cataloging-in-Publication Data Gore, Sheila M. Renal transplantation : sense and sensitization / Sheila M. Gore, Benjamin A. Bradley. p. cm.--(Developments in nephrology) ISBN 0-89838-370-6 (U.S.) 1. Kidneys--Transplantation--Immunological aspects. I. Bradley, Benjamin A., 1942II. Title. III. Series. [DNLM: 1. Graft Survival. 2. HLA Antigens. 3. Kidney-transplantation. 4. Transplantation Immunology. W1 DE998EB / WJ 368 G666r] RD575.G67 1988 617.4'610592--dc19 DNLM/DLC 88-1408 for Library of Congress CIP ISBN 0-89838-370-6 Kluwer Academic Publishers incorporates the publishing programmes of Dr W. Junk Publishers, MTP Press, Martinus Nijhoff Publishers, and D. Reidel Publishing Company. Distributors for the United States and Canada: Kluwer Academic Publishers, I01 Philip Drive, Norwell, MA 02061, USA for all other countries: Kluwer Academic Publishers Group, P.O. Box 322, 3300 AH Dordrecht, The Netherlands

Copyright © 1988 by Kluwer Academic Publishers, Dordrecht and Council of Europe, Strasbourg. 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, mechanical, photocopying, recording, or otherwise, without the prior written permission from the copyright owners. PRINTED IN THE NETHERLANDS

DIRECTOR OF STUDIES Professor B A Bradley UK Transplant Service and National Tissue Typing Reference Laboratory Southmead Road, BRISTOL BS10 5ND UK BIOSTATISTICIAN TO THE STUDY Dr S M Gore MRC Biostatistics Unit 5 Shaftesbury Road CAMBRIDGE CB2 2BW UK MEMBERS OF THE STUDY GROUP Prof Dr med E Albert National Reference Laboratory on Histocompatibility Universitat Munchen Pettenkoferstrasse 8a D-8000 MUNCHEN 2 Germany Dr F H J Claas Department of Immunhaematology and Bloodbank University Hospital Rijnsburgerweg 10 2333 AA LEIDEN The Netherlands Dr R Fauchet and Prof B Genetet Laboratoire d'Histocompatibilite Centre Regional de Transfusion Rue Pierre Jean Gineste 3500 RENNES France

Dr M Jeannet H6pital Cantonal Division d'Immunologie 24 Rue Micheli-du-Crest 1211 GENEVE 4 Switzerland Dr M Madsen and Dr L Lamm Tissue Typing Laboratory Aarhus Kommunehospital DK-8000 AARHUS C Denmark Dr G Persijn Eurotransplant Foundation c/o Bloodbank University Hospital Rijnsburgerweg 10 2333 AA LEIDEN The Netherlands Dr M Scalamogna and Prof G Sirchia Centre de Transfusion et d'Immunohaematologie via Francesco Sforza 35 MILAN Italy

Secretariat: Mrs Vera Boltho-Massarelli, Council of Europe ORGAN SHARING ORGANISATIONS INVOLVED IN THE STUDY: Eurotransplant France-Transplant Hispano Transplant Luso Transplant North Italy Transplant Scandia Transplant Swiss Transplant UK Transplant Service

vi The Study Group acknowledge the invaluable assistance of the following centres who have provided data to this study.

AUSTRIA I Medizinische Universit~itsklinik GRAZ I Universit~itsklinik ffir Chirurgie INNSBRUCK Allgemeines Krankenhaus LINZ Krankenhaus der Elisabethinen LINZ Allgemeines Krankenhaus WlEN Institut fiJr Blutgruppenserologie WlEN Kinderdialyse Allgemeines Krankenhaus WIEN

BELGIUM Academisch Ziekenhuis der Vrije Universiteit BRUSSEL/JETTE Cliniques Universitaires St Luc BRUXELLES Hopital Erasme BRUXELLES Universit6 Catholique de Louvain Tissue Typing Laboratory BRUXELLES Academisch Ziekenhuis Antwerpen EDEGEM Bloedtransfusie Centrum Antwerpen Belgische Rode Kruis EDEGEM Academisch Ziekenhuis GENT

Bloedtransfusiecentrum Belgische Rode Kruis LEUVEN Kinderdialyse U Z St Rafael Gasthuisberg LEUVEN Univ Ziekenhuizen St Rafael Gasthuisberg LEUVEN Laboratoire des Groupes Sanguins Universit~ de Liege LIEGE Universit+ de Liege LIEGE

DENMARK Department of Clinical Immunology The Tissue Typing Laboratory Blood Bank and Blood Grouping Laboratory Aarhus Kommunehospital AARHUS Urological Department Aarhus Kommunehospital AARHUS Department of Medicine Rigshospitalet COPENHAGEN The Tissue Typing Laboratory Rigshospitalet COPENHAGEN Renal Unit K A S Herlev HERLEV Department of Nephrology Odense Sygehus ODENSE

vii FINLAND Tissue Typing Laboratory Finnish Red Cross Blood Transfusion Service HELSINKI University Central Hospital Unioninkatu HELSINKI

FRANCE Transplant Unit BORDEAUX Centre de Transfusion Sanguine LYON Transplant Unit NANTES Laboratoire d'Histocompatibilit6 Centre Hayem H6pital Saint-Louis PARIS Transplant Unit RENNES Transplant Unit TOULOUSE

GERMANY Neues Klinikum der RWTH Abt Med Mikrobiologie Gewebetypisierung AACHEN Rheinisch Westfalische Technische Hochschule AACHEN

Klinikum Steglitz Haematol Zentrallabor Labor ffir Gewebetypisierung BERLIN Medizinische Einrichtungen der Univ Kliniken BONN Bluttransfusionsdienst Klinikum Freien Hansestadt BREMEN Institut ffir Blutgerinnung und Transfusionsmedizin DUSSELDORF Medizinische Einrichtungen der Universit/it DUSSELDORF Institut ffir Klinische Immunologie ERLANGEN Medizinische Einrichtungen der Universit~it ESSEN Zentrum fiir med Okologie fiir Immunogentick ESSEN Immunhaematologische Abteilung der Universit/~t Blutspendedienst Hessen FRANKFURT Johan Wolfgang Goethe Universit/it FRANKFURT/MAIN

DRK Blutspendedienst HLA-Labor BAD KREUZNACH

Albert Ludwigs Universit/it FREIBURG

Klinikum Steglitz der Freie Universit/it BERLIN

Blutspendedienst Tissue Typing Labor FREIBURG/BREISGAU

viii Inst fiir Klin Immunologie und Transfusionsmedin Tissue Typing Labor GIESSEN Universit~itsklinik HLA-Labor GOTTINGEN Medizinische Einrichtungen der Universit/it GOTTINGEN

Universit/its Kinderklinik KOLN Medizinische Hochschule LUBECK Medizinische Hochschule Institut fiir Immunologie und Transfusionsmedizin LUBECK

Universit~itskrankenhaus Eppendorf HAMBURG

Klinikum der Phillipsuniversit~it Zentrum f'tir Innere Medizin HLA-Labor MARBURG

Nephrologische Zentrum Niedersachsen HANN MUNDEN

Kinderpoliklinik der Universit~it HLA-Labor MUNCHEN

Medizinische Hochschule HANNOVER

Klinikum Rechts der Isar MUNCHEN

Institut ffir Immunologie und HLA-Labor HEIDELBERG

Ludwig Maximilians Universit~it MUNCHEN

Ruprecht Karls Universit~it HEIDELBERG Medizinische Universit~it Klinik HOMBURG/SAAR Institut fiir Rechtsmedizin HLA-Labor KAISERSLAUTERN St~idtisches Krankenhaus KAISERSLAUTERN

Westfalische Wilhelms Universit~it MUNSTER SRidtische Krankenanstalten NURNBERG Abteilung fiir Transfusionswesen HLA-Labor TUBINGEN Eberhard Karls Universit/it TUBINGEN

Institut fiir Rechtsmedizin KASSEL

D R K Blutspendedienst Abt fiir Transplantationsimmunologie HLA-Labor ULM

Abteilung Immunologie HLA-Labor KIEL

Universitfit Ulm ULM

Christian Albrechts Universit~it KIEL

Julius Maximilians Universit~it WURZBURG

Institut fCir Transfusionmedizin HLA-Labor KOLN/MERHEIM Medizinische Universit~it KOLN

IRELAND Beaumont Hospital (Formerly Jervis Street Hospital) DUBLIN

ix ITALY

NETHERLANDS

Ospedale Regionale "Spedali Civili" Divisione Nefrologia e Dialisi BRESCIA

Academisch Medisch Centrum AMSTERDAM

Ospedale Regionale "S Martino" Anatomia Chirurgica dell 'Universita' GENOVA Ospedale Maggiore Policlinico di Milano Divisione Nefrologia e Dialisi MILAN Ospedale Nigurada Divisione Nefrologia e Dialisi MILAN Ospedale Maggiore Policlinico di Milano Instituto di Science Mediche dell 'Universita' MILAN Istituto Scientifico "S Raffaele" Divisione Medicina I SEGRATE Ospedale Regionale "S Maria dei Battuti" Divisione Nefrologia ed Dialisi TREVISO Ospedale Regional "Maggiore di S G Battista e della Citt~ di Torino-Molinette" Divisione Nefrologia e Dialisi TORINO Ospedale Regionale "Civile Maggiore" Catterdra di Nefrologia Chirurgica VERONA

Centraal Laboratorium Bloedtransfusiedienst Nederlandse Rode Kruis AMSTERDAM Academisch Ziekenhuis GRONINGEN •

Academisch Ziekenhuis Bloedgroepenlaboratorium GRONINGEN Academisch Ziekenhuis LEIDEN Academisch Ziekenhuis MAASTRICHT St Radboud Ziekenhuis Leucocytenlaboratorium NIJMEGEN St Radboud Ziekenhuis NIJMEGEN Academisch Ziekenhuis Dijkzigt ROTTERDAM Sophia Kinderziekenhuis ROTTERDAM Academisch Ziekenhuis UTRECHT Wilhelmina Kinderziekenhuis UTRECHT

NORWAY Rikshospitalet OSLO

LUXEMBOURG PORTUGAL Centre Hospitalier de Luxembourg Tissue Typing Laboratory LUXEMBOURG

Centro de Histocompatibilidade do Sol LISBOA

SPAIN

SWITZERLAND

Clinica Puerta de Hierro Servicio de Immunologia MADRID

Abteilung fiir Nephrologie Kantonsspital BASEL

Hopital 1° de Octubre Carretara Andalucia MADRID

Transplantations-Labor Institut fiir Klin Immunologie Inselspital BERN

SWEDEN Department of Transplantation Surgery and Institute for Transplantations Immunology The Blood Central Sahlegrenska Sjukhuset GOTHENBURG Department of Transplantation Surgery Sahlgrenska Sjukhuset GOTHENBURG Department of Clinical Immunology Huddinge Hospital HUDDINGE

Blutspendezentrum Kantonsspital St GALLEN Division de N6phrologie H6pital Cantonal Universitaire GENEVE Division d'Immunologie & Allergie Department de M6decine LAUSANNE Abteilung fiir Chirurgie Universifiitsspital ZURICH

UNITED KINGDOM Departments of Transplantation Surgery and Clinical Immunology Royal Infirmary* Huddinge Sjukhus ABERDEEN HUDDINGE Belfast City Hospital Laboratory of Transplantation BELFAST The Blood Centre Queen Elizabeth Hospital Lasarettet BIRMINGHAM LUND Southmead Hospital Department of Surgery BRISTOL Malmoe Allmaenna Sjukhus MALMOE Department of Clinical Immunology Akademiska Sjukhuset UPPSALA

Addenbrookes Hospital CAMBRIDGE Cardiff Royal Infirmary CARDIFF

Department of Transplantation Surgery Akademiska Sjukhuset UPPSALA

Western General Hospital EDINBURGH

* Only waiting list data from these centres were included in the study.

St James Hospital LEEDS

Western Infirmary GLASGOW

xi

General Hospital

The London Hospital

LEICESTER

LONDON

Royal Liverpool Hospital LIVERPOOL

Manchester Royal Infirmary MANCHESTER

Charing Cross Hospital

Nephrologische Klinik

LONDON

MANNHEIM

Guys Hospital

Royal Victoria Infirmary

LONDON

NEWCASTLE-UPON-TYNE

Hammersmith Hospital

City Hospital

LONDON

NOTTINGHAM

Royal Free Hospital

John Radcliffe Hospital

LONDON

OXFORD

St Bartholomews Hospital*

Derriford Hospital

LONDON

PLYMOUTH

St Mary's Hospital*

St Mary's Hospital

LONDON

PORTSMOUTH

St Paul's Hospital

Royal Hallamshire Hospital

LONDON

SHEFFIELD

St Thomas's Hospital*

North Staffs Royal Infirmary*

LONDON

STOKE-ON-TRENT

Contents

PREFACE

xxi

C H A P T E R 1: S E N S I T I Z A T I O N TRANSPLANTATION

AND SURVIVAL IN RENAL

1. O r i g i n s o f a l l o i m m u n i t y 1.I Natural phenomena I. 1.1 T cells, HLA-vigilantes 1.1.2 Individual variation in responsiveness to alloantigens 1.1.3 Neonatal immunity to maternal alloantigens 1.1.4 Maternal immunity to neonatal alloantigens 1.1.5 Multiparity and paradoxical allograft protection 1.2 Blood transfusion 1.2.1 Immune responses to transfused blood 1.2.2 Unwanted effects of transfusion in renal transplantation 1.2.3 Donor specific blood transfusions and renal allograft protection 1.2.4 Third party blood transfusion and renal allograft protection 1.3 Transplants 2. A s s e s s i n g s e n s i t i z a t i o n 2.1 Sequential studies of alloantibody production 2.2 The prognostic value of the pre-transplant cross-match test

10 10 12

3. F a c t o r s affecting i m m e d i a t e graft f u n c t i o n 3.1 Cold IgM antibodies 3.2 Immediate non-function as a prognostic indicator of graft outcome 3.3 Recipient and donor hydration

14 14 15 15

4. H i s t o c o m p a t i b i l i t y 4.1 ABO 4.2 HLA 4.3 The potential of organ sharing

15 15 16 17

CHAPTER

2: C O U N C I L

OF EUROPE

STUDY PLAN

19

1. B a c k g r o u n d a n d t e r m s o f reference

19

2. P r a g m a t i c d e f i n i t i o n o f h i g h l y sensitized: m o r e t h a n 8 0 % p e a k reaction frequency

19

xiv . Questions posed 3.1 Questions relating to serological pattern 3.2 Questions relating to highly sensitized patients on renal transplant waiting lists 3.2.1 Sources of sensitization 3.2.2 Responder phenotypes 3.2.3 Transplantation rates 3.3 Questions relating to transplanted highly sensitized patients 3.3.1 Transplant survival 3.3.2 Daily clinical course: from transplant to hospital discharge 3.4 Questions relating to special schemes for transplanting highly sensitized patients

4. Sources of information: networked through the European Transplant Organizations . Strategy for data collection: pragmatically designed and activated studies 5.1 5.2

Data collection for questions relating to serological pattern Data collection for questions relating to highly sensitized patients on renal transplant waiting lists 5.2.1 Sources of sensitization and responder phenotype 5.2.2 Transplantation rates and other transactions 5.3 Data collection for questions relating to transplanted highly sensitized patients 5.3.1 Transplant survival 5.3.2 Daily clinical course 5.4 Data collection on special schemes for transplanting highly sensitized patients

6. Design faults

20 20 20 20 20 20 21 21 21 21

22

22 23 23 23 26 26 26 36 36 42

7. Strategy 8. General notes on statistical thinking and methods 8.1 8.2 8.3 8.4 8.5 8.6 8.7

Regression models Regression coefficients and risk score summation Covariate structure Standard error, z-score and confidence interval for regression coefficient Comparison of regression coefficients; also of percentages Statistical reasoning: goodness of fit ~(2 and regression ~2 8.6.1 Goodness of fit Z2 8.6.2 Regression ~(2 For reference

C H A P T E R 3: CAUSES

45 45 46 46 47 48 49 50 51 52

53

1. Introduction

53

2. Plan of study

53

3. Characterization of the data

54

4. Variations in laboratory practices

54

5. Modal patterns of response

56

6. Concordance of B and T patterns with time

58

xv

7. Responsiveness to blood transfusions

58

8. Profile with former failed transplants

59

9. Discussion

59

10. Conclusions

59

C H A P T E R 4: S E N S I T I Z A T I O N 1986: P R E V A L E N C E A N D

SOURCES ACROSS EUROPEAN WAITING LISTS

74

1. Introduction

74

2. Waiting lists: standardizing differently reported sensitization levels

74

3. Council of Europe Study intended sensitization levels: prevalence 1986

78

4. Reported sensitization levels: by source (sex, graft number, blood group, registry) 4.1 4.2 4.3

Study method (Regression) model sequence Results: main effects (see COMPOSITE diagrams) and their registry-specific variation (first order interactions with registry) 4.3.1 Sensitization 4.3.2 Sex 4.3.3 Graft number 4.3.4 Blood group 4.3.5 Registry 4.4 Results: first- and higher-order interactions with sensitization origins of sensitization 4.4.1 12 Sensitization with sex 4.4.2 13 Sensitization with graft number 4.4.3 14 Sensitization with blood group 4.4.4 123 Sensitization with sex and graft number 4.5 Results: first-order and other interactions not involving sensitization 4.5.1 23 Sex with graft number 4.5.2 34 Graft number with blood group

5. Discussion

78 78 80 86 86 86 86 88 88 88 88 93 93 95 97 97 97 98

C H A P T E R 5: R E S P O N D E R P H E N O T Y P E S

1. Introduction

104

2. Study outline

104

3. Motivation for linear-logistic regression

106 106 106 109 109 109

3.1 3.2 3.3 3.4 3.5

Odds on being unsensitized Naive Bayes rule Ln odds on being unsensitized Linear-logistic regression Linear-logistic regression: goodness of fit

xvi 4. E x p l o r a t o r y analysis o f c o v a r i a t e s a n d sensitization

III

5. M o d e l building

114

6. F i n a l regression m o d e l

120

. R o b u s t n e s s o f r e l a t i o n s h i p o f H L A p h e n o t y p e with p a n r e a c t i v i t y 7.1 A or B homozygotes; A and B heterozygotes 7.2 Graft number and sex 7.3 Registry specific variation in HLA-associations with panreactivity 7.4 Transplanted database: highly sensitized and control grafts, 198~85

120 120 120 124 127

. H a r d y - W e i n b e r g e s t i m a t i o n o f gene frequencies in waiting list, transplanted and donor databases 8.1 Waiting list patients 8.1.1 Waiting list patients: HLA-DR 8.1.2 Waiting list patients: HLA-A and B 8.2 Transplanted patients 8.2.1 Transplanted patients: HLA-DR 8.2.2 Transplanted patients: HLA-A and B 8.3 Reference donor gene frequencies: Eurotransplant and UK Transplant 8.3.1 Eurotransplant and UK Transplant: HLA-DR 8.3.2 Eurotransplant and UK Transplant: HLA-A

129 130 130 130 132 132 132 134 134 139

9. Discussion

143

Appendix

145

C H A P T E R 6: T R A N S P L A N T A T I O N

RATES

1. I n t r o d u c t i o n

149

2. S t u d y m e t h o d

149

3. T r a n s p l a n t a t i o n rates by registry a n d sensitization level 3.1 Postulate1: systematic underestimation of peak reaction frequency for patients registered as having 1-50% peak reaction frequency 3.2 Postulate2: Eurotransplant medians inferred for different sensitization levels 3.3 Transplantation rates for first versus regrafts: Eurotransplant

153 156 158 158

4. Difficulties in assessing the rate o f a c c u m u l a t i o n o f highly sensitized patients: r e a c t i o n frequency changes for new a n d registered p a t i e n t s

159

5. N e w registrants a n d re-registrations

t61

6. D e a t h s on the w a i t i n g list a c c o r d i n g to sensitization level

161

7. D e - r e g i s t r a t i o n s o t h e r t h a n t r a n s p l a n t o r d e a t h a c c o r d i n g to sensitization level

162

8. Discussion

162

xvii C H A P T E R 7: T R A N S P L A N T SURVIVAL: F O L L O W - U P OF H I G H L Y SENSITIZED A N D C O N T R O L R E N A L G R A F T S T R A N S P L A N T E D 1982 TO 1985

163

1. Study design

163

2.

163

Realization

3. Risk factor report: first grafts and regrafts 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10 3.11 3.12 3.13 3.14 .

Transplant year Recipient sex and pregnancy history Recipient age Mismatching of HLA antigens Antigen sharing Recipient homozygosity Beneficial/DR matching subdivided by donor DR homozygosity Selected HLA-DR antigens: DR1, DR2 and DR7 Cold ischaemia time Positive crossmatches Cyclosporin A on day 1 and day 1 graft function Blood transfusion Duration of previous graft and wait from previous graft failure to regraft Subdivision of highly sensitized recipients by latest reaction frequency

Statistical method: stratified piece-wise proportional hazards ( = relative risks) 4.1 Stratification 4.2 Piece-wise versus constant proportional hazards (=constant relative risks) 4.3 Covariate structure 4.4 Testing interactions or differences between corresponding regression coefficients

. Transplant survival: results 5.1 Time dependent penalty associated with high sensitization 5.2 Model building: additions to background covariates 5.2.1 Tissue matching: HLA mismatches or antigen sharing (overall and in two distinct epochs) 5.2.2 Model building: high-low sensitization 5.2.3 Model building: pregnancy 5.2.4 Model building: ischaemia time 5.2.5 Model building: transplant year 5.2.6 Model building: INTERACTION of high sensitization and non-beneficial matching 5.2.7 Model building: recipient homozygosity 5.2.8 Model building: recipient HLA-DR phenotype 5.2.9 Recipients as well as donors fully typed: HLA-DR homozygosity (donor or recipient) and recipient HLA-DR phenotype revisited 5.2.10 Eurotransplant excluded: positive crossmatch 5.2.11 Registry: to stratify or not? 5.2.12 Model building: duration of previous graft and waiting time from previous graft failure to regraft 5.3 Preferred coding for HLA-mismatches: model preference amalgamating other covariates

164 164 164 165 165 165 166 166 166 166 167 167 167 168 168

168 170 170 171 173 174 177 177 182 190 191 191 192 193 195 196

199 200 204 204 207

..o X V l n

5.4 Final regression models including day 1 graft function 5.4.1 Day I graft function 5.4.2 Final regression models 5.4.3 Transplant survival: summary

219 219 221 229

6. Mortality: results

229

7. Discussion

230

Appendix I

Realization of study design

234

Appendix II

Risk factor report by first versus regraft

235

Appendix III

Risk factor report by registry

248

Appendix IV

Covariate names, structure and description

250

C H A P T E R 8: D I S T I N C T P O S T - T R A N S P L A N T C O U R S E F O R H I G H L Y SENSITIZED RECIPIENTS? ( K A L M A N FILTER MONITORING)

253

1. Introduction

253

2. Study method and Kalman filter

253

3. Pilot study results 3.1 Designand data quality 3.2 Distinct post-transplant course for SOS patients: "grumbling start" 3.3 Kalman filter: analysis 1 on nine SOS/control pairs 3.4 Retuned Kalman filter: analysis 2

254 254 256 258 262

,

Validation exercise

262

5. Discussion

267

C H A P T E R 9: SPECIAL SCHEMES F O R T R A N S P L A N T I N G HIGHLY SENSITIZED PATIENTS

268

1. Introduction to 11 special schemes

268

2. Special schemes: logistics

273

3. Crossmatches and other features of special schemes

274

4. Maximum acceptable donor HLA-A, B or D R mismatches for highly sensitized patients and priority in recipient selection

275

5. Organ exchange hierarchy

277

6. Discussion

277

C H A P T E R 10: M A K I N G SENSE OF S E N S I T I Z A T I O N

282

1. Introduction

282

2. Definition of high sensitization

282

xix 3. Promoting inter-registry collaboration

283

4. Antecedents of high sensitization

284

5. Exploding the myth of sensitization being confined to HLA-A and B antigens

284

6. Quality of tissue-typing

286

7. Responder phenotypes

286

8. International variation in gene frequency

287

9. Transplantation rates and special schemes

287

10. Transplant survival

287

11. Clinical implications and future studies

289

References

290

Index

299

Preface

In 1986, the Committee of Experts on Blood Transfusion and Immunohaematology of the Council of Europe chose for their Programme of Co-ordinated Research "An investigation of the procurement and sharing of transplantable organs for potential recipients who are highly sensitized to HLA-antigens". This topic was of common concern to all centres practising renal transplantation. The terms of reference of the study were: 1. To estimate the number of patients who are virtually "untransplantable" because of high sensitization in each European country. 2. To study the nature of immunization in terms of the type and specificity of antibodies present in the blood and techniques used for their detection. 3. To investigate possible practical solutions - both current and future, involving cross-matching procedures, the circulation of reference material from patients, and the willingness of the national organizations to share resources. 4. To explore other methods of resolving this problem. Although the study did not offer the prospect of a brilliant new insight into the problem of high sensitization, it was unique in several ways: for the first time we saw all European organizations collaborating in a common project to provide information on their activities, their problems and the methods to resolve them; it introduced, for this subject, relatively novel statistical methods to investigate susceptibility to sensitization and factors affecting transplant outcome; it enabled a large database of transplanted highly sensitized patients and matched controls to be assembled, that would have been unavailable as a research resource at any single centre. In the final analysis, both transient and persistent risk factors influencing graft function were identified. Our understanding of the central role of HLA matching in the survival of all grafts was confirmed and expanded, and we slew a few myths, particularly one relating to the innocence of a positive B cell cross-match. Enthusiasm for the project developed spontaneous!y and was carried forward to the directors of the national transplant services.Without the willing

xxii support of the Study Group and others, notably Dr. Bernard Cohen (EUROTRANSPLANT), Professor Joachim Machado Caetano (LUSO TRANSPLANT), Professor Jacques Hors (FRANCE TRANSPLANT) and Dr. Antonio Arnaiz Villena (HISPANO TRANSPLANT), it would not have been possible to collect clinical data on over 16,000 patients awaiting transplantation throughout Europe and over one thousand transplanted highly sensitized recipients. To preserve confidentiality we cannot individually thank clinicians and scientists who provided data, but we would, nevertheless, like to offer our sincere thanks in centre acknowledgment to all those who contributed. The time constraint on the Study Group was to complete its work between February and December 1986. This was achieved through very generous provision of resources by the MRC Biostatistics Unit, which provided most of the facilities for data management and statistical analysis; the UK Transplant Service which provided spirited liaison; and the Council of Europe's Health Division which provided a venue and funds to convene the study group meetings. Dr. Kerry Gordon and Professor Adrian F. M. Smith (Department of Mathematics, University of Nottingham) co-author Chapter 8 on Kalman filter monitoring of post-transplant course and provided resources thereunto. Special thanks are due to Miss Margaret Fowler, then Statistical Assistant in the MRC Biostatistics Unit in Cambridge, who resourcefully solved computing problems and martialled the data management with excellent good humour. Her assistance was invaluable and was supported by kind permission of Dr. Nicholas Day, Director of the Unit. Illustrations were commissioned from Clifton Studios in Bristol, their rapid throughput and constructive suggestions on over a hundred figures are worthy of our acknowledgement. No research group functions well without superb secretarial support, and we were privileged to have access to the diligent and dedicated offices of both the MRC Biostatistics Unit and the UK Transplant Service. To Mrs. Margaret Cowling especially, and Mrs. Iris Castleton (MRC Biostatistics Unit, Cambridge) and to Mrs. Janet Stinchcomb and Mrs. Ruth Couzens (U K Transplant Service, Bristol), we give our sincere thanks. The Council of Europe sponsored the study; funding was provided by the Council of Europe, MRC Biostatistics Unit and the United Kingdom Transplant Service. The text is the sole responsibility of the authors. B. A. Bradley Director of Studies August 1987

1. Sensitization and Survival in Renal Transplantation

1. Origins of ailoimmunity 1.1. Natural phenomena 1.1.1. T cells, HLA-vigilantes. During foetal development lymphocytes (T cells) learn to recognize self HLA gene products (Jerne 1981). Many react vigorously to foreign HLA antigens carried by other individuals, even without prior contact with these antigens. How this apparent commitment to foreignness develops has no complete explanation, but the most plausible theory, not necessarily correct in detail, is that alloimmunity is a by-product of T cell differentiation. Normally pre-T cells enter thymic cortical tissue, differentiate into cells that bind loosely to self HLA and emerge into the post-thymic pool there to function as HLA-vigilantes, surveying the body for HLA associated unwanted or foreign antigens. This vital role is dramatically illustrated by individuals born with defective expression of HLA; they develop fatal immunodeficiency disease (Touraine et al 1978, Schuurman et al 1979). Thymic tissue acts as a sieve allowing only those cells to pass that exhibit a low avidity for self-HLA; from thence they pass into peripheral lymphoid tissues where they mature and perform two major functions. They regulate development of immune responses and they kill target cells bearing foreign antigens (Benacerraf 1980). Both functions require T cell receptors to interact with HLA on the target cell membrane (Marrack et al 1983). Normally self HLA, interacting with T cell receptors, fails to elicit a response, but the slightest abnormality in the target cell brought about by infective or neoplastic change triggers the T cell into an activated state. Thereafter altered cells are targeted and destroyed by T cell aggressors (Zinkernagel and Doherty 1979). Most allotypic variants of HLA are excellent inducers of T cell responses. This has been seen as the inevitable consequence of selection of low avidity clones in the developing thymus, a process that favours cells binding to epitopic variants of

HLA with high avidity. Thus alloimmunity is a by-product of T cell recognition of altered self. Virgin B lymphocytes are devoid of precocious inclinations to engage HLA alloantigens spontaneously and secrete alloantibody. Germ free animals fail to generate alloantibodies even though their T cells display spontaneous alloimmunity in mixed lymphocyte cultures (Wilson and Fox 1971). Later, during immunological development B cells do produce alloantibodies to major blood group antigens absent from self. However, this is attributable to cross reacting oligosaccharide epitopes on gut bacteria (Springer and Horton 1969). It is a cross reactive response. Similar cross reactions have been described between streptococcal antigens and human transplantation antigens (Rappaport and Chase 1964, Hirata and Terasaki 1970). After grafting with foreign tissues anti-HLA antibody is the predominant component of humoral immune responses. This is a consequence of the amplification by T cells that carry the capacity to react to foreign HLA; a process which directly engages MHC molecules (Kindred et al 1972). Since T cell regulation of B cell differentiation is antigen specific, anti-HLA is the preferred B cell product. 1.1.2. Individual variation in responsiveness to alloantigens. Blind spots in the range of specificities recognised by killer T cells correspond to self-HLA thereby avoiding autodestruction. These develop during ontogeny (Klein 1980). Allelic products of HLA genes contain multiple antigenic sites or epitopes some of which are unique and some are shared with other allelic products. Epitopes that are shared between self and foreign HLA might extend the limits of non-responsiveness by inadvertently creating blind spots to part of another individual's HLA type particularly those belonging to the same crossreactive group. In experimental animals subtler variations in the ability to respond have been identified (Butcher and Howard 1982). In experiments with rat recipients of grafts from the coisogenic RT1A strain donors, alloimmunity to RT1A is controlled by a gene termed Ir-RT1A", thought to map in the Class II region of the rat Major Histocompatibility Complex (MHC). The c allele is associated with low alloantibody production, low levels of killer T cells and prolonged organ graft survival. The u allele is associated with high levels in these modalities. These variations in responsiveness are mediated through T helper cells. Responsiveness to non-MHC antigens is also under genetic control but has different allelic associations; for example, responsiveness to the male linked histocompatibility antigen, H-Y, varies between the RT1A c haplotype, which is associated with slow rejection via, and the a allele which is associated with fast rejection of syngeneic male grafts (G/inther et al 1985). In a similar way

the response to the H-Y antigen in mouse varies depending on the H-2 context in which the antigen is seen. H-2 b haplotypes give less vigorous skin graft rejection than H-2 k haplotypes (Bailey and Hoste 1971, Gasser and Silvers 1971, Stimpfling and Reichert 1971). The best documented example of phenotypic variation in human allo-reactivity is in renal transplantation where low responder status is attributed to HLA-DR1 (Katz et al 1985, Cook et al 1987). HLA-DR1 individuals are less likely to produce alloantibody and to reject renal transplants irrespective of the mismatch. An opposite effect has been described in the Eurotransplant data for HLA-DRw6 recipients (Hendriks et al 1982); but this effect may have been compromised by multiple blood transfusions, rendering confirmation of this finding difficult in subsequent series (Lagaaij et al 1987). 1.1.3. Neonatal immunity to maternal alloantigens. Healthy non-transfused males are occasionally found to produce alloantibody to foreign HLA antigens carried by their mothers (Chardonnens and Jeanett 1980, Yamagachi et al 1983, Werneberg et al 1984, Miyagawa 1984). In healthy offspring there is no evidence that maternal cells have entered or that they persist in foetal circulation but immunologically compromised neonates, born with combined immuno-deficiency disease sometimes carry B cells of maternal origin (Kadowaki et al 1965, Geha and Reinherz 1983). These cells exist in a state of stable chimerism with their neonatal host. Under other circumstances it was reported that maternal cells attacked foetal tissue and caused abortion at the twelfth week of gestation (Taylor and Polani 1965). 1.1.4. Maternal immunity to neonatal alloantigens. Pregnancy induced leukoagglutinins were first recognised in 1958 (Payne and Rolfs 1958) and have since been a major source of HLA typing reagents (Van Rood et al 1959). Rodent experiments suggest that the induction of antibodies during pregnancy is under genetic control (Smith et al 1982a,b). In mice a quantitative difference in the relative distribution of immunoglobulin isotypes of alloantibodies occurs during pregnancy compared with graft rejection (Bell and Billington 1980). The differences depend on mouse strain combinations but in those studied noncomplement fixing anti-MHC antibodies are predominant during pregnancy whereas complement fixing antibodies are predominant after graft rejection. The relationship between past pregnancies and renal allograft survival is such that pregnancy appears to be associated with a significantly lower graft survival in recipients of first renal transplants (Sanfillipo et al 1982). This may be related to heightened sensitivity to blood transfusions in parous women. High sensitization is more common after transfusions in parous women than in nulliparous women (Opelz et al 1981). However the relationship between level of sensitization, transfusion and parity is complex (Sanfillipo et al 1982).

Parity is associated with decreased graft survival in untransfused recipients, but in transfused recipients it is associated with a significant benefit even though patients are moderately sensitized (0-60% panel reaction frequency). 1.1.5. Multiparity and paradoxical allograft protection. Thirty years ago a report of an investigation into sources of skin donors for burned patients claimed that skin grafts taken from offspring and transplanted onto mothers survived longer than from offspring to fathers (Peer 1957). These studies were sparsely recorded, difficult to repeat and have been largely forgotten; but there followed some very elegant rodent experiments in multiparous mice (Prehn 1960, Breyere and Barrett 1960a,b, Breyere and Barhoe 1963). Tumours and skin allografts survived significantly longer in multiparous than in nulliparous recipients, when either major (H-2) or minor (H-Y) histocompatibility barriers were breached. The effect in the mother was specific for paternal alloantigens carried by her offspring. An infusion of paternal bone marrow cells several days postpartum strengthened the suppression and rendered it more specific. A quantitative relationship existed between the number of pregnancies and the extent of protection. Protection persisted for the lifetime of the mother (Breyere 1967). Heart allografts in in-bred rats between paternal strain donors and their multiparous mothers survived longer than in corresponding transplants from paternal strain donors into nulliparous controls (Heron 1971, 1972a,b). Similarly in rabbits, neonatal hearts taken from babies and transplanted back into the offspring's mother enjoyed longer survival than similar transplants into the father. In parous women renal allograft survival was compared between offspringto-mother and offspring-to-father transplants; 222 offspring-to-father grafts had a survival of 70% (se = 3.1%) but 117 offspring-to-mother grafts had a survival of 80% (se = 3.6%). The paradox between these findings and those showing an increasing risk with multiparity may be explained by differences in the histocompatibility relationship between offspring and mothers. Child to mother transplants may reactivate specific suppressor mechanisms.

1.2. Blood transfusion 1.2.1. Immune responses to transfused blood. Until 1956 leukoagglutinins and thromboagglutinins were widely studied as potential aetiological agents for leukoneutropenia and thrombocytopoenia. Thus in multiply transfused patients they were of interest for their autoreactive rather than their alloreactive properties (Moeschlin and Wagner 1952, Dausset and Neuna 1952, Dausset 1954). Leukoagglutinins were identified as causal agents in non-haemolytic transfusion reactions in 1956 (Van Loghem et al 1956, Brittingham and Chaplin 1957). By this time it became apparent that transfusions induced 'complete'

antibodies, which agglutinated leukocytes directly and 'incomplete' antibodies which required anti-globulin reagents for leukoagglutination (Van Rood et al 1959). It is difficult to anticipate immune responses after transfusions. Many factors are involved including: the patient's disease (uraemics are more immuno-depressed than healthy individuals); prior experience of alloantigen through pregnancy or failed transplants; the volume of the blood given; the interval between transfusions; the frequency of test samples; the constituents of the transfusate; and the HLA mismatches between transfusion donor and recipient. One study documented an immunization rate of 90% following four, small transfusions of 160 mls of blood spaced at six monthly intervals (Soulillou et al 1980). In 63% of patients anti-B lymphocyte antibodies emerged and tended to appear earlier after transfusion. In 49% of patients anti-T lymphocyte antibodies appeared but developed later after transfusion. Washed blood was administered, hence the induction of alloantibodies was surprisingly high considering the poor leukocyte content. In other studies, alloantibody production was dependent on the number of viable leukocytes in the transfusate (Martin et al 1985). A correlation existed between transfusions and panreactivity as reflected in alloantibody production against the population. Panreactivity of greater than 60% occurred more frequently with more transfusions, and after six to ten transfusions the overall rate was 9% but in parous females it had risen to 20% (Sirchia et al 1981). In another study only 2% of untransplanted male patients who were given ten blood transfusions developed lymphocytotoxic antibodies to more than 90% of the population, but 14% of females and 30% of multiparous females with three or more pregnancies, reacted with 90% of the population. The relationship between numbers of transfusions and proportion of the population against which antibody is produced was non-linear; after 5 transfusions the fraction developing alloantibodies levelled off and only a small relative increment occurred between 5 and 15 transfusions (Opelz et al 1981). Thus transfusions appeared to amplify immunity, induced by prior pregnancies. In parous women who had rejected a graft the majority developed persistent panreactive antibody following transfusion. Persistent responders to transfusions had all exhibited alloantibody binding to lymphocytes detectable by flow cytometry. Transient responders to blood transfusions had no such antibody (Scornik et al 1984). Other types of antibodies that develop after transfusion are directed to targets other than HLA. These include "anti-idiotype" antibodies, so-called because of their capacity to inhibit anti-HLA antibody reactions of serum samples taken from the same individual at earlier times in the immunization history. However, formal demonstration of binding of these antibodies to the V r~ regions of HLA antibodies is a requirement for true idiotypy, and this has

never been demonstrated. Nevertheless these reactions are of interest; they appear six to eight months after the disappearance of transfusion induced alloantibodies and in a few instances their presence is associated with good graft function (Reed et al 1983a, b, 1985, Sucia-Foca et al 1985). Enhanced cellular immunity to alloantigens was demonstrated after multiple blood transfusions. Patients with aplastic anaemia who had received many transfusions of platelets from both HLA identical siblings and random donors at a rate of 4 units, twice weekly for over a year developed high levels of killer cells (Wunderlich et al 1972). These findings are consistent with later studies in which T killer cells produced under similar circumstances reacted against the combined target of self HLA and the male linked histocompatibility antigen H-Y (Goulmy et al 1981). The induction of T killer cells after more modest levels of transfusion may occur and is consistent with the observed increase in the number of activiated T cells of the OKT8 series after transfusion (Lenhard et al 1982). Paradoxically the same authors found that cellular immunity in cellular proliferative assays was depressed. In vivo depressed cellular immunity was evidenced by significant reduction, post-transfusion, in the DNCB skin reactivity (Watson et al 1979). Decreased cellular immunity may result from autoantibody directed against T cell receptors (Ludwin et al 1986); however chemical confirmation of the target molecule involved in these reactions is unavailable. An alternative explanation, suggested in several studies, is that T suppressor cells, known to increase after transfusion, are responsible for suppressed immunity (Smith et al 1982). In summary, blood transfusion may lead either to panreactivity, or suppressed activity in complement dependent lymphocytotoxicity assays. It is followed by enhanced specific T killer cell activity and non-specific suppression of cellular immunity. Six months after the transfusion some form of auto anti idiotypic or alloantibody develops. 1.2.2. Unwanted effects of transfusion in renal transplantation. In previous sections we have raised the spectre of transfused blood providing a trigger for sensitization in two ways: firstly as an immunogen in its own right and secondly as an activator of B cells already primed to produce allo-antibodies. In 1966 Kissmeyer-Nielsen described two cases of hyperacute rejection of cadaveric kidney grafts in multiparous women attributable to high levels of alloantibody induced by multiple transfusions (Kissmeyer-Nielsen 1966). Thereafter the practice of cross-matching was introduced to avoid this catastrophe. The culpability of blood transfusions was seriously questioned by Opelz and colleagues in 1973 when they demonstrated that patients with no detectable alloantibody had better graft survival if they had received more than ten blood

transfusions (Opelz et al 1973). The non-transfused recipients were expected to have the best survival, however they turned out to have the worst. The question of whether or not patients who have produced alloantibody benefit from transfusions in terms of improved graft survival has been addressed in some studies. Opelz et al in 1973 showed no detectable benefit from tranfusirns in patients who were producing lymphocytotoxic antibodies. Dausset in 1974 even showed a correlation between the numbers of transfusions and poorer graft survival in patients producing lymphocytotoxic antibody (Opelz et al 1973, Dausset et al 1974). However, by 1977 cross-match testing was more widely practised and the likelihood of hyperacute rejection reduced. This allowed the beneficial effects of transfusion in sensitized recipients transplanted with cross match negative kidneys to be evaluated. Thus Sanfillipo and colleagues studied a series transplanted between 1977-1981 and showed that the transfusion benefit was greatest in the unsensitized but was also present in the moderately sensitized. In patients with higher levels of sensitization (over 60% panel reactivity) no detectable benefit was discernible (Sanfillipo et al 1982). Thus the beneficial effect of transfusions occurred irrespective of graft number and parity, and was apparently separate from its alloantibody triggering properties. The notoriety attributed to transfused blood for its sensitizing properties is ill founded in individuals who have not been previously immunized. 1.2.3. Donor specific blood transfusions and renal allograft protection. In 1964 blood from a kidney donor given subcutaneously to dogs prior to transplantation was shown to be associated with prolonged renal allograft survival in related donor-recipient pairs mismatched for a single DLA haplotype (Halasz et al 1964). Research in rodents has subsequently indicated that similar phenomena can be achieved by infusions of nucleated B cells, platelets or erythrocytes and that both heat treated and ultra violet irradiated blood are effective (Batchelor et al 1977, Lauchart et al 1980, Wood et al 1985, Wakerley et al 1985, Martinelli et al 1987, Malik et al 1985). In humans alloantibody against prospective kidney donors is generated in 30% of recipients after multiple transfusions from a single donor but such transfusions also induced significant suppression of graft rejection (Salvatierra et al 1980, 1981). The mechanism of the suppression appears resistant to treatment with Azathioprine and possibly Cyclosporin-A when given concurrently with transfusions (Glass et al 1983, Anderson et al 1984, Salvatierra 1985). But the generation of lymphocytotoxic antibody appears to be sensitive to these drugs. Thus specific suppression may be retained whilst sensitization is ablated. Further speculation on mechanisms involved in this form of graft protection has invoked a sequence of events involving T suppressor cells and their capacity to down regulate T helper cell function (Hutchinson 1984).

1.2.4. Third party blood transfusion and renal allograft protection. In 1973 patients who had received no transfusions and who had developed no lymphocytotoxic antibodies were widely assumed to enjoy a superior renal allograft survival compared to those who had been transfused; but the opposite was true (Opelz et al 1973). Patients given ten or more transfusions, who had developed no detectable lymphocytotoxins when compared to non-tranfused patients, enjoyed a significantly improved survival. These results were repeatedly confirmed in human and animal studies (Tiwari 1985). An incremental benefit was demonstrated between numbers of transfusions given and graft survival; the more transfusions, the better the survival; but one study clearly showed that a single transfusion was sufficient to induce graft protection (Persijn et al 1977). A single transfusion had the theoretical advantage of reducing the risk of sensitization. The component parts of transfused blood survive in the recipient's circulation or tissues for varying times. The most potent fraction of blood responsible for graft protection appears to be lymphocytes. Animal experiments suggest that B lymphocytes may be more effective than non-B lymphocytes in terms of graft protection (Lauchart et al 1980). However other components are also effective; purified platelets given in sufficient quantity induce graft protection and have the added advantage of being poor inducers of primary immunization to HLA antigens (Borleffs et al 1983). However washed human red cells are ineffective (Persijn et al 1981). In recent studies the beneficial effect of blood transfusions has apparently weakened (Opelz 1987, Groth 1987). This observation, made in several series, coincided with improvements of graft survival attributable to other therapeutic procedures. It is difficult to concede that a beneficial effect of this magnitude could suddenly disappear and the suspicion is that results may have been inadvertently biased by a centre effect. The effect remains to be confirmed in a prospective controlled clinical trial. Transfusion of the donor prior to transplantation also protects grafts from rejection (Jeekel et al 1983). 1.3. Transplants In 1944 Medawar's theory of actively acquired immune responsiveness explained skin allograft failure in a novel way (Medawar 1944). Central to his theory was the observation that second grafts from one donor, placed after failure of the first, were broken down in accelerated time; the accceleration being unrelated to the graft interval. This, he termed the "second set phenomenon". Ten years later a parallel phenomenon was described by Simonsen in second kidney grafts in dogs (Simonsen 1953a,b). Dempster then demonstrated that

actively acquired immunity to graft antigens was a systemic process (Dempster 1953). Having first sensitized dogs with skin grafts from prospective kidney donors, he observed that they immediately rejected kidney transplants. This established that immunity to alloantigens expressed on one tissue heightened reactivity to subsequently transplanted tissue, even although the tissues originated from different organs. Chief culprit for this heightened alloimmunity in dogs was thought to be alloantibody and supporting evidence came from serum transfer experiments (Altman 1963). Skin graft sensitized dogs donated immune serum to non-sensitized recipients of kidney grafts from the same donor animal. Within twenty minutes kidneys were rejected, implicating alloantibody. A distinction is often made between hyperacute, acute and chronic kidney graft rejection. In each case elements of antibody mediated and T killer cell mediated tissue destruction have been described. Cellular immunity plays an important part in second set rejection as illustrated many years ago in male to female skin grafts within in-bred mouse strains. Recipients who had already rejected one skin graft from a male donor were sensitized exclusively to the mismatched H-Y antigen (Eichwald et al 1957); no antibody has been convincingly demonstrated in mice to this antigen and rejection is attributed to killer T cells. Cellular immunity as a cause of hyperacute rejection was implicated in a kidney graft model in mini-pigs (Kirkman et al 1979). Pairs of unrelated animals were cross-sensitized with multiple skin grafts and grafted with kidneys from the same donors. Rejection occurred minutes later but no antibody was found either before or after transplantation. Enhanced anti donor cellular responses were demonstrable. In man rapid rejection of kidney grafts was first documented in 1968 with several descriptions of hyperacute rejection following second, third and fourth transplants (Williams et al 1968). Histological hallmarks were widespread infiltration with polymorphonuclear leukocytes and capillary thrombosis accompanied alloantibody production to HLA (Morris et al 1968). In chronic graft failure there is a significant association between the appearance of alloantibody to donor Class II mismatches (Soullilou et al 1978); but there is also a significant correlation between the emergence of donor specific T killer cells and graft failure (Goulmy et al 1981). When rejectingtransplants cease to function and immunosuppressive therapy is discontinued, panreactive anti-HLA antibody tends to be produced in some cases (Hardy et al 1979). This occurs especially when grafts are left in situ; if removed, antibody tends to be less panreactive (Norman and Barry 1985). Furthermore if immunosuppression (with Azathioprine) is continued after graft nephrectomy anti-HLA activity is suppressed to negligible levels for the duration of the immunosuppression.

10 2. Assessing sensitization

2.1. Sequential studies of alloantibody production Studies of the development and persistence of alloantibody following immunization are usually insufficient to provide a complete sequence of events. Various aspects have been documented with greater or lesser detail during pregnancy, transplantation and after one or more blood transfusions. Such studies are largely confined to lymphocytotoxic antibodies that fix complement; occasional distinction is made between IgG and IgM. But little attention has been paid to non-complement fixing opsonic antibodies that may be responsible for antibody mediated unresponsiveness or graft enhancement (Lems et al 1981a, b, Hutchinson and Zola 1977). Furthermore, IgG isotypes capable of arming host killer cells (K cells) are unjustifiably ignored when assessing sensitization. During pregnancy lymphocytotoxic antibody (hereafter alloantibody) production is influenced by parity and phase of gestation. Vives et al showed that alloantibody appeared progressively earlier in gestation with increasing parity; thus it was detectable after the fourth, second and first months of gestation during first, second, and third or subsequent pregnancies (Vives et al 1976). 19% of prima-gravidae and 30% of multi-gravidae (5 or more) develop alloantibodies during pregnancy but a significant decline occurs in the proportion of antibody positive women between the sixth and eighth month. The specificity of sera also narrowed.(Tongio and Mayer 1977). The proportion of women producing lymphocytotoxic antibodies was related to parity; in this study after four or more pregnancies 47% of women developed antibodies. Several other studies confirmed an association between parity and proportion of women producing alloantibodies. Doughty and Gelsthorpe revealed an association between antibody titre and parity at all stages of gestation. Furthermore a post-natal decline in the proportion of positive women from 17% at delivery to 12% six months later Occurred irrespective of parity (Tongio et al 1973, Doughty and Gelsthorpe 1976). In theory the vast majority of mothers should produce alloantibody to foreign HLA, but many are reputed to carry small numbers of foetal lymphocytes in their circulation, some up to 12 months post-natally (Herzenberg et al 1979). Schr/Sder et al observed that 37% primiparous mothers carrying male offspring had detectable levels of foetal lymphocytes in their peripheral blood and these were apparently of B cell type (Schrrder and de la Chapelle 1972, Schrrder et al 1974, 1975). Their disappearance at various times postnatally was inversely correlated with the appearance of alloantibody. Thus mothers who are negative at delivery become positive, microchimerism has waned.

11 Further discussion of pregnancy associated humoral immunity awaits more detailed, sequential studies aimed at clarifying immunoglobulin class, sub-class, specificity and biologic function (Head and Billingham 1983). The alloantibody response to kidney grafts is difficult to evaluate. Most patients at some stage prior to transplantation have been primed to alloantigens and as a consequence the Post-graft response is modified in several ways; by the absorptive capacity of the kidney or its antigeneic products; by non-specific polyclonal B cell reactivation; and by therapeutic immuno-suppression. Graft verus host antibody reactions are also documented; mismatches perceived in the host by donor cells can elicit antibody production by donor lymphocytes transferred in the graft. These sequest into host tissues and generate antibodies to blood group mismatches (eg Rhesus D) in the host and may persist for many months after graft nephrectomy (Ahmed et al 1987, Ramsey et al 1986). Blood transfusion of recipients before or during the transplant operation might have been expected to sensitize patients to alloantigen after grafting. However, Ting and Morris observed that although most non-transfused patients developed donor-specific alloantibodies after-transplantation this occured in significantly fewer of the patients who had been transfused (Ting and Morris 1979). None of the patients studied had detectable pre-transplant alloantibodies and all were receiving their first transplant. More than most other studies this addressed the question of the relevance of graft induced antibodies during the post-engraftment period. In another study Roy et al showed that, in the majority of patients, alloantibody produced post-engraftment was of the cold reacting (4°C), IgM type and was irrelevant as a predictor of graft failure. IgG alloantibodies were associated with poorer graft outcome (Roy et al 1981). This observation took no account of the anti-donor specificity of the IgG alloantibody or graft number (the study included both primary and regrafts). Further dissection of post-engraftment antibody responses with special attention to specificity, class, and biological function is required. Only then a final judgement can be made as to its clinical relevance. After graft rejection the evolution of alloantibodies depends on events such as blood transfusions, graft nephrectomy and the discontinuation of immunosuppression. The majority of alloantibody occurring after graft failure is directed towards HLA, as revealed by segregation studies using a panel of cells derived from pairs of HLA identical siblings (Soulillou et al 1981). The proportion of recipients who develop humoral immunity to donor antigens after graft failure is difficult to estimate. Scornik used a sensitive flow cytometry technique to detect IgG alloantibodies that bound at 37°C; he found that virtually all rejectors produced detectable anti-donor antibody to a much higher titre than would be detected by lymphocytotoxicity. This persisted after

12 rejection for at least five months (Scornik et al 1984). In many of these cases no alloantibody was detectable by conventional cytotoxicity tests but, if during the post rejection period blood transfusions were administered, kidney donor specific lymphocytotoxic antibody production was triggered. It is generally assumed that the sensitized state following graft rejection is little different from that following pregnancy or blood transfusion, however evidence from absorption experiments shows that the lymphocytotoxicity following graft rejection is accompanied by antibodies directed towards kidney specific polymorphisms (Mohanakumor et al 1981). In summary alloantibody development after engraftment and after graft failure is poorly documented, not only with regard to its specificity within the HLA system, but also with regard to its immunoglobulin class, its sub-class and biological function. 2.2. The prognostic value of the pre-transplant cross-match test In 1966 Kissmeyer-Nielsen observed an association between the presence of leukoagglutinating antibodies directed towards donor cells and subsequent hyperacute rejection in two multiparous women who had been multiply transfused. The role of alloantibody in hyperacute graft rejection was then poorly understood (Kissmeyer-Nielsen et al 1966). This was followed in 1969 by the first convincing evidence of the prognostic value of the cross-match test as we now use it (Patel and Terasaki 1969). A micro-lymphocytotoxicity test was used to show that 24 out of 30 transplants performed across a positive cross-match failed to function. The remaining transplants were later reviewed (Belleil et al 1972); of these two had excellent function at 3 years post transplant but the rest had failed between 3 and 24 months. Another isolated case of a positive crossmatch transplant that functioned after 12 days of oliguria was reported by Heale and Morris (1969). Another series published in 1974 confirmed the association between cross-match positivity and graft failure; of 21 patients with anti-donor antibody prior to transplantation, only seven were still functioning 18 months later (Myburgh et al 1974). Thus, in its unsophisticated form, the cross-match test is an important but not an absolute prognosticator of hyperacute rejection. In recent years evidence has emerged to suggest that clinically relevant antidonor alloantibody is of IgG class and directed towards HLA mismatches on the donor cells (Chapman et al 1987). Antibody directed towards auto-antigens and IgM alloantibody appear innocuous in terms of hyperacute rejection (Fabre and Morris 1972, Reekers et al 1977, Park et al 1977). However, cold agglutinating antibodies are an exception (see below). Similarly alloantibody directed towards non-HLA targets, especially those confined to B cells, is irrelevant (Reed et al 1983).

13 In theory, a positive cross-match test against B lymphocytes may be attributed to IgG anti-HLA-DR antibody. However if anti~HLA-A and B antibodies have not been removed from sera by platelet absorption prior to testing, positive tests attributable to anti HLA-A and B antibodies will occur despite negative results against T cells (Jeannet et al 1981). 50% of all positive B cell tests performed with unabsorbed sera are attributable to anti-HLA-A and B antibodies. The temperature dependency of serum reactivity is prognostically relevant in two ways; firstly, cold reactive anti-donor antibodies, including IgM allo and auto antibodies, are associated with graft non-function during the early post transplant period when cold kidneys are transplanted (see below). Secondly, cold reactive anti-donor antibodies, particularly IgM auto anti B cell antibodies, are associated with improved graft survival (Klouda et al 1976, Iwaki et al 1978, Jeannet et al 1980, Ayoub et al 1980, Ettenger et al 1983). Until 1982 it was widely assumed that once a patient was sensitized he remained sensitized for all time. Sound immunological reasoning would dictate that an anamnestic response followed by hyperacute rejection would occur if a transplant was performed across a positive cross-match test using any of the sera obtained from the patient throughout his dialysis history. Cardella, having confirmed an interesting phenomenon that multiple transfusions given to sensitized patients were in many cases followed by declining sensitization (Cardella et al 1982a), developed an immunosuppressive protocol that allowed the recipient to overcome past sensitization (Cardella et al 1982b). Fifteen patients including nine regrafts were transplanted. In all cases the non-current (historic sera) gave positive cross-match results with the donor but the current sera gave a negative cross-match test. The reaction frequency of the non-current sera ranged from 20-100% with peaks of over 50% in all cases. Current sera ranged from 0-90% reaction frequency. In all but one patient the reaction frequency was falling slowly between peak and the current sera and in nine cases the patient received transfusions during the interval between the two serum samples (range 2-36 months). Prior to transplantation patients were treated with rabbit anti-thymocyte serum for 24 hours and this was continued for 21 days post transplant. In addition patients received Prednisolone and Azathioprine. The results in terms of graft survival were not significantly different from the 79 conventionally treated controls. Though not conclusive in itself several other studies confirmed these initial observations (Norman et al 1985) but the impression gained was that positive cross-matches in any serum in patients receiving a re-graft should be respected (Kerman et al 1985). The lack of sensitivity of the conventional cross-match test has been shown in several ways. Fuller developed a sensitive cross-match test that featured a second stage of development in which an antiglobulin antiserum cocktail was added to the test prior to the addition of complement (Fuller et al 1978). He

14 identified 17 patients whose conventional cross-match result was negative but whose enhanced test result was positive. 16 of these cases rejected within two months post-transplant. Kerman showed a significant asssociation between positivity in a crossmatch test based on 51Chromium release and graft failure at one year post transplant (Kerman et al 1985). This was significantly better than the conventional cross-match test. Garavoy using fluorescence activated cell sorter (FACS), not only detected higher titres of anti-donor lymphocyte antibody, but also found an association between the "FACS positive-conventional test negative" transplants and graft failure during the first 3 months post transplant (Garavoy et al 1983). All these studies suggest that whereas conventional cross-matching may be sufficient to predict hyperacute rejection, a more sensitive cross-match assay may help to predict graft failure during the first year.

3. Factors affecting immediate graft function 3.1. Cold IgM antibodies In 1971 Belzer et al described a patient carrying cold reactive auto anti-N antibody who received a cadaveric transplant (Belzer et al 1971). The kidney failed to function and on histological examination the vessels were full of erythrocyte aggregates and infarcts. The second kidney from the same donor, now forty hours old, was transplanted into the same patient but was irrigated with warm perfusion fluid prior to opening up the blood supply. This kidney functioned immediately and continued well beyond five months. They suggested that patients with cold anti-erythrocyte antibodies should not be transplanted with cold kidneys. These observations were later extended in a larger series (Schweizer et al 1982). In 1976 and again in 1980 Kjellstrand and Brophy and colleagues reported an incidence of initial non-function in transplants from living related donors of 10-11% and in cadaveric transplants of 32% (Kjellstrand et al 1976, Brophy et al 1980). An independent study documented a similar rate of early non-function in cadaveric transplants (Lobo 1980a,b). Initial non-function was linked to the presence of cold reactive IgM anti-donor antibodies. Biopsies taken one hour after transplantation revealed in 22 out of 23 non-functioning kidneys segmental glomerular capillary aggregates and fibrin deposits. This was significantly associated with cold IgM lymphocytotoxic antibodies in the recipient prior to transplantation. These lesions were distinct from hyperacute rejection and acute tubular necrosis traditionally associated with ischaemic damage beyond 72 hours. No significant difference in the

15 cold-ischaemia time existed between kidneys with glomerular lesions (27 + 6 hours) and kidneys without glomerular lesions (26 + 7 hours). Warming the kidney prior to establishing the blood supply reduced the incidence of nonfunction (Lobo et al 1984). 3.2. ffnmediate non-function as a prognostic indicator of graft outcome Multifactorial analyses of risk factors affecting the outcome of kidney transplants have shown that delayed graft function is one of the strongest factors affecting the outcome of transplants up to six months (Sanfillipo et al 1985). The relative risk is 1.46 (Z = 5.37 P < 10-5). This risk factor is separate from the centre effect, panel reactive antibody, anti-rejection therapy, source of donor (local or shared), transfusion history, HLA-A and B matching and ischaemia time. Of interest, since delayed graft function is often assumed to be attributable to acute tubular necrosis induced by prolonged ischaemia, was its effect over and above the method of organ preservation and the preservation (ischaemia) time. Belitski and colleagues showed that the duration of non-function correlated both with transplant survival and with post-operative serum creatinine levels in the recipient (Belitski et al 1987). 3.3. Recipient and donor hydration Of equal importance to all immunological factors affecting immediate function is the degree of hydration of both recipient at the time of transplantation and the donor prior to nephrectomy. Under-hydration leads to early anuria (Woods et al 1972, Anderson and Etheredge 1977, Luciani et al 1979, Carliev et al 1982).

4. Histocompatibility Three major aims of tissue matching are to avoid targets for hyperacute rejection, to reduce the need for immunosuppressive therapy and to achieve prolonged survival of the graft, if possible for the patient's lifetime. 4.1. ABO In 1956 Merrill and colleagues reported a successful kidney transplant in uniovular twins (Merrill et al 1956). At that time virtually nothing was known of the HLA system. The ABO system became a prime suspect in 1964 when Starzl published a small series implicating AB blood group mismatches in early graft loss (Starzl et al 1964). This was confirmed in a more extensive series in 1967 but it was evident that one-third of the AB mismatched transplants were

16 still functioning several months after transplantation (Gleeson and Murray 1967). Thus AB mismatching is not an insurmountable barrier to kidney graft survival, a fact borne out in recent studies (Slapak 1981, Brynger 1984, Alexandre et al 1985). 4.2. H L A In 1965 the association between HLA mismatching and survival was seen simply as a matter of matching a few alleles at a single locus (Simonsen 1965). The role of HLA matching was confirmed in several studies of transplants performed between siblings within families (Van Rood et al 1967, i968, Dausset et al 1968, 1969, Singal et al 1969). Relatively crude tissue typing reagents directed towards a few high frequency antigens (eg HLA-Bw4) were available at the time and the complexity of the HLA system that was subsequently to emerge had in no way been appreciated. Based on an anticipated demand for kidneys from cadaveric donors, national and international organ sharing programmes were established with the aim of matching donors and recipients and avoiding wastage of transplantable organs. From then until the early 1980's there followed a period of confusion during which the role of HLA matching was strengthened by increasing evidence from matched living related transplants; but was weakened by paradoxical demonstrations of little or no effect in unrelated transplants. This was by no means a universal finding. Nevertheless there was sufficient doubt to question the validity of matching programmes. The main reason for this confusion was the unforeseen multiplicity of loci at the HLA system which have since been more fully unravelled by DNA hybridization studies; also, the complexity of the serological reagents used for tissue typing and the accuracy of the typing results obtained was and in some respects still is suboptimal. Now with the introduction of DNA hybridization techniques for tissue typing the genetic map of the HLA region has been almost completely drawn, and with the introduction of monoclonal antibodies to tissue typing the multitude of epitopes that characterize a single HLA specificity is more fully appreciated. The variation in quality of typing results is now carefully monitored at both national and international levels. Currently the products of the HLA-A, B and DR loci are matched but the quality of tissue typing is poorest with HLA-DR. The true potential of HLA matching, equivalent to that seen in HLA identical sibling transplants, can best be appreciated when the dependence between loci is taken into consideration in the analysis; mismatching at one locus crucially depends on mismatching at adjacent loci. In siblings this dependence is almost absolute. Thus in a statistical model developed to evaluate the full effects of HLA matching Gilks et al (1987) examined the independent effect of 27 varieties of mismatch given by 0, 1 and 2 mismatches at HLA-A, B and DR loci

17 Table 1.1. % 1-year graft survival (first transplants)

HLA-(A,B,DR) mismatches

United Kingdom and Irelanda

North Americab

Europec

000 100 010

93% (73) 86% (108) 81% (97)

83% (98) 68% (97) 62% (117)

92% (39) 90% (87)

67% 73% 70% 71% 65%

64% 62% 62% 57% 55%

67% 68% 65% 61%

001 2 in 3 in 4 in 5 in

total total total total

(96) (603) (720) (399) (154)

(107) (1229) (1406) (820) (194)

(74) (299) (238) (90)

a Estimated multifactorially controlling for transplant centre and year of transplant; based on UKTS data. b Based on results of Mickey (1985). c Based on results of Persijn (1985).

(3 x 3 x 3 = 27). The greatest matching benefit occurred when there were no mismatches at the HLA-A,B or DR loci (abbreviated to 000 for mismatches at HLA-A, B and DR), and next best when there was at most one mismatch for HLA-A or B (100 or 010). The matching increment beyond these levels was small but significant. The relationship can be better appreciated by comparing three large independent databases (Table 1.1). Although the long-term mismatching risk cannot be fully appreciated before the HLA-DR typing era (circa 1980), studies in family transplants performed at least 10 years ago, where one-haplotype mismatch donors were compared with HLA identical sibling donors show that the hazard of graft loss associated with mismatching persists for at least 10 years. Patients receiving one haplotype mismatch transplant from family members have a significantly shorter "half life" than HLA identical siblings (Takiff et al 1986). This implies that the risk of HLA mismatching is persistent throughout all post operative epochs up to ten years and as such is one of the most potent factors affecting long term outcome of kidney transplants. 4.3. The potential of organ sharing It has been suggested that in the "Cyclosporin era" kidneys can be safely transplanted into patients irrespective of mismatch. This would deny recipients the full benefits of matching and substitute the hazards of immunosuppression. However, matching is limited by the extensive polymorphism of the HLA-system; and its benefit can only be realized fully through multicentre organ sharing programmes. Simulation studies have been performed to investigate how many patients could be beneficially matched. The results are summarized in Table 1.2.

18 Table 1.2, HLA-A,B and DR mismatch category

Simulations* (recipient pool size) 100 500 1000 3000 5000

000

I00

010

Other

Donor kidneys

3% 7% 10% 17% 28%

4% 11% 14% 22% 24%

5% 12% 17% 22% 21%

88% 70% 59% 39% 26%

10000 10000 10000 10000 10000

* Simulations assumed that: all donors and recipients are typed for HLA,A,B and DR; all kidneys offered to the pool initially; ABO blood group identity is required (to avoid accumulation of group O patients in the pool); and the pool excludes highly sensitized patients. This shows the relationship between p r o p o r t i o n beneficially matched and pool size. With a pool size o f 100 only 12% beneficially matched (000 + 100 + 010) transplants would be achieved; such a pool would equate to an average size transplant centre. With a pool size o f 5,000, which is roughly equivalent to the entire Eurotransplant waiting list, up to 73% o f transplants could be beneficially m a t c h e d . Hence organ sharing is justifiable in terms o f the matching benefit gained. There are other cogent reasons, that together constitute a rational basis for organ sharing (Bradley 1987).

2. Council of Europe Study Plan

1. Background and terms of reference

In brief, the Council of Europe Study was to collect basic data to compare the incidence and prevalence of high sensitization across European registries; to assess origins and associations; to quantify the transplant penalties associated with high sensitization compared to other risk factors; and to detail special schemes for transplanting highly sensitized patients.

2. Pragmatic definition of highly sensitized: more than 80% peak reaction frequency

In Chapter 1 we explored the diverse immunological origins, time course and assessment of high sensitization. Faced with such heterogeneity, what is meant by "highly sensitized"; what do the transplant organizations mean by "highly sensitized"; and how do we in the Council of Europe Study define "highly sensitized"? European registries have faced the common consequence of high sensitization: that patients carrying broadly reactive antibodies which kill cells of the majority of potential donors remain untransplanted. The registries needed a measure of sensitization status by which to recognise such patients, and by common consent adopted peak reaction frequency. Peak reaction frequency is specious both immunologically (see Chapter 1) and statistically - because duration and intensity of monitoring differ between patients; and because cells tested and test environment, as well as panel size and composition, vary between laboratories. Yet, it affords the only working registry definition of highly sensitized. Accordingly, the Council of Europe Study definition of highly sensitized is likewise pragmatic: an endstage renal failure patient awaiting transplantation whose serum is registered as having reacted with more than 80% of the

20 population or, if transplanted, whose serum prior to that transplant reacted with more than 80% of the population, as reported by local test procedure.

3. Questions posed The Council of Europe Study Group posed questions of, and collected data from, four sources: tissue-typing laboratories; registry waiting lists; transplant follow-up; and about the special schemes for finding crossmatch negative kidneys for highly sensitized recipients. The questions were as follows.

3.1. Questions relating to serological pattern Chapter 3 is a retrospective survey of the practical monitoring of alloimmunity. How frequently are tests performed; are T and B cell antibodies measured? How many response patterns are discerned when % reaction frequency in consecutive serum samples is charted for individual patients? How do these patterns relate to immunising events such as blood transfusion, pregnancy and failed transplants? What proportion of patients exhibit the various patterns? Is clinical management altered by responder status? 3.2. Questions relating to highly sensitized patients on renal transplant waiting lists 3.2.1. Sources of sensitization. Chapter 4 asks the question: what proportion of patients awaiting renal transplantation in Europe in 1986 are highly sensitized? How does the proportion differ between registries; with the recipient's sex; whether awaiting a first or regraft; by blood group (0 versus non-0); and by combinations of these? 3.2.2. Responder phenotypes. Chapter 5 investigates responder phenotypes: what is the relationship between HLA-type and high sensitization amongst patients awaiting renal transplantation? Is homozygosity for class I or class II antigens implicated in antibody production? Are specific antigens more common in the unsensitized than in highly sensitized patients awaiting transplantation, and vice versa? Is the relationship between HLA phenotype and antibody production the same for patients who have been transplanted, as for patients who await transplantation? Whether responder phenotype influences transplant survival is investigated later in Chapter 7. 3.2.3. Transplantation rates. Chapter 6 asks at what rate highly sensitized patients are being transplanted compared to unsensitized and moderately

21 sensitized cases; what is the morbidity and death-rate on the waiting list of highly sensitized patients; at what rate are highly sensitized patients being added to waiting lists? 3.3. Questions relating to transplanted highly sensitized patients 3.3.1. Transplant survival. Chapter 7 answers such questions as: what is the overall survival rate of kidneys transplanted between 1982 and 1985 into highly sensitized recipients? Are highly sensitized patients worth transplanting - what is the relative risk of transplant failure for highly sensitized compared to other recipients? Is the increased relative risk of transplant failure persistent or shortterm? How does its time dependence compare to other prognostic factors? Is the relative risk of transplant failure mitigated if the highly sensitized patient's latest reaction frequency prior to transplant is nil? What transplant penalty is associated with a B cell positive crossmatch test? What is the relationship of HLA-A, B, DR matching to transplant survival in highly sensitized patients? Taking high sensitization into account, do specific recipient DR antigens and A or B or DR locus homozygosity influence transplant survival? Does the survival of highly sensitized transplants (first or regrafts) vary between registries? Is day 1 graft function determined to a greater or lesser extent by the recipient being highly sensitized? 3.3.2. Daily clinical course: from transplant to hospital discharge. In Chapter 8 we ask: is the detailed post-operative course of transplanted highly sensitized patients different from that of appropriate controls? Comparison is made of reciprocal creatinine profiles, how and when rejection episodes are treated, and dialysis support in the immediate post-operative period.

3.4. Questions relating to special schemes for transplanting highly sensitized patients Chapter 9 details each scheme. Questions are asked as to the date of initiation of the scheme, how many centres are served by it, how many transplants to date and what proportion of donor kidneys are so used; what is the manner and frequency of distribution of sera, what quality control is imposed on % peak reaction frequency and how highly sensitized must recipients be before acceptance into the scheme. What about HLA matching requirements; treatment of autoantibodies; whether crossmatches with donor tissue are performed on all historical sera; and what priority is accorded to the scheme in the organ exchange hierarchy?

22

4. Sources of information: networked through the European Transplant Organizations The transplant organizations- Eurotransplant, France Transplant, Hispano Transplant, Luso Transplant, North Italy Transplant, Scandia Transplant, Swiss Transplant and UK Transplant - were the natural liaison centres for the Council of Europe Study because much relevant information was held already on their confidential databases of waiting-listed and transplanted patients. Anonymous data could be transferred centrally on floppy disk or magnetic tape to minimise transcription errors. The Study Group accessed follow-up information through the registry directors, who held the key to coded patient identifiers. Confidentiality was essential and so data acquisition and error checking outwith the registry database was also through the intermediary of registry directors (or their nominee) who undertook correspondence with individual doctors to resolve data management queries.

5. Strategy for data collection: pragmatically designed and activated studies The Study Group met in Strasbourg on 13 and 14 February 1986 to determine a strategy for data collection to answer the questions posed about serological pattern; highly sensitized patients on renal transplant waiting lists; transplanted highly sensitized patients; and special schemes for finding crossmatch negative kidneys for highly sensitized patients. The time constraint on the Study Group, to complete its work by December 1986, dictated that the Council of Europe Study should be pragmatically designed. A study manual was drafted which scheduled the manoeuvres to be enacted within the various European registries to initiate designated studies in the target areas. Speed was of the essence for several reasons: first, for all studies to be contemporaneous; second, for initiative and enthusiasm to be sustained; third, to permit data checking and correction prior to analysis; and fourthly, for analyses uniquely to reflect the flow of ideas across parallel fields of study. The Study Group met in June 1986 to review its progress on data collection and to comment on preliminary analyses of serological pattern and transplantation rates. Interim analyses of all studies were discussed in September 1986. The latest date for receiving answers to data management queries was 14 November 1986. The Council of Europe Study Group met for the last time in mid-December 1986 to review a draft report on final analyses of all studies. Studies were designed and activated as follows:

23

5.1. Data collection for questions relating to serological pattern Transplant centres which were represented on the Council of Europe Study Group (Bristol, Geneve, Leiden, Milan, Miinchen, Rennes) collaborated in charting serological data. Each centre was enjoined to send to the Study Director by 7 April 1986 a complete list of its renal patients who were awaiting transplantation and who, at some time, had had a reaction frequency of more than 50%. If the submitted list exceeded 30 cases, as for Leiden, the serological study was limited to 30 patients, selected by simple randomization. Mfinchen volunteered to chart all of its eligible patients; other centres listed fewer than 30 cases. Table 2.1 shows the questionnaire and antibody fluctuation chart which were completed for each patient. The chart allows for documentation of serological history and immunizing events between January 1980 and June 1986; requires panel size and cell type to be noted as well as % reaction frequency; and requests that serial events within the same month be written in chronological order. 5.2. Data collection for questions relating to highly sensitized patients on renal transplant waiting lists 5.2.1. Sources of sensitization and responder phenotype. The Council of Europe Study entailed computerised central transfer at the beginning and end of a 49 day period (7 April to 26 May 1986) of waiting lists from the following organ exchange organizations: Eurotransplant, France Transplant, Hispano Transplant, Luso Transplant, North Italy Transplant, Scandia Transplant, Swiss Transplant and UK Transplant. Individual patients were identified only by code numbers, the cipher to which was retained by the registry. Provision was also made for trial transfers prior to 7 April 1986 in case there should be difficulties in reading the floppy disks or magnetic tapes; such difficulties as there were being resolved in the MRC Biostatistics Unit. On 7 April 1986 a complete listing and tape of the waiting patients, including suspended patients, was generated to include: patient's code centre code ABO blood group H L A - A, B, DR type % peak reaction frequency transplant number (awaiting first or regraft) sex H L A - A, B, DR type of previous donors and dates of previous transplants.

24 Table 2,1. COUNCIL

Antibody

fluctuation

more t h a n

over

time:

50X p e a k r e a c t i v i t y

OF

E~ROPE

multi-centre

who a r e

STUDY

collaboration,

currently

awaiting

based

renal

on

patients

~ith

transplantation

~.~,--,.-...,-............ ~::.~...:,~.~:~:.>:..¢.:..¢~:~v~.>:.>•:.~. .>:•.,. :.•~:.,.. .:.•:.,. :.•:,. .:.7" :¢"+~ .:.:"+', .:.:.•:"~ .:~>:.."~+:+'~ .:".:~.:~..:.+:•~."~ :~.•.+"~." .:..~:.~'~ .~:.+~.~~'~ .~+.~" .:•+~" ..~•.•:•.•:."~;'~;:; ~.:.:.:";:;; +~.~~:. ..:..•.:.:. ...:.+:. ...•...:.; .~..~.~.,:. >...-> ...•• ~Number of p r e v i o u s renal g r a f t s (0 = untransplanted)i.:i ~:::;:~:~¥:~:::::i:.~i:i:i:~:~;~:i:~ ~:;:~:~$~::::::::~:::::.~:::::~::>Y¢~::::::~.:::.~::::.~:~:::~::.~:::::~::::::::::::::::::::~:~:::::::::::~.:::::::::::::::::::~::::::::::i:!:~

Sex of p a t i e n t

(| = male,

2 = female)

IF the

is female,

please

patient

has

IFtA - t y p e

of

she e v e r

recipient

been

F~ i.~

answer: pregnant

and p r e v i o u s

RECIPIENT

~ii

( ! = no,

2 = yes,

9 = not k n o w n )

D

donors

|st D O N O R

2rid D O N O R

3rd or most recent DONOR

A , B loci . . . . . . . . DR

locus . . . . . . . .

Transfusion

Panel

Date

history

.... t i v l t y

of most

Lowest

of p e a k

reactive

percentage

| = never transfused 2 = transfused 9 = transfusion history

.....

(peak)

of a n t i b o d y

(%) . . . . . d i n g

serum

since

(day,

not k n o w n

to T .... p l a n t

month,

] January

~--~ ~

Registry

I

i

I

1

year)

|980

Ill[

25

(continued)

Table 2.1.

COURCIL OF EUROPE STUDY Antibody fluctuatlon o v e r ti~e: m u l g i - c e n t r e c o l l a b o r a t i o n b a s e d on p a t i e n t s with more than 50~ peak reactivity who are currently awaiting renal transplantation

Month

Year

Ol

80

Month Ol

Events* . . . . . . . . . . . . . .

Year 83

Events* . . . . . . . . . . . . . .

83

. . . . . . . . . . . . . . . . . . . . . . . . . . .

02

80

. . . . . . . . . . . . . .

02

u3

80

. . . . . . . . . . . . . .

03

83

04

80

04

83

05

80

05

83

06

80

06

83

07

80

07

83

O~

80

08

83

0[,

80

I( ~

. . . . . . . . . . . . . .

09

83

80

10

83

I~

80

11

83

12

80

. . . . . . . . . . . . . . .

12

83

ol

8)

. . . . . . . . . . . . . . .

01

84

02

81

. . . . . . . . . . . . . . .

02

84

03

8~

. . . . . . . . . . . . . . .

03

84

O~

81

. . . . . . . . . . . . . . .

04

84

O?

81

. . . . . . . . . . . . . . .

05

84

06

81

...............

06

84

07

81

. . . . . . . . . . . . . . .

07

84

08

8~

. . . . . . . . . . . . . . .

08

84

09

8]

. . . . . . . . . . . . . .

09

84

Io

81

. . . . . . . . . . . . . .

10

84

I1

81

. . . . . . . . . . . . . .

II

84

~

81

. . . . . . . . . . . . . .

12

84

0~

82

. . . . . . . . . . . . . .

Ol

85

02

82

. . . . . . . . . . . . . .

02

85

03

82

. . . . . . . . . . . . . .

03

85

04

82

. . . . . . . . . . . . . .

04

85

O~

82

. . . . . . . . . . . . . .

05

85

06

82

. . . . . . . . . . . . . .

06

85

07

82

. . . . . . . . . . . . . .

07

85

08

82

. . . . . . . . . . . . . .

08

85

no

82

. . . . . . . . . . . . . .

09

85

~o

82

. . . . . . . . . . . . . .

lO

85

11

82

. . . . . . . . . . . . . .

11

85

12

85

O| 02

86 86

12 *

. . . . . . . . . . . . . .

82

In chronological

R

waiting

deregistered reason other

. . . . . . . . . . .

. . . . . . . . . . . . .

order

Event codes: please use the following codes document a n t i b o d y f l u c t u a t i o n s from J a n u a r y to the present and to record r e l e v a n t intervening events,

X

. . . . . . . . . . . .

to ~980

list r e g i s t r a t i o n

from w a i t i n g l i s t f o r than d e a t h or t r a n s p l a n t

03

86

04

86

05

86

06

86

T

transplanted

p

pregnancy

Y

graft

WB

whole

blood

D

patient

B

blood

transfusion

A

aucoantibodies

?%

L8

lymphocyte-free

reaction frequency of serum tested against a panel of lymphocytes/panel size/cell type e.g. 70%/30/U (T,B, or U for T cells, B cells Or u n s e p a r a t e d l~phocytes).

failure death detected blood

transfusion

(nos.)

transfusion

(nns.)

(nos.)

26 Listing, floppy disk or magnetic tape, and format details were sent to the Study Director and forwarded to the MRC Biostatistics Unit after preliminary tabulation (see Table 2.2) and for direct analysis of the relationship between registered HLA phenotype and sensitization status. 5.2.2. Transplantation rates and other transactions. Table 2.3 shows an example of the tally charts on which registry transactions between 7 April 1986 and 25 May 1986 were accumulated daily by sensitization status. Sensitization status was read from a reference hard copy of the 7 April 1986 waiting list of active plus suspended patients on which were listed only patients' code and % peak reaction frequency. To back up the tally charts and monitor successive transactions on individual patients, the hard-copy was annotated, using four coloured pens, with event dates for individual patients. Colours were assigned as follows: green records date of transplantation red records date of death blue records date of temporary suspension from the waiting list yellow records date and code for other transactions such as U % N F R X

unacceptable antigen change % reaction frequency change new registration re-registration after failed transplant other re-registration other transaction such as name change

The annotated hard-copy plus tally charts completed through 25 May 1986 summarised waiting list ebb and flow over a seven-week period by sensitization level (not recorded; unsensitized; 1-50% peak reaction frequency; 5180% peak reaction frequency; more than 80% peak reaction frequency at 7th ~ April 1986). 5.3. Data collection for questions relating to transplanted highly sensitized patients 5.3.1. Transplant survival. The Council of Europe database of highly sensitized and control patients transplanted between 1 January 1982 and 31 December 1985 was established through liaison with directors of the transplant registries (or their nominee). No patient or centre identifiable information was required by the Council of Europe Study Group; instead the registry directors forwarded a simple printout which identified highly sensitized and control transplants by

27 Table 2.2. COUNCIL OF EUROPE STUI)Y Summary of renal transplant registry current waiting list by peak sensitization

Registry

Waiting list analysis date

I_~__~ day

Please complete summary tables separatelyfor Blood Group 0 and Blood Group non-O $ waiting-llst patients BLOOD ~ O U P :

0

Total petients on aetlve file

S U B G R 0 U P female male female male no previous no previous previously previously + ~ t~l[--~ I i ~ ~d t~ ~ d i ~

|IIII

C~rent waltinE time !das_~__ mean

N ~ r of ~tients by peak sensitizationeate~ryl__~__T~ unsensitized (0%) IIIII I-I0%

--~

--~--

--~--~[

l lll~l ~

~°°~ 0~o~ ~_~o~ ~_~o~ ~+~

.T~T T T~T, T~T T~T ~ ~ . , ~ ~III ~ ~ ~ ~ ~ ~

~T~ ~ ,~ IIIII ~ ,~,

not recorded

~

~ ~

~ ~

,,~,,~

~

IIIII~

,,,,,,

"

I

month year

28 Table 2.2.

(continued) CO~I{CIL OF E~ROPE STUDY

Reaction frequency of most reactive serum prior to index transplant

-'--~1%

Date tested

Reaction frequency of latest serum prior to index transplant

~

Date tested

%

!

: ....... :k ~:~~.::.::!i:.::ii:!!!:! .~:~.~L.:~'L.:'::.~...~..,,:~,,.!~.~.~!_~.~.).~Y..~.~.~ .~:~.:%C~:~.~:~..' ~ ~:~: ~:~~:~~:~ ~..~%~:.~:~:. ~::~k..~:~.~.~'~x.~':~~.~.~~.;'~:.'~.~.~.~.~.:'~:

~Please record cross match results at index transplantation ~ ~ ~ ~:~:~:~:~:~:~:~:~:~:~:~~::~~::~~::~~:~:~:~:~:~~::~~::~:~~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~:~$~:~:~

::

~

:: ~B c e l l s

~ ~

~1 ~

1 = negative 2 = pos£t£ve

~~ ; ~ ~u

~unseparated 1 ~phocyt es ~ ~:~::~:~{~:{~{~:~:~%~{~{~ Please record total ischaemia time in HOURS (999 = not known) for the index transplant

~

HRS ~

~

~

Was Cyclosporin included in INITIAL (DAY I) immunosuppression I = no for the index transplant 2 = yes 9 = not known

--

Was there immediate kidney function of the index transplant?

--

_

I = no 2 = yes 9 = not known

_

Recipient status at last known follow-up Please record recipient's last known status I = alive, index 2 = alive, index 3 = dead, index 4 = dead, index

graft graft graft graft

functioning failed functioning at time of death failed

Date of last known follow-up (for status I, 2 recipients) Date of return to chronic dialysis after index transplant (for status 2, 4 recipients) Date of death (for status 3, 4 recipients):

Name of recipient

day, month, year

...............................................

Registry recipient code

I

I

I

1

1

1

1

1

1

1

1

1

29

c~o

~l

®!

|

X ~

~

°~

~

°~

~

~

~

~

30 code numbers, the key to which remained with the registry. The list gave for each transplant: recipient's code centre code recipient date of birth recipient date of transplant transplant number (first or subsequent graft) recipient sex whether diabetic % peak reaction frequency pairmate's code. Instructions on how to sample matched controls for highly sensitized patients had been sent to the registries. Because transplant survival varies by graft number, year and centre of grafting, control transplants were centre, sex, graft number (first versus regraft) and year of transplant matched to highly sensitized recipients, sex matching being invoked because the prevalence of high sensitization differs between the sexes. First transplant controls were determined to be 10% or less sensitized (peak reaction frequency). A pilot search at UK Transplant for regraft controls showed that a more liberal upper % peak reaction frequency was necessary to find sufficient centre, sex and year of transplant matched control regrafts. Accordingly, regraft controls were determined to be 30% or less sensitized - see sampling instructions in Table 2.4. The decision to compare highly sensitized to lowly sensitized control recipients was taken to ensure that the Council of Europe Study gave a 'worst case' answer to the question "are highly sensitized patients worth transplanting?" by comparison of the practical extremes of sensitization. The importance of listing all highly sensitized transplants irrespective of whether a complete follow-up record was then available to the registry was stressed, for the Council of Europe database would be completed from individual patient questionnaires (see Table 2.5) sent out through the intermediary of registry directors who, of course, held the key to patient identification. Individual questionnaires were generated and checked from the lists received via registries; Council of Europe Study numbers were assigned to identify matched highly sensitized and control grafts, for example UAH301 and UAC301 designate the highly sensitized (H) and control (C) members of graft pair 301 for UK Transplant (U). UK pair 301 was transplanted in centre A.Questionnaires also carried the patient's code as given by each registry, so that the registry director could identify the patient for correspondence with individual doctors. The partially completed Council of Europe questionnaires were returned with a covering letter from the Study Director and the Council of Europe

31 COUNCIL

OF E U R O P E

SECRETARIAT

GENERAL

P|¢ale quote :

Strasbourg, 16 April 1986 VMB/kf

SUBJECT:

Procurement and sharing of transplantable organs for highly sensltlsed patients

Dear Professor/Doctor, As you may "know, the Council of Europe has been very active in the field of blood transfusion and hlstocompatibllty for many years, through its Committee of Experts (SP-}LM~). One of this Committee's most important activities is a biennial programme of co-ordinated research, which for 1986 is concerned with "an investigation of the procurement and sharing of transplantable organs for potential recipients who are highly immunised to HLA-antlgens". This subject will assume particular importance as we prepare for the Conference of European Health ~linisters in France next year, which will be devoted to the whole question of organ transplantation. The Conference will naturally focus attention on the various problems and developments in this field and the results of recent research. The Study Group set up to supervise the SP-~LM research programme agreed at its first meeting that baseline information could most easily be collected through the various European organisations responsible for organ sharing. Confidentiality of the data would, of course, be a paramount consideration. You will be receiving, together with this letter, a personal invitation from the Study Director to participate in the study, I do hope you will be able to accept this most important invitation.

~,~ Vfira N/~SSARELLI-BOLTItO Health Division

LETTER ADDRESSED TO F~DICAL PERSONNEL COOPERATING IN THE ABOVE COUNCIL OF EUROPE STUDY

Figure 2. l.

32 U.K. TRANSPLANT SERVICE Benjamin A. Bradley

Medical Director

Derek R. Moras Neville H. Selwood Peter 7[ Klouda

Administrator Data Processing Immunogenetics

Oornet

c/o Regional Transfusion Centre Southmead Bristol BS 10 5ND. Telephone: (0272) 507777 Telex : 449384

$4.35/mjc

Date: 6 May 1986

Dr Lars Lamm Tissue Typing Laboratory Aarhus Kommunehospitalet DK-8000 AARHUS C Denmark Dear Lars

Council of Em-ope Study Please find enclosed two packages. The first contains letters of introduction to the doctors in charge plus a letter and codicil to be returned giving their consent to participate in the study. The second consists of a letter to the doctors in which their transplanted highly sensitized patients and controls should be listed. This should be sent together with the appropriate number of labelled forms (white for first transplants and yellow for regrafts). Please could you: I,.

Read the instructions on "how to sample controls for transplants etc."

2.

Make lists for each centre.

3.

Fill in the Doctor's name and the estimated number of patients on whom you expect to ask for information (last p a r a ~ a p h ) and dispatch the introductory letters.

4.

Prepare a sufficient number of forms for each centre and prefill forms with as much data as you already have on file.

5.

Send prefilled forms together with the covering letter (complete the name of the doctor, the list of patients and the registry name) to the Doctor in Charge for a) checking and b) by completion Of data and c) returning to you by 26 May 1986. You should send a eoverlng letter to this effect.

6.

Collate the completed forms and dispatch them to me.

Sorry to burden you. Thank you for your help ....

Ben Bradley Ene:

"Package [" 1.

Instructions on selection of controls.

2.

Copies of introductory letter from Vera Massarelli-Boltho on behalf Of the Council of Europe and letter of introduction (number of patients to be inserted) and a ~ e e m e n t to participate, return to Dr Ben Bradley.

"Package If" 3.

Copies of white and yellow forms. Letters of instruction t o d o c t o r s .

Figure 2.2a.

Please read carefully.

33 U.K. TRANSPLANT SERVICE Benjamin A. Bradley

Medical Director

Derek R. Moras Neville H. Selwood Peter 7: Klouda

Administrator Data Processing Immunogenetics

ou~ ~ :

Dr Dr

c/o Regional Transfusion Centre Southrnead Bristol BS 10 5ND. Telephone: (0272) 507777 Telex : 449384 Oa,e:

6 May 1986

..........

Study of the procurement and sharing o f transplantable ors~ns for hlgl~ly sensitized patients You are invited to participate in this study whose objective is to answer questions relating to the outcome of transplantation in highly sensitized patients. Too few patients exist at any one centre and it is necessary to assemble a database consisting of donor-reclpient pairs from several European centres. These will be studied on a strictly confidential basis both in terms of preserving the anonymity of the donor and recipient as well as the name of the transplant centre. None of these pieces of information is relevant to the study and it need not be revealed to the study team. Anonymously coded data will be collected on a computer database and analysed centrally. Needless to say you will receive a copy of the final repot and your centre will be acknowledged therein should you wish to participate. Our deadline is short and we hope to have the final report assembled in July 1987. We anticipate that the work involved would not extend to more than ..... patients. Please indicate your wishes below and return the reply sllp to me immediately. Thank you. Yours sincerely

B A Bradley Director of Study

Name of Centre:

...............................................................

Address:

...............................................................

I accept/refuse the invitation to partlcpate in the Council of Europe Study. Signature:

.........................

Position:

.........................

Encl:

Figure Z2b.

Section 5.4 of Study Manual Section 5.5.3 of Study Manual

34 Table 2.4. How to sample controls for first transplant~ hi~hl~ sensltlsed (HS) 1982-85 recipients and for re-transplants I.

EXCLUDE LIVING RELATED DONOR GRAFTS

2.

FOR EACH CENTRE SEPARATELY: construct 8 centre flats Of "more than 80% sensltised Ist transplanted recipients" as follows : ist TRANSPLANT

Ist TRANSPLANT CENTRE-LIST

Hi~hlz sensltlsed (more than 80%) recipients

CONTROL (10% or less) recipients

I

RS males transplanted in 1982

C 10% males transplanted in 1982

2

HS males transplanted in 1983

~ I0% males transplanted in 1983

3

HS males transplanted in 1984

( 10% males transplanted in 1984

4

RS males transplanted in 1985

( 10% males transplanted in 1985 4 10% females transplanted in 1982

5

HS females transplanted in ]982

6

HS females transplanted in 1983

~ 10% females transplanted in 1983

7

HS females transplanted in 1984

4 10% females transplanted in 1984

8

HS females transplanted in 1985

~ I0% females transplanted in 1985

3.

FOR EACH CENTRE: generate g corresponding centre-lists of "10% or less sensitised ist transplanted receipients" (see above table)

4.

FOR EACH CENTRE SEPARATELY: match controls from list 1 to highly sensitised recipients on list 1; controls from list 2 are used as matches for highly sensitlsed recipients on llst 2 and so on. If llsts are in order of pool number~ take controls from the top of the list; otherwise, sample randomly. If the control llst is shorter than corresponding HS llst, then select additional controls (of the same sex) from the top of the list for the following year. Do not select the same control twice. If the control llst is longer than the corresponding HS list~ ignore additional controls.

Example:

UKTS

CENTRE-LIST A

5.

1

Ist TRANSPLANT

Ist TRANSPLANT

High[ ~ sensitlsed recipients

CONTROL

pool number 0090

.... MATCH ....

pool number 0103

recipients

pool number 0105

.... MATCH ....

pool number 0554

pool number 5006

.... MATCH ....

pool number 1143

IGNORE ....

pool number 2}01

In the example above, Council of Europe study numbers might he assigned as : UAHO01 (UKTS)(CentreA)(Highly sensitised)

UACO01 (UKTS)(CentreA)(Control match for H001)

UANOO2

UACOO2

UAROO3

UACOO3

For re-transplants: As a~ove, but controls " 30Z or less semsltlsed" and NOT MATCHED for graft number ( s e c o n d , t h i r d , . . . g r a f t ) . 6.

PRECODED revised Council of Europe forms to be sent to the transplant centres with request for data checking and entry of new details. ~{:~:~:~:{:~:~{${:~{:{~{:~{:~:{:~:~:~:~:~:~$~:~:~9~:~{:{~:{:~:{:~{:~:~:~:~e~Z~:~:::::::::~:::~::~:~:~:~:~:~:~:{:~:{:~:~:~:~{:~:{:{:9{:~:{:~e{:{~:~e~:~:::~::~::~:::~::;~{ !ii~Transplant centres should be asked tO check whether a 'so-called' highly sensitised patlent~i!~ Ii was more than 80% sensltised at the time of Index transplant. ~ If YES, please complete highly sensitlsed and control forms. If NO, please return the palr (H,C) of forms marked: "inellglble because HS-reclpient was not highly sensltlsed (more than 80%) at tlme of index transplant"

7.

Revised Council of Europe forms will be circulated to registries by 5th May 1986.

35 Tab& Z ~ COUNCIL OF EUROPE STUDY

Follow-up of 1982-85 highly sensitized (higher than 80~ peak reactivity) and control (IO~ or lower peak reaotlvity) eadaverie renal FIRST TRANSPLANT recipient pairs. Council of Europe Follow-up:

recipient number

Recipient date of birth (day, month, year)

l

Date of index transplant on which follow-up is requested (day, month, year) Graft number of index transplant

(I = first, 2 = second...)

13

IF the index transplant is the recipient's second or subsequent transplant, please record: date of immediately preceding transplant (day, month, year)

I

I

I

type of donor kidney for immediately (I= cadaver, preceding2 = live transplant donor) date of failure of immediately preceding transplant (day, month, year)

I

3 I

I I

I I

I I

I I

I I

Sex of recipient (I = male, 2 = female)

~

Is the recipient diabetic?

~--~

(I = no, 2 = yes, 9 = not known)

IF the recipient is female, please answer: has she ever been pregnant prior to index transplant? (I = no, 2 = yes, 9 = not known) ~:~{~!~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i~i{i~i~i{i~i~i~i~i{i~i~i~....i~i~i~ iiiHLA - type and mismatohes at index transplant ~ii ~iiiii~i~i~i~!~!~!~!~!~!i!~!i!i~!i~i!i!i!i!i!i!i!i!i!i!i!i!i!~....i~i~i~i~i~i!i~i~i~i~i!i~i~i~i~i!i!i!~!~!i!~!~!~!~!~!~!~!~!~!~!~!~!~!~!~!~!~!~!!~i~!~!~!~!~!~)!~!~.~i~!~!~!! RECIPIENT A

locus

........

B

locus

........

DR locus

........

Transfusion history prior to index transplant

DONOR

I = never transfused 2 = transfused 9 = transfusion history not known

2 MISMATCHES

36 Health Division Secretariat (see Figures 2.1 and 2.2) to the organ exchange organizations, where additional data were transcribed from the registry database before the director (or his nominee) approached individual doctors to ask for their consent to the Council of Europe Study and participation - by checking the prefilled data, supplying missing information and carefully completing the section on recipient status at last known follow-up. Questionnaires were returned from the organ exchange organizations to the MRC Biostatistics Unit where a data checking program was implemented; queries were resolved by reference back to registry directors and so to individual doctors. In Eurotransplant most data required for the Council of Europe Follow-up Study were held already on the Eurotransplant database, so that a magnetic tape of the relevant data for all highly sensitized transplants from 1982 to 1985 could be prepared. A second tape was sent which reported on all control transplants; matching, as prescribed, was implemented at the MRC Biostatistics Unit. Only the dates of peak reaction frequency for highly sensitized grafts were not transferred on magnetic tape and so paperwork was involved in their acquisition. 5.3.2. Daily clinical course. The detailed post operative course of matched controis and recipients transplanted under UK special scheme for highly sensitized patients (SOS scheme) was monitored in selected centres, in continuation of a pilot study initiated by the UK Transplant Service Management Committee.Table 2.6 shows the record of serum creatinine and immunosuppression (and whether dialysed or treated for rejection) which was completed retrospectively from the day of transplant until hospital discharge. 5.4. Data collection on special schemes for transplanting highly sensitized patients Table 2.7 illustrates an open questionnaire designed as a prompt for more or less detailed answers to questions about special schemes for transplanting highly sensitized patients. The questionnaire was addressed to the director of each scheme who was invited additionally to record any other special features not covered by the questionnaire. Details of the following schemes are discussed in Chapter 9: Eurotransplant Scheme I (European highly sensitized patient) Eurotransplant Scheme II (European immunized file) Eurotransplant Scheme III (acceptable HLA-A and B mismatches) France Scheme I (serum exchange between six centres) Heidelberg Highly Immunized Trial (HIT Scheme) North Italy Transplant Scheme I (more than 30% peak reaction, frequency)

37

o

~ ~ll ~ D ~

o u

~v

U

38 Tab~ 2. 6b. HIGHLY SE~SITISED STUDY : SUMMARY SHEET OF REJECTION EPISODES IN FIRST YEAR A~TER (INDEX) TRANSPLANTATION

Patient's

name . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

HSS serial number O _ _ N I 3 centre

Date of transplant O~e

o~ o - - ~ o~ ~ o ~

~ooo~oo

Date Of discharge

0333N UKTSno.

0----~ day

OD month

0_~

$3

day I~

month

day

month

I~

__N code : I = HS patient 2 = control patient O~ year

~ra~t number 0 3

~_~ year

I~ year

Date of onset of each rejection episode for vhich steroid or other therapy is given ~o~oo

~ o ~

: oo.~

I_~ ~_~ ~_~

re_~ection episode 2 : onaet

~ day

month

year

day rejection episode 4 : onse~ J ~

month I~

year I~

rejection episode 5 : onset ~

mon~

~__

re~ecc~on episode 6 : onset ~ d ~

~on~

~__

~e~=~oo

r~

JeccZon

~ o ~ ,

: oo.~

L~N

O~ ~

O~

.~.o~ 7 ~ o_~ day

month

year

39 Tab~ 2.6c. HIGHLY SENSITISED STUDY :

Patlent~s

.~"

n~me . . . . . . . . . . . . . . . . . . . . ~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.~.~ ooo~,~ Cl_-I_-EI

:l_-I_-iZl_-I

centre

~S

code : I = HS patient

no.

2 = control patient FOLLOW UP RECORD ~

Patient status at last known follow-up I 2 3 4

= = =

alive, alive, dead, dead,

[I

l ~

functioning graft failed graft (PLEASE SEND CRAFT FAILURE RECORD) functioning graft at time of death failed graft (PLEASE SEND GRAFT FAILURE RECORD)

Date of death (for status 3,4 patients)OR d a t e of l a s t

follow-up (status

~

I ~

~

1,2 p a t i e n t s ) day

month

year

CRAFT FAILURE RECORD D a t e of g r a f t

failure

day

month

da y

month

I_~

D a t e o f r~moval of g r a f t (999999 i f g r a f t has n o t been removed)

D...

o~

..,~o

~o

..,~..

,,.,y.,.

u_~

_~a

day

Reason for graft failure

(please specify

I = rejection 2 = non-i~unolo~lcal

...................................

year

month

[~ ~ )

year

~-~ year

40 U.K. TRANSPLANT S£RVICE Benjamin A. Bradley

Medical Director

Peter M. Brooman Neville H. Selwood Peter T, Klouda

Administrator Data Processing Immunogenetics

OU¢Ref:

South Western Regional Transfusion Centre Southmead Bristol BS I 0 5ND. Telephone: (0272) 5 0 7 7 7 7 Telex : 449384

BAB/RC

Date:

PROFESSOR G D TRANSPLANT UNIT GENERAL HOSPITAL Dear Geoffrey, Re: Verification of ~our data for Council of Europe Study on Highly Sensitized Patients. Further to my letter of 5th June 1986 please find enclosed semi-filled forms containing UKTS held information on your transplanted-highly sensitized and non-sensitized control patients who have been matched for sex, year and transplant number. The white forms contain information on first transplants and the yellow forms contain information on retransplants. The patients name and UKTS number are in the bottom right hand corner and the index transplant under study is identified by a date and a number on the left hand-side, line 6. The Council of Europe reference number contains a U for United Kingdom, a centre code (your centre is A), a sensitization code (H for highly sentized, C for control) and a patient number (001 etc.). From our records we have identified 9 highly sensitized first transplants and 6 highly sensitized retransplants together with an appropriate number of controls. However since our records may not be fully comprehensive I am enclosing a set of blank forms for use at your discretion. Please could you do the following: I.

Carefully check the date and number of the index transplant.

2.

Check the prefilled information against your record for accuracy. ( Corrections in colour are preferred).

3.

Fill in the missing information

4.

D i s p a t c h the completed forms in the envelope provided to Dr. S.M. Gore, MRC Biostatistics Unit, 5 Shaftesbury Road, CAMBRIDGE CB2 2 B W - to arrive by the DEADLINE of IST. AUGUST 1986.

(indicated by a ?)

I am sorry for the tight schedule but we intend to have the study analyzed and the report written by the end of November 1986. Thank you for your help. Yours sincerely,

Encl: first transplants (9) retransplants (6) 3. Matched controls - first transplant (8) 4. Matched controls - retransplants (5)

Ben Bradley Director of Study

Figure 2.3.

1. 2.

HSP HSP

5.

Blank

-

forms

6. Addressed envelope

41 Table 2. 7.

Open questionnaire for details of special schemes to find acceptable kidneys for highly sensitized patients. Name of Scheme

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Date Scheme initiated

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Material distributed (Lists,serum sets, duplicate serum sets etc ............................................................................................... Frequency of distribution of material to centres .......................................................................................... Number of centres served ............................................................................................ % RF cut off for eligible patients .......................................................................................................... Treatment of autoantibodies

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Maximum acceptable H L A - A & B mismatches .......................................................... Minimum acceptable H L A - A & B shared antigens ..................................................... Maximum acceptable H L A - D R

mismatches ...............................................................

Minimum acceptable H L A - D R

shared antigens .........................................................

Are positive pre-operative cross-matches ignored?. .......................................................................................

B cell

Are crossmatches w i t h donor tissue performed w i t h A L L pre-operative (historic) serum samples ~ ............................................................................................

i!i!i~i~i:i:!;i;!;!;i;i:i;!;!;i;i:i:i~i~i:i;!;!;!~:~;~;!;;:!~;:;:;~;~;:;~::::;:;:;:;~;:;;;;;;;;~:::;:;;;;;~;;~:~:::~:~;~;~::::~;:;:;;;~:i

;ii Total number of transplants il !:ililcarried out under this schemei~i!..................................................................................... What % of all kidneys handled by your service are transplanted into HSP under this scheme ? ....................................................................................... ~=~i~i~i~i~i~i~i~i~i!~i!~!=!i~i!~i!i~i~i~¢i!i!i$i~i$i~:$i;!~i~i~i~i~$~$!~!i!=!~!$~i!:~i~=~$~!~!i!~!;!i!~!$~:~i~';~i

i;ii Wh'~t are the priorities for iili iiiii offering kidneys in your routine iiill iili organ exchange programme ? .....!~!................................................................................. ::::::::::::::::::::::::::::::~:~:~:;:;:;:~:;:~::::::::::::::::::::::::~.:;:i:!:i~::i:i:i~i:;:i:i:i:i:!:!:!~!:!:!:!:!:!:!:!:!:i:i:~:i~i:;i:::i:i~:~i~

Other special features of the scheme ..............................................................................................................

42 North Italy Transplant Scheme II (more than 85% peak reaction frequency) Scandia Transplant Scheme I (more than 90% peak reaction frequency) Swiss Transplant Scheme I (more than 50% peak reaction frequency) Swiss Transplant Scheme II (more than 80% latest reaction frequency) UK Transplant SOS (Save our Sensitized) Scheme.

6. Design faults Pragmatism characterised the study plan, as it did the definition of high sensitization. Some deficiencies of questionnaire or study design were the price of that expediency. Pilot studies were limited to pre-testing at UK Transplant of the antibody fluctuation chart (Table 2.1), the tally chart for registry transactions (Table 2.3) and the scheme for sampling control grafts (Table 2.4) in the follow-up study on transplant survival. The daily record of serum creatinine and immunosuppression (Table 2.6) had been piloted previously. Ironically the only serious deficiency- in the transactions s t u d y - escaped detection, despite piloting at UK Transplant. It emerged that registries differed in how they record the sensitization status of patients entering the waiting list. Design faults are highlighted on the study documents and discussed here: Table 2.1. "Number of previous transplants" should have read "Number of

transplants prior to January 1980", all subsequent transplants being evident from the serological chart. Some respondents quoted total transplants; others reasoned that the number of transplants prior to January 1980 was the missing datum and answered accordingly. The ambiguity could have been avoided by asking for the dates of all transplants, as was eventually done to resolve this design fault. Table 2.3. Two design faults foiled our estimation of the rate at which highly

sensitized patients are added to waiting lists. Firstly, the practice in several registries (see Chapter 6) is initially to register all new patients on the waiting list as "sensitization status not known", so that these registries tallied no new registrations of sensitized patients. Future transaction studies in such registries should plan to follow-up new registrants to discover their peak reaction frequency as first designated after compliance with registry protocol. The second problem was that "OTHER TRANSACTIONS: antibody frequency change" should have read "OTHER TRANSACTIONS: peak antibody frequency change" and made clear that only changes between sensitization categories (~) were to be tallied:

43 + + + + +

not recorded; 0% peak reaction frequency; 1-50% peak reaction frequency; 51-80% peak reaction frequency; more than 80% peak reaction frequency.

Table 2.4. Instructions on how to sample matched controls for highly sensitized patients were received in Scandia Transplant when selection of controls had already been completed. The local procedure failed to match adequately for year of transplant (see Chapter 7). The sampling instructions and also the Study Director's letter of instruction to doctors (see Figure 2.3) asked for verification that so-called highly sensitized patients had had, prior to the transplant of interest, serum which reacted with more than 80% of the population. The check was instituted because peak reaction frequency could be overwritten at UK Transplant. For example, 5% peak reaction frequency before first graft could be overwritten by 85%, if the recipient's serum prior to regraft reacted with 85% of test panel cells - such a patient is genuinely highly sensitized at regraft, but not at first graft. Thus, sampling was provisional until highly sensitized (and control) status had been verified in the transplant centre. The burden of verification fell most heavily on UK centres, with consequent mismatching in totals of and year of transplant for highly sensitized and control grafts (see Chapter 7). Table 2.5. Recipient blood group and the HLA type of previous donors were

overlooked in the follow-up questionnaire. The questions on positive crossmatch results were ill-conceived because, whereas some laboratories test all historical sera, others test only peak and latest serum. The crossmatch results on peak and latest serum prior to index transplant should have been elicited separately; any other positive crossmatch tests should have been qualified by the dates of the sera which reacted against the donor's cells. In addition, the form did not ask for the target tissue, eg spleen versus peripheral lymphocytes. Follow-up questionnaires would have been returned more quickly if clinical and laboratory data (HLA-type, reaction frequencies, crossmatch results) had been requested on separate forms, avoiding sequential completion. Table 2. 7. The total number of transplants carried out under a special scheme needs to be related to the scheme's duration. A supplementary letter was sent to ask for the number of transplants up to a recent convenient, specified date, date of initiation of the scheme being known already. The letter also gave an example of offer priority for special scheme (SOS) patients in the UK and invited corresponding flowcharts from other registries to explain what priority is accorded to their special scheme patients in the organ exchange hierarchy.

44

7. S~a~gy Time constraints emphasised the need to anticipate data management, analysis and presentation of results at the very design and planning of the Council of Europe Study. Accordingly, in advance of receiving the data: (1) checking routines were written to complement the designed data collection forms; (2) analysis plans were formulated in sufficient detail that analysis programs could be written, including appropriate data management subroutines for dates to be transformed to graft survival times, HLA-splits transformed to broads when determining number of mismatches, and for indicator variables to be created to test interactions, as between high sensitization and beneficial matching (ie zero DR mismatches and at most one A ÷ B mismatch); and (3) graphical representation, the art of statistics, was envisaged for results of complex analyses, and the necessary graphics programs were devised. Because research is an iterative cycle of design, experimental data, analysis, discussion followed by redesign, more experimental data, re-analysis, more discussion, the Study Group scheduled meetings strategically for June, September and December 1986. In June (pour encourager les autres) the Study Group reviewed data acquisition and preliminary analyses of transplantation rates and serological pattern, which were new fields of study. Discussion resulted in (1) re-experiment - Eurotransplant could provide data separately on transplantation rates for patients awaiting first versus regraft - and (2) re-analysis by improvement of the graphical output on serological pattern. In September (ved skillevejin) analyses, as formulated, of all studies were discussed, albeit data were then incomplete. Discussion resulted in (l) re-experiment - UK Transplant and Eurotransplant were to provide HLA-type of first donors for highly sensitized/control second graft pairs to test whether mismatching at first graft was associated with later sensitization; acquisition of France Transplant waiting list to validate sources of sensitization elucidated by other registries' analysis; acquisition from Eurotransplant of latest reaction frequency (and date) prior to index transplant to evaluate more definitively peak positive, currently unsensitized transplants. Discussion led to (2) reanalysis- to investigate homozygosity and recipient phenotype and antigen sharing, as well as mismatching, in relation to transplant survival. In December (wha dare meddle wi' me) the final analysis report, incorporating suggestions to date, was presented. Still, discussion resulted in (1) re-experiment- UK Transplant and Eurotransplant, and other registries if possible, were to provide current Hardy-Weinberg analysis of donor phenotype as a backcloth for analyses of recipient phenotype and high sensitization; and (2) re-analysis-to investigate day 1 graft function in relation to transplant survival. Moreover responder phenotype was to be assessed in transplan.ted as well

45 as waiting recipients and complemented by Hardy-Weinberg analyses of waiting list and transplanted databases, separately for highly sensitized and control patients. Responder phenotype was a speculative field of study for which only exploratory analysis had been planned - its interest revealed, appropriate multifactorial methods were finally invoked which resolved the Study G r o u p ' s unease at trying to assimilate a series of antigen-specific analyses. The iterative research cycle thus continued beyond December 1986 to deal with issues raised at the Study G r o u p ' s final meeting. Advance preparation of data management and analysis routines was crucial if studies were to be not only designed but analysed contemporaneously, facilitating uniquely the flow of ideas between parallel studies, and for the final report to reflect that intercourse.

8. General notes on statistical thinking and methods

"Nature will best respond to a logically and carefully thought out questionnaire; indeed if we ask her a single question, she will often refuse to answer until some other topic has been discussed". Sir R A Fisher. Nature's refusal to answer a single question can be seen as a warning against simplistic analysis. Analysing factors one by one can mislead: (1) by overlooking important influences discernable only when some co-factor is also present in the equation; (2) by ascribing significance when there is none except by confounding with another covariate; and (3) by overclaiming significance for companion covariates, any one of which could stand as proxy for the others and which therefore do not give separate insights. Multifaceted problems require multifactorial methods for their solution; the multifactorial methods which we apply in the Council of Europe Study involve regression models of one sort or another. 8.1. Regressio n m o d e l s

Briefly we consider the range of regression problems resolved in three chapters of the Council of Europe Study. Chapter 4

How does the number of patients awaiting renal transplantation relate to sensitization status, recipient sex, graft number (first versus regraft), blood group, registry and interactions amongst these? Chapter 5 In addition to the foregoing factors, which aspects of recipient phenotype weight in favour of high sensitization and which point to the recipient being unsensitized, and by how much is the risk score tipped in either direction? Chapter 7 How do the many covariates, such as HLA-mismatching, high sensitization, year of transplant, Cyclosporin A, ischaemia time, jointly influence transplant survival and how can their several influences be quantified? Technically, counts - that is numbers of waiting patients belonging to the same crossclassification when described by sensitization status, sex, graft number, blood group and

46 registry - are the response variables in the first problem. One such count is the number of highly sensitized, blood group 0 females awaiting a first transplant in the UK. In the second problem, the binary outcome for which a risk score should be evolved is whether the patient is highly sensitized or unsensitized. And in the third problem, the risk score should relate to transplant survival time, so that the response variable is a

survival outcome. The three outcome variables require different links between risk score and response variable. The first is a log-linear regression model in which the In counts (natural logarithm to the base e of counts) are regressed on the risk score; the second is a linear-logistic regression because the logistic or In(odds) transform of the probability of being unsensitized is regressed on the explanatory variables; the third is a relative risks or proportional hazards regression model in which the logarithm of the relative risk of transplant failure is regressed on the covariates (alias explanatory variables alias prognostic factors). 8.2. Regression coefficients and risk score summation Although the link is different in the three problems, and so the statistical estimation is technically different, the goal of that estimation is the same in all three settings: namely to estimate the regression coefficients which quantify the influence of covariates in the risk score. Thus central to any regression model in the Council of Europe Study is a risk score, which is defined as a weighted sum of covariates, the weights being the (regression) coefficients which are estimated from the data. We illustrate a (hypothetical) risk score for distinguishing between highly sensitized and unsensitized patients awaiting transplantation in the UK. All covariates in this example are coded 0, 1. Because 1 "indicates" presence of the covariate and 0 its absence, such covariates are often called "indicator variables". HYPOTHETICAL U K RISK SCORE FOR BEING UNSENSITIZED risk score = 2.2 - 1.3 x (female) - 2.5 × (regraft) + 1.1 x (female regraft) - 0 . 4 x (A homoz.) - 0 . 3 x (B homoz.) +0.1 x (DR homoz.) To work out the risk score for a regraft female who is A homozygote but B and DR heterozygote we sum:

= =

2.2-1.3 × 1 -2.5 x 1 +1.1 × 1 (female) (regraft) (female regraft) -0.4x 1 -0.3×0 +0.1 × 0 (A homoz.) (not B homoz.) (not DR homoz.) 2.2-1.3-2.5+1.1 -0.4 -0.9

The BASELINE 2.2 is the risk score for a baseline individual who is male, heterozygote on A, B and DR loci, and awaiting a first graft. Figure 5.1 in Chapter 5 shows how to convert a linear-logistic risk score of -0.9 to the probability (28% chance) of being unsensitized; the BASELINE male has a 90% chance of being unsensitized. 8.3. Covariate structure How covariates are coded is important - model comparison may involve comparing different covariate coding schemes. Compared to 1982 (BASELINE), three indicator

47 variables could identify separately the.transplant years 1983, 1984 and 1985 or a linear trend could be imposed by coding transplant year as 1 if 1982, 2 if 1983, 3 if 1984 and 4 if 1985. Coding for trend thus forces the risk score contribution for "transplanted in 1985" to be four times that for "transplanted in 1982". In Chapter 7, we explore a variety of coding schemes for HLA-mismatching in search of a scheme for intelligent HLA-mismatching which still safeguards transplant survival. 8.4. Standard error, z-score and confidence interval for regression coefficient Estimating regression coefficients is not the end of business. We need a measure of precision (so-called standard error) to judge that the estimated regression coefficient EITHER deviates significantly from zero so that the covariate is deemed influential, OR is a quite plausible realisation even had the covariate truly no influence on the outcome of interest. Approximately, a 95% confidence interval for the true regression coefficient runs from two standard errors below the estimated coefficient to two standard errors above the estimated coefficient. If the 95% confidence interval includes zero then the observed regression coefficient is consistent (at the 5% significance level) with the covariate having no true influence on the outcome of interest. If the 95% confidence interval excludes zero then the estimated regression coefficient deviates significantly from zero (at the 5% significance level) and the covariate is deemed influential. Throughout we assume that regression coefficients and their standard errors are estimated multifactorially, that is jointly with the coefficients for other explanatory variables also in the risk score. The confidence interval tells us more than mere significance testing because it substitutes interval estimation for point estimation - the limits of the 95% confidence interval reveal the lowest and highest true influence of the covariate in the light of which the observed regression coefficient is plausible - that is, would not be rejected as extreme by a significance test at the 5% level which compared the observed regression coefficient to any value in the confidence interval. Likewise there is an affinity between 99% confidence intervals and significance tests at the 1%0 level - a 99%0 confidence interval consists of all possible true covariate influences with which the observed regression coefficient is consistent at the 1% level. Whereas the width of a 95% confidence interval is 4 standard errors, the width of a 99% confidence interval is 5.2 standard errors. Several regression coefficients from the above hypothetical U K risk score are tabulated in Table 2.8 along with standard error (se), z-score, (see below), lzl (z-score without its sign) and 95% confidence interval. The 95 % confidence interval for the regression coefficient for A homozygosity (from - 0 . 5 6 to -0.24) lies entirely to one side of zero; the 95% confidence interval for the influence of DR homozygosity (from - 0 . 0 5 to 0.27) straddles zero and so DR homozygosity is not a significant risk factor at the 5% significance level. Table 2.8 shows also for each covariate its z-score, that is by how many standard errors the regression coefficient deviates from zero. Thus: z-score

-

regression coefficient standard error

Given regression coefficient and z-score: standard error = regression coefficient z-score

48

Table 2.8. Covariate

Coefficient

se

95% confidence interval

z-score

lzl

female regraft A homoz. DR homoz.

1.33 -2.52 -0.40 0.11

0.13 0.16 0.08 0.08

1.07 to 1.59 -2.84 to -2.20 -0.56 to -0.24 -0.05 to 0.27

10.23 - 15.75 -5.00 1.38

10.2 15.8 5.0 1.4

F o r brevity, z-score is often reported as l z l , the direction of the deviation from zero being evident from the sign of the regression coefficient. Standard error is always positive; given regression coefficient and l z l : standard error = ]regression coefficient] lzl Mostly, tables in subsequent chapters will give regression coefficient and l z l from which standard error can be deduced. The z-score or l z l is useful as a quick guide to statistical significance - significance at the 5% level corresponds to l z l being 2 or more. This quick guide lacks subtlety when covariates form a structured set, such as indicator variables for increasing ischaemia time. Then interest lies not in individual coefficients or their deviation from zero, but in whether there is an orderly trend through the regression coefficients denoting stronger influence for longer ischaemia times. Alternative coding of the covariates allows such trends to be assessed formally. And the regression Z 2 statistic (see below) can be used to assess the influence of an unordered, but related, set of indicator variables such as those identifying different registries. 8.5. Comparison of regression coefficients; also of percentages Comparison of corresponding, independently estimated regression coefficients, as when the same regression model has been estimated separately for patients awaiting a first or regraft, can be approximated as follows. We borrow from Chapter 5 the (linear-logistic) regression coefficients for A10 in relation to unsensitized versus highly sensitized waiting patients. For patients awaiting a first graft the A10 coefficient is 0.09 (se = 0.13) and for regrafts is - 0 . 3 7 (se = 0.22). To check whether the two estimates are consistent with each other, we test whether the difference between them deviates significantly from zero, and may do so by formulating a z-score, which expresses the deviation from zero in standardized units. W h a t is the standard error for the difference between the regression coefficients? The answer derives from the variance of the difference being the sum of the two variances, when samples are independent. Thus: difference between regression coefficients for A10 = - 0 . 3 7 - 0 . 0 9 = - 0 . 4 6 variance of the difference ( = sum of variances) = 0.132 + 0.22 z = 0.0653 standard error of the difference ( = x/variance) x/0.0653 = 0.256 z-score = difference = - 0.46 its se 0.256 =

-

1.80

49 The z-score is not extreme (ie does not exceed 2 in modulus) and so there is no compelling evidence to reject the contention that the influence of A10 on sensitization status is the same for patients awaiting first as for regrafts, given the other covariates also in the regression model. Alternatively, a 95% confidence interval for the difference in regression coefficients runs from two standard errors below to two standard errors above the estimated difference: - 0 . 4 6 - 2 × 0.256 to - 0 . 4 6 + 2 × 0.256 ie from - 0 . 9 7 to 0.05 The 95% confidence interval straddles zero, but only just; the interval is wide and so the difference between first and regraft coefficient for A I 0 is not tightly estimated. The Scottish verdict of 'not proven' is apposite. Comparison of two percentages, such as the percentage of the 10690 patients awaiting first grafts who are blood group 0 (55%) and the percentage (44%) of the 2909 patients awaiting regrafts who are blood group 0 likewise begins with working out the standard error for the difference between the two percentages. As above, the variance of the difference, this time between percentages, is the sum of the variances provided the samples are independent. What is the variance of a percentage? The answer is in the mnemonic "success" rate × "failure" rate number in the sample where blood group 0 counts as "success", blood group non-0 as "failure". Knowing the difference between the two percentages and the standard error of that difference, we can calculate either a z-score or a 95% confidence interval for the difference in percentages. Thus: difference between blood group 0 percentages

= 55% - 44% 55 × 45

= 11%

standard error of the difference in percentages

= x/1.0785

= 1.04%

z-score ,

= difference its se

= 11 1.04 = 10.6

variance of blood group 0 percentage: 1st grafts variance of blood group 0 percentage: regrafts sum of variances

= 0.2315 10690 44x56 = = 0.8470 2909 = 0.2315 + 0.8470 = 1.0785

Alternatively, a 95% confidence interval for difference in percentages runs from: 11 - 2 x 1.04 to 11 + 2 x 1.04 ie from 9% to 13% The narrow width of the 95% confidence interval confirms that we have estimated rather precisely the difference in blood group 0 prevalence on first versus regraft waiting lists. 8.6.

Statistical reasoning: goodness of fit )~2 and regression )~

Simple or parsimonious answers, as distinct from naive ones, are recognised by a trail of reasoning which leads E I T H E R from a maze of initial complexity to the goal of end

50 simplicity OR starts off on low ground and climbs higher until a sufficiently clear view emerges. Statistical thinking guides each step, EITHER shedding a layer of complexity whenever that can be done without loss of fit to the data (see goodness of fit Z2) OR stepping up the regression ladder until there is no further significant prognostic information to be wrung from the data (see regression ;(2). 8.6.1. Goodness offit Z 2. Statistical method can be boiled down to comparison between (regression) models for the intrinsic structure underlying data. One possibility is that each model is summarized by a goodness of fit statistic, typically chi-squared (Z 2) with degrees of freedom which reflect how much structure has been imposed on the data there are fewer remaining degrees of freedom when more structure, usually in the form of regression coefficients, has been estimated. Comparing two statistical models we ask: (a) whether the simpler model fits the data and (b) whether significant explanatory value has been lost by shedding the extra structure which distinguishes the more complex from the simpler model. In answering (a) and (b) we make use of three easily memorized properties of the family of ;~2 distributions. i. the mean, or expected value, o f a ~(2 distribution with n degrees of freedom equals n, its degrees of freedom. ii. the variance ( = standard deviation squared) of a ;(2 distribution with n degrees of freedom equals 2n, twice its degrees of freedom. iii. the difference between two independent ;(2 statistics is itself a ~(2 statistic, with degrees of freedom equal to the difference in degrees of freedom between the two comparison Z2 statistics. To illustrate model comparison using goodness of fit ;(2 we borrow an example from Chapter 4, in which the difference between models D and E for waiting list composition is that model D allows the association of blood group with graft number to vary between registries whereas model E simplifies to a common association of blood group (0 versus non-0) and graft number, irrespective of registry. The goodness of fit ;t 2 for model D is 93.26 on 79 degrees of fredom, and for model E (simpler structure and so more remaining degrees of freedom) is 101.99 on 83 degrees of freedom. Question (a) asks: does model E fit the data? The answer is yes, provided that its associated goodness of fit ;(823 statistic 101.99 deviates only randomly from expectation. Answer (a) : consult ;(~3 tables and discover that the upper 10% critical value for the ;t823 distribution is 99.88, the upper 5% critical value being 105.27, so that goodness of fit of model E to the data is suspect at the 10% significance level but passable at the 5% level since 101.99 does not exceed the 5% critical value. Before answering question (b) we digress to introduce a calculation which substitutes when statistical tables are not at hand and works well enough if the ~ 2 degrees of freedom are at least five. To test whether an observed ;(2 value deviates "significantly" from its expectation, calculate how many standard deviations the observed ;(2 value is from its expectation (calculate so-called z-score): observed ;(2_ expected ~2 101.99-- 83 18.99 -

-

-

-

1 . 4 7

x/variance x/166 12.88 If the z-score exceeds 2 in magnitude, goodness of fit is disputed at the 5 % significance level at least - strictly the p-value approaches 0.025 when the degrees of freedom are sufficient for the approximation to work well. Reverting to question (b)' has significant explanatory value been lost by shedding the extra structure in model D, that is by postulating a common blood group with graft number association across registries?

51 Answer (b) : if the additional structure in model D is unnecessary then the difference in the goodness of fit ;t 2 statistics, 101.99 - 93.26 = 8.73, deviates only randomly from expectation, that is from 4, the difference between corresponding degrees of freedom, 83-79 (Property iii above). Does 8.73 significantly exceed its expectation? Consult ;~ tables to discover that 10% of the ;(~ distribution exceeds 7.78 and 5% of it lies above 9.49. The extra regression ;(2 on 4 degrees of freedom (see later: regression ~2) is not significant at the 5% level and so the simpler model E suffices. Summarizing, model E represents adequate fit (answer a) and sufficient structure (answer b). 8.6.2. Regression ;(2. Chapter 5 starts off from the ground gained in Chapter 4 and climbs higher by successively adding locus-specific homozygosity and antigen-specific terms to the regression model which distinguishes between highly sensitized and unsensitized patients awaiting renal transplantation. Successive models are compared in respect of their regression ;(2, which measures how much of the variation has been explained by the regression coefficients, the number of coefficients determining the degrees of freedom for the regression ;(2. Comparing two nested regression models - nested meaning that the explanatory variables (alias covariates alias prognostic factors alias regression variables) in the simpler model are a subset of the covariates in the extended model - we ask: (c) whether significant explanatory value has been added by including the extra covariates? The sequence of regression models in Chapter 5 for distinguishing between unsensitized and highly sensitized recipients begins with a model which features indicator variables for being female; awaiting a regraft; Eurotransplant; UK Transplant; Scandia Transplant; interactions between sex and the three registry covariates; and interactions between graft number and the three registry covariates. The above model comprises 12 indicator variables in all, for which the regression ;(2 on 12 degrees of freedom is 1824.0, very highly significant. Model 2 adds to model 1 three indicator variables (alias covariates) for A locus homozygosity; B locus homozygosity; DR locus homozygosity. The regression ;(2 for model 2 on 15 degrees of freedom is 1865.2. Question (c) asks: has significant extra explanatory value been contributed by the three locus-specific homozygosity covariates. Answer (c) : if the extra covariates are not discriminatory between highly sensitized and unsensitized recipients, then the difference in the two compared regression ~2 should deviate only randomly from its expectation, that is from 3. A random ;(~ value exceeds 16.27 with probability 1 in 1000; the observed difference, 41.2 ( = 1865.2-1824.0), between the two regression ~2 statistics far exceeds 16.27 and so is even less likely as pertaining to the g~ distribution. We conclude therefore that the extra set of three covariates contributes very highly significant explanatory value. Having established that the set of locus-specific homozygosity indicators is highly significant, we may ask whether all three indicators,for class II as well as class I, make a siginificant contribution to the regression ~2. Two solutions are approximately equivalent. EITHER investigate DR-locus homozygosity by dropping its covariate from model 2; the difference between the two regression ~2 would be Z 2 on 1 degree of freedom. OR inspect the z-scores ( = regression coefficients divided by standard error) for A, B and DR locus homozygosity in model 2; reckon that a covariate whose z-score deviates from zero by at least 2 (that is lzl exceeds 2) makes a regression contribution which is significant at the 5% level. Since lzl for DR homozygosity is only 0.04 (see Chapter 5: model 2), class II homozygosity does not influence sensitization status

52 significantly. This second approach is not advised when covariates form an ordered set such as indicator variables for increasing ischaemia t i m e - t h e n , the regression coefficients should likewise display some order, making it not sensible to draw inferences from individual z-scores. Recoding such covariates to evaluate any trend is more appropriate than crude significance testing - by either of the methods discussed in this paragraph. 8.7. For reference In Chapters 4, 5 and 7 we apply the statistical thinking and methods which have been outlined here for general reference. Individual chapters give additional detail on, or motivation for, how we tackle particular regression p r o b l e m s - counts in multi-way tables, In (odds) on being unsensitized or In relative risk of transplant failure. Goodness of fit ~(2 or regression X2 statistics or z-scores guide model choice throughout, and so examples of how to interpret these statistics have been worked through in detail in the above reference section. Confidence interval estimation is preferred to significance testing because the width of a confidence interval informs us about precision (or lack of it) in estimation; the location of the confidence interval (straddling zero or not) reveals statistical significance.

3. Causes

I. Introduction The percentage reaction frequency ( % RF) of a patient's serum is an estimate of the proportion of kidney donors who would react positively in a crossmatch test. The accuracy of this estimate depends on the composition of the test panel and on a number of technical variables. Sequentially tested sera reveal fluctuations in the °/ORF. These result from changes in the antigenic repertoire of alloantibodies. Expansion of the antigenic repertoire to include larger numbers of antigens gives higher % R F and a narrowing of the range of antigen specificities gives a lower °/ORF. In this study the practice of monitoring sensitization was compared between six laboratories throughout Europe. In order to achieve comparability complex clinical charts were reduced to simplified sets of symbols. Thereafter sensitization profiles were related to immunizing events.

2. Plan of study The method of collection of serological profiles from six laboratories is described in 2.5.1. Records spanned a 78 month period from January 1980 to June 1986. The size and type of cell panel (U, for unseparated T or B for separated lymphocytes) was recorded as was the sequence of immunizing events. In the analysis, centre codes were used in order to facilitate objective discussion. Profiles were analysed for features that corresponded to spikes, plateaux and niveaux as defined in Table 3.1. An immunizing event was recorded as occurring before a feature if it took place within the six month interval prior to the first point defining that feature, ie in the case of a spike or a plateau, the first point showing a 30% rise. All blood transfusions, single or multiple, occurring in six months were considered as a single immunizing event. An event was recorded as occurring during the feature if it occurred between the first and last points defining that feature. Where the serological record contained less than

54 Table 3.1. Definition of spike, plateau and niveau Feature*

Test panel size

Increment in % R F

Decrement in % R F

Duration (M)

Point estimates of % R F

Spike

< 50 >~50 < 50 >~50 < 50 ~>50

~>30 ~>20 ~>30 ~>20 < 30 20 ~>15 < 20 3 ~>3

Plateau Niveau

* Each feature was enclosed in a twelve m o n t h window which ended on the last point defining that feature.

three points during a twelve month period no feature was recorded. The features can be best appreciated by overlaying a perspex window onto the chart and shifting it from left to right across the chart. The twelve month span enclosing a feature was defined in retrospect from its last plotted point.

3. Characterization of the data

Of the 232 charts submitted 62 were considered eligible for study. The reasons for ineligibility were; fewer than four points during a 12 month span; a charted peak of less than 50%; incomplete blood transfusion history; incomplete transplant failure history; and incomplete history of reaction frequency. Of the 62 eligible charts 43 were from highly sensitized patients (Table 3.2). Further characterization is contained in Table 3.3. Only one profile was obtained from a patient who had never been transfused (D11); 18 patients had neither been grafted before the study period nor received a transplant during the study period; 29 had received a transplant before the study period; 12 received a transplant during the study period; 3 received two transplants, one before and one during the study period. All 50 acceptable B cell charts were obtained after testing with platelet absorbed sera.

4. Variations in laboratory practices

These are summarized in Table 3.4. In 19% of profiles the panel size for estimating % R F changed radically (eg 15-20 cells or more). Intervals between point estimates were sometimes too long to give a continuous profile: for example in 45% of cases there were at least six consecutive months with no point charted.

55 Table 3,2. Charts received: eligible charts and rejected patients

Centre (typical panel size)

No. of patients received

Total

A

13

5

B

4

3

C D E

31 35 30

F G

30 89

TOTAL 1 2 3 4

28 26 selected ~ charts

Charted peak > 8 0 % RF

Acceptable B cell chart

Grafted prior to 1980

3 2 20 18

0 0 24 26

1 1 13 17

43

50

32

04

selected2,3 charts

232

Incomplete Incomplete Incomplete Incomplete

ELIGIBLE CHARTS

62

blood transfusion history graft history transplant failure history R F history

Table 3.3. Eligible patients: sex, parity, blood transfusions and graft history

Centre Male

Sex and parity Female

Nullips

A B C D TOTAL

3 2 14 13

Parous

Blood charted

?*

Yes

No

1 1 4

5 2 27 14

1 1 11

15

6

48

2 6 3 32

* Parity unknown.

7 6 9

Never trans.

Graft history: Pre/post 1980 PRE 1980: Yes Yes No No POST 1980: Yes No Yes No

1 1

3 1

1 1

1

12 15

7 1

8 8

13

3

29

1218

56 Table 3.4.

Variation in laboratory procedure

1. Change in panel size (within patient) 2. At least 6 consecutive months with no RF charted 3. At least 2 consecutive months after blood transfusion with no RF charted 4. Consecutivereaction frequencies separated by transplant failure, with testing interval at least 6 clear months

12/62 patients

19%

28/62 patients

45%

10/48 patients

21%

6/25* patients

24%

* Approximate number of distinct transplants and failures.

This occurred in 24% of patients between the date of a transplant and the date of its failure. At least two months elapsed after a blood transfusion with no point charted in 21% of patients.

5. Modal patterns of response

Selected individual profiles are charted in Figs. 3.1 to 3.6 and appropriate summaries are given in code below each chart. A collective summary of patterns obtained with all of the charts is illustrated in Fig. 3.7 and is summarised more simplistically in Table 3.5a for T or U cell profiles, and in Table 3.5b for B cell profiles. The selected profiles included only patients whose peak % R F exceeded 50% with the exception of C28 (Fig. 3.6) whose B cell profile alone exceeded 50%. All selected profiles were classified as highly sensitized by virtue of having % R F above 80%, with the exception of C28 (highly sensitized against B cells but not T cells) and C13 (Fig. 3.2). Fig. 3.1 portrays two multi-transfused male patients who had not been previously grafted.Note the sporadic spikes associated with blood transfusions. In Fig. 3.2 a previously ungrafted nulliparous female patient is shown (C13) responding sporadically against both T and B cell panels with a spiking pattern; note the independence of the T from the B cell pattern. In the lower half of this figure a nulliparous female (CO2) who had previously rejected a transplant is shown responding to multiple transfusions with a declining response pattern. Fig. 3.3 shows an example (D1 l) of gradually ascending % R F following failure of a six year old transplant ( F occurred at one month). No blood transfusions were reported to have been given to this patient. In the lower panel

57 Table 3.5. Patterns: spike, plateau, niveau (a) unseparated lymphocytes and T cells Pattern* ALL patients

Grafted before 1980

Not grafted before 1980

S.. SP. S.N SPN

9 1 29 7

3 1 12 4

6 0 17 3

... .P. ..N .PN

0 1 7 8

0 0 6 6

0 1 1 2

Totals

62

32

30

(b) B cells Pattern

ALL patients

Grafted before 1980

Not grafted before 1980

S.. SP. S.N SPN

6 1 12 5

3 1 5 5

3 0 7 0

0 1

0 1

0 0

... .P. •. N

.PN Totals

22

11

I1

3

2

1

50

28

22

* S = Spike, P = Plateau, N = Niveau,. = Absence of spike, plateau or niveau.

is a patient (C010) who responded to multiple transfusions with successively lower %RF only to be followed by a series of multiple spikes. This patient had rejected his first transplant in 1978. Figs 3.4, 3.5 and 3.6 show different patterns of responses associated with transplants. In Fig 3.4 two first transplants (C05 and C23) were followed after rejection by a high plateau. In both cases these were accompanied by multiple blood transfusions.In C23 it was remarkable that the response to B cells remained so low (40-50%RF). In Fig 3.5 a multiparous female patient (C17) is shown rejecting a first transplant that had been placed as long ago as 1974. Rejection was heralded by fluctuating anti-B cell activity and a high spike of T cell activity. Note that no blood transfusions preceded this spike. The patient in the lower panel D24 was a multiparous female regraft; she received her transplant whilst the %RF was

58 well above 50%. The level showed little change until after graft rejection at month 52, thereafter it rose steadily to 100%. B cell responses after graft failure showed a series of declining spikes followed by ascending spikes. Fig 3.6 shows a multiparous female (C08)rejecting a first transplant. She had only low levels of %RF after graft failure despite multiple transfusions. In the lower panel C28 is offered as an example of a multiparous female regrafted patient who, after rejection, became only modestly sensitized to T cells, but highly sensitized to B cells. These examples illustrate the protean nature of the responses to alloantigens accompanying immunizing events. It will be noted that spike followed by niveau was the commonest pattern seen with unseparated cells and a simple niveau, usually below 30%RF, typified many B cell patterns (Tables 3.5a and 3.5b).

6. Concordance of B and T patterns with time

The question here was whether or not responsiveness to B cells could be assumed from a knowledge of the anti-T cell reactivity. We wished to know whether B and T cell patterns were concordant. The summary in Fig. 3.7 shows, almost without exception, complete temporal discordance between the T cell profiles and B cell profiles.

7. Responsiveness to blood transfusions

Blood elicited individual response patterns in different patients. Some individuals gave repeated spikes to single transfusions whereas others gave neither spike nor plateau with multiple transfusions and yet others gave sporadic responses. Based on a majority response against three or more consecutive transfusions, four patients could be said to be responders (A01, C10, C11, C18); and by the same criteria five were non-responders (C2, C12, C13, C14, C25); of the remainder 12 were equivocal and the rest were unclassifiable. Overall there was insufficient data available to identify a pattern typically associated with transfusion. Although the most common pattern was no response at all (low niveau). No evidence was obtained to support the view that a spike pattern typified a blood transfusion since in some cases the transfusion was followed by a high niveau, and in other cases transfusion progressed to frank and rapidly rising levels above 80%. In short responsiveness to blood was sporadic and almost completely unpredictable.

59 8. Profile with former failed transplants

Patients who had lost a transplant prior to the study period (before January 1980) were significantly more likely to exhibit a niveaux profile against unseparated or separated T lymphocytes than patients who had not had a failed transplant prior to that period (Table 3.5). 9. Discussion

Each profile consists of an accumulation of alloantibody responses directed to a variety of HLA and non-HLA targets. Each HLA target constitutes several public, private, split or interlocus epitopes. For example the phenotype defined according to private specificities HLA-A2; B 12 and 17; might include the splits, B44 and B57; the public Bw4, and the interlocus antigen, A2-B17. The %RF is determined by the frequencies of these targets within the test population. It is also determined by the constellation of targets represented within the serum. Synergistic effects might occur between weak antibodies directed to separate specificities. The effect of blood transfusion on this profile might be severalfold: it may elicit an alloantibody response de novo; it may reactivate former alloimmunity, as an anamnestic response; it may function as a non-specific polyclonal B cell activator stimulating all cells primed for alloantibody production; it may add antibodies passively in the donated plasma; alternatively, antibody producing B cells may be transfused, that continue to secrete alloantibody into the patient's serum until they are finally eliminated. By contrast, blood components may absorb low titre antibodies causing a transient fall in the %RF. Repeated transfusions are sometimes associated with an inexplicable and gradually declining %RF over a long period of time. Typical examples of such slow decay are given in Fig 3.2 (C02) and 3.3 (C10). From this survey we expected to find typical profiles that followed certain immunizing events; none were found. An exception perhaps was that failed transplants were more often followed by plateau or high niveau than nontransplanted individuals (Table 3.5). I0. Conclusions

Sensitization was poorly monitored in the majority of laboratories. Information relating to crucial immunizing events such as failure of transplants or times of transfusions was lacking. There were long gaps in the monitoring sequence during which important events may have passed unrecognised (e.g., transient spikes).

60 Highly sensitized patients constitute a heterogeneous collection. The natural history of serological profiles is but one aspect of this heterogeneity. In the absence of discernible modal patterns relating to different immunizing events no distinction can be made between the sequence of these events. We have no alternative but to continue with our initial definition of high sensitization based on purely pragmatic and arbitrarily chosen level of reaction frequency of over 80%.

61

100-

80-

8

'~ 4 0 -

20-

0 BLOOD ] TRANSFUSIONTII

...... I 2O I IIII II

"]" 4O

¸..L I

Months

I

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112

(3,0 %

SUMMARY: B~

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0

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I

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Mo~ths

60

BI-OOD l

TRANSFUSIONT/I ....

I

III I

~-~

C12

SUMMARY: B~

I

I

l] r~ ....~,30% "1j ~,."'~,.~ B ~

112

~x~N~

Figure 3.1. T w o multi-transfused male patients, not previously grafted: sporadic spikes associated with blood transfusion - -

T cells, - - -

B cells.

62

100--

80--

I I I I I I I I I I

~ 60-

'~ 40-~, m..

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I 1 I

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60

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SUMMARY:B/

100

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211

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40 II

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Mo~rths

I

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)3o~ B ~ E-~-~ : E~-~ __~-~

B

IIIIIII

:

222

Figure 3.2. T w o multiparous female patients, C13 previously ungrafted and C02 previous grafted failure. - -

T cells, - - -

B cells.

100-

'~., - g

~m

~.r', .Jid, I Ik,,lll~.'h2.

63

~

!!

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SUMMARY: B

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122

~ ~ ~ ~ ~ B

B

>50%

>30%

Figure 3.3. Two male patients with failed graft: respectively ascending and descending spiked %RF. T cells, - - - B cells.

64

100 -

80-

'60-

'~ 40-

20-

(::05

0 BLOOD I TRANSFUSIONT{I

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SUMMARY: (T)

(v)

212

~-~%~

Figure 3.4. Two first transplants: high plateau a n d multiple blood transfusions after rejection. --

T ceils, - - -

B ceils.

100

65

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SUMMARY: B,

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Figure 3.5. Rejection: heralded by anti-B cell activity (C17) or followed by ascending % R F and B cell responses (C24) in multiparous females. ~

T ~lls, - - -

B cells.

66 100

-

80-

~

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72 10

PATIENT I.D.

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.

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73 PATIENT

10

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422 .~30%

212

D31 >80%

r__-_~___]' ~g = O, I o r 2 m i s m a t c h e s

Figure 7.1. Different coding schemes for HLA-mismatches.

highly sensitized a n d c o n t r o l recipients ( H C B E ) , p e r m i t sex to have a different influence ( n o t p r o v e n ) on t r a n s p l a n t survival in highly sensitized a n d c o n t r o l recipients ( H C M F ) , a n d a m o n g s t regrafts allow there to be a different p r o g n o s tic influence ( n o t p r o v e n ) a s s o c i a t e d with high sensitization a c c o r d i n g to

173 whether the previous graft failed within 3 months or not (HCP2). A fourth interaction, defined a posteriori, considered whether the improvement in graft survival in later transplant years was different between highly sensitized and control recipients (HCYR). 4.4. Testing interactions or differences between corresponding regression coefficients Besides the formal testing of specific interactions, as above, fitting regression models for transplant survival separately for highly sensitized and control recipients, or for first versus regrafts, constitutes weak (in virtue of the limited number of transplant failures) tests of generalized interaction whereby all covariates are allowed to have a different influence on transplant survival depending upon whether the recipient is highly sensitized or control, first or regraft. How, informally, do we compare corresponding regression coefficients - for example, for ischaemia time in highly sensitized versus control grafts? Answer: the difference between corresponding regression coefficients is assessed by computing an approximate 95% confidence interval (see Chapter 2), which runs from two standard errors below to two standard errors above the observed difference. For ischaemia time we compute: (isch.coeffHs -- isch. c o e f f c o n t r o l )

=

observed difference in regression coeff.

variance of the difference ( = sum of variances) = isch.seZns+isch.se~2ontro~ standard error of difference ( = x/variance)

= x/(isch.se~s q- isch.sec2ontro~)

95% confidence interval runs from: observed difference - 2 . s t a n d a r d error of difference to : observed difference + 2.standard error of difference ie (isch.coeffrts - isch.coeff~ontrol)+ 2*x/(isch.se~s + isch.se~o.t~o~) Remember that the observed difference between corresponding regression coefficients is an estimate only, and always qualified by a standard error. Regression coefficient divided by its standard error gives the z-score (see Chapter 2). Disparate z-scores, the one statistically significant the other not, may deceive us into believing that some clinically relevant phenomenon, rather than random variation, underlies the disparity. Formal tests of interaction, ie comparison of corresponding regression coefficients, are a necessary, but not sufficient, guard

174

against that deception. Other considerations include: 1) whether the subgroups were of prior interest to the investigators, 2) whether the subgroups were discovered by exploratory analysis and 3) whether there is corroboration from independent data sources.

5. Transplant survival: results

Graft failure or death with a functioning graft constitutes failure of the transplant. Table 7.2 summarizes transplant survival for highly sensitized versus control recipients o f first or regrafts. Sixty-eight percent o f highly sensitized first grafts ( n = 6 3 8 ) survive to one year c o m p a r e d to 77% one year survival for control first grafts (n = 653). Corresponding transplant survival rates at one year for regrafts (see Figure 7.2) are 59% and 74% in highly sensitized ( n = 527) and control recipients ( n = 4 3 9 ) . The relative risk o f transplant failure in the first week (regrafts) or two weeks (first grafts) post-transplant (see Figure 7.3) is doubled in highly sensitized versus control grafts. F o r example, 11% o f highly sensitized first grafts failed in the first two weeks post-transplant c o m p a r e d to 6% o f first graft controls. There is accelerated failure o f regrafts with 14% o f highly sensitized regrafts and 7% o f control regrafts failing in the first week post-transplant, equalling the two-week failure rates for first grafts. Table 7,2. Summary survival statistics

1st grafts

HS n=638

Control n=653

% Tx surviving at 3 months 1 year 3 years

76% 68% 58%

86% 77% 68%

% Tx failing on or before day 3 % Tx failing on or before day 8 % Tx failing on or before day 15

4% 8% 11%

3% 4% 6%

Regrafts

Control n=439

HS n= 527

% Tx surviving at 3 months 1 year 3 years

70% 59% 54%

82% 74% 65%

% Tx failing on or before day 3 % Tx failing on or before day 8 % Tx failing on or before day 15

11% 14% 18%

4% 7% 9%

Tx day = day 1

175 COUNCIL OF EUROPE : HS v CONTROL 100'

80>

1st GRAFTS 653 controls

=>60-

638 highly sensitized

n- 4 0 =~ 20-

0 o

0

200

400

600

800

1000

DAYS SINCE TRANSPLANTATION

COUNCIL OF EUROPE : HSv CONTROL lOO

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REGRAFTS 439 controls 527 highly sensitized

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200 400 600 800 1000 DAYS SINCE TRANSPLANTATION

Figure 7.2. Transp]ant survival

176

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177

5.1. Time dependent penalty associated with high sensitization From Table 7.3 (for first grafts and regrafts respectively) we see in the coefficients for HSC (highly sensitized versus BASELINE = control) very significant In relative risks associated with high sensitization in the first week or two weeks post-transplant and continuing up to 3 months. In the third epoch from 101 days onwards the risk associated with high sensitization has dissipated. Figure 7.3 illustrates these finding in terms of relative risks of transplant failure, quoting for the second and third post-transplant epochs 95% confidence intervals for the risk of transplant failure in highly sensitized versus control recipients. Figure 7.3 also shows how closely the ratio of transplant failure rates in the first epoch (ratio=2) agrees with exponentiating the In relative risks estimated in the corresponding regression model: for regrafts In relative risk is 0.7, the exponential of which is 2. This link to the familiar reminds us of the simple notion which underlies piece-wise proportionality of risks. Table 7.4 summarizes for ALL grafts the transient nature of the increased risk in highly sensitized patients; the regression coefficient associated with high sensitization is.59 in the first 3 months (standard error = .09) and reduces to. 11 thereafter (95% confidence interval for the In relative risk regression coefficient from 3 months onwards being from -0.12 to ÷ 0.34). Figure 7.4 illustrates the foregoing In relative risks for ALL grafts; also shown in three distinct post-transplant epochs, separately for first and regrafts, are the natural logarithms of the relative risks given in Figure 7.3. Figure 7.4 conforms to the format which will be used to illustrate results in section 5.2 on model building. Notice that the scale is In relative risk; that the upper diagram (usually ALL grafts) identifies the BASELINE category which applies also in subset diagrams (for example, first versus regraft); that In relative risks which differ from zero ( = BASELINE In relative risk) at the 5% significance level are shown as shaded bars; standard errors are not plotted but can be derived from tabulated In relative risks and z-scores (see Chapter 2). 5.2. Model building: additions to background covariates In the following subsections different covariates are explored individually against a background which at least takes account of high sensitization, year of transplant (as indicator variables) and recipient sex, and may include other covariates also. Each table identifies the background covariates to which a new explanatory variable is being added. If the additional regression ~2 exceeds its 5% or 1% critical value then the exploratory analysis has identified a potential prognostic factor which in sections 5.3 and 5.4 is fitted jointly with the full set of other prognostic factors to judge its contribution multifactorially to the risk score for transplant survival: overall and in distinct epochs.

178

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• Total A+B+DR mismatches MM27 27 varieties of mismatch • ~e - 0.2 • se - 0.3 ~ se- 0.4 H S C : H i g h l y Sensitized versus C o n t r o l ] T R Y R : Year of transplant "| a c c o u n t e d for J

Figure 7.8. A + B + DR mismatches and 27 varieties of HLA-mismatch: ALL grafts. Antigen sharing. Numbers of shared antigens between donor and recipient on the three loci A, B, D R have been analysed as fully as antigen mismatches but, because antigen sharing is less insightful than antigen mismatches, Tables 7.3 to 7.5 condense the alternative analyses to the 27 varieties of antigen sharing (SH27) for ALL grafts and the entire follow-up interval (see Table 7.4); and, by epoch, (see Tables 7.3 to 7.5) to indicator variables for the number of shared antigens across loci (SHS). Typically the number of shared antigens (SHS) has a lower Z 2 than is associated with the number of mismatched antigens (MMS), except in respect of regrafts or highly sensitized recipients. For ALL grafts (see Table 7.4), the 27 varieties of antigen sharing contribute a Z 2 of 35.05 on 26 degrees of freedom whereas the 27 varieties of mismatch account for a higher Z2 of 53.84, also on 26 degrees of freedom.

190 RISK OF HIGH

•

SENSITIZATION

WITH

TIME

1.0EPOCH 0-101

P -~ ~

[--1 552

0

"

323

.J

[

I I 366

I - - ] , Baseline =15 hours or less 391 219

406

Number of patients

-0', 1st GRAFTS

REGRAFTS

1.0-

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HOURS 0"5 I

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157

259

163

171

130

Number of grafts

-05 HSC : Highly Sensitized versus C o n t r o l ~ accounted for T R Y R : Year o f transplant H L A - matching

Figure 7.12a. IschaemiaTime(hours).

86

196

•

1'0"

p 1985 FEMM: female BENE: non-beneficially matched * for regrafts for 1st grafts

(b) proportional hazards (REGS)

plus PRE2,WAIT,MMDR,ISC1,CYA plus BENE

Table 7.18. Duration of previous graft Model comparison

Regrafts

(a) HSC,TRYR,FEMM,BEN6,PRE6 versus (b) HSC,TRYR,FEMM,BEN6,PRE2

Z~=3.03

From model (b)

coeff,

z-score

PRE~

-0.04 0.04 0.13 -0.18 0.44

-0.19 0.21 0.72 -0.92 - 2.60

8 15 days 1 6 40 days 41-100days 101-365 days 366+ days

-

207

Table 7.19. Regrafts: wait from previous graft failure to regrafting Model comparison:

Regrafts

Background HSC,TRYR,FEMM,BEN6,PRE2,CYA,ISCH In addition

total ~2

df

coeff.

Izlscore

(a) WAIT: per 5 yrs

86.95

15

0.22

1.93

91.74

19 -0.02 0.12 0.08 -0.09 0.43

0.12 0.67 0.40 0.39 2.39

or

(b) IWAIT: I-2 yrs 2-3 yrs 3-4 yrs ,~5 yrs > 5 yrs

substitutes indicator variables for successive years of waiting up to the fifth does not justify abandoning simple linearity (WAIT) in so unobvious a covariate. 5.3. Preferred coding for I~LA-mismatches: model preference amalgamating other covariates The various insights, apart from tissue matching, which we have built up in the previous section are amalgamated into a multifactorial background for our choosing between rival schemes for coding H L A mismatches. The front runners (ALL grafts) from subsection 5.2. l, when few other covariates were considered, were number of D R mismatches (MMDR), beneficial matching (BEN4), beneficial/DR matching (BEN6) and total number of mismatches (MMS). We also review MBDR, that is the number of B + D R mismatches. The chosen epoch is l-1600 days giving maximum failures. Back-reference should be made to subsection 5.2.1 where coding schemes were compared against a simpler background but in two distinct epochs post-transplant (up to 3 months and thereafter). Separately for first versus regrafts (see Table 7.20), for ALL grafts without and with restriction to fully typed recipients as well as donors (see Table 7.21), and for highly sensitized versus control grafts (see Table 7.22) we compare likelihood ratios or regression X2 for five models which differ only in how H L A mismatches are coded. Model (c), which invokes beneficial/DR matching (BEN6), is reported in detail; for the others - that is, model (a) beneficial matching (BEN4); (b) D R mismatches ( M M D R ) ; (d) B-t-DR mismatches (MBDR) and (e) total A + B + D R mismatches (MMS) - w e document only the In relative risks for HLA-mismatching. This economy is permissible because no matter how we code HLA-mismatches the regression coefficients for other covariates are essentially undisturbed.

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Previous graft

8-15 days; 16-40 days; 41-100 days; 101-365 days; 366 4- days) PRE2

I

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fail interval of previous graft (0-100 days; 1014- days) INTERACTION: HSC x PRE2 (rest;

HS and previous fail time 1014- days) linear regression on waiting time for regraft: from previous failure to index graft (months) waiting interval for regraft ( < 1 yr;

l-2yrs; 2-3yrs; 3-4yrs; 4--5yrs; > 5yrs) Recipient sex FEMM PREG

I I

male versus female pregnancy/male (female, pregnancy NO;

f, pregnancy YES; f, pregnancy NK; male) Other covariates BCEL J UTCL l CYA DAY1 AGEO 2 DIAB

I I I I I I

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* Type I = indicator variables L = linear regression on continuous covariate T = linear trend on ordered categories t restricted to non-Eurotransplant recipients 2 restricted to adults; and age not recorded included as 31-50 years

8. Distinct Post-Transplant Course for Highly Sensitized Recipients? (Kalman Filter Monitoring)*

1. Introduction

Early in 1984, UK Transplant Service (UKTS) initiated its multi-centre 'Save our Sensitized (SOS)' scheme (see Chapter 9) to reduce the accumulation of highly sensitized patients on the UK renal transplant waiting list. Sera with more than 85% reaction frequency against the national reference panel were selected for distribution in Terasaki trays to make up what was called the "SOS serum set". Under the scheme, donor kidneys that were crossmatch negative with both plated ('peak') and 'current' sera (tested pre-operatively) were transplanted. No mismatches of former grafts were repeated, but transplants were otherwise performed irrespective of HLA mismatches. To answer the question: is the post-transplant course for highly sensitized patients distinct from that of other recipients, the UKTS Management Committee proposed a prospective study of SOS and matched control recipients in which post-transplant course would be recorded daily until discharge, dates of onset of subsequent rejection episodes would be reported, and immunological and genetic data would be provided. Appropriate forms (see Chapter 2) were designed by the UKTS Management Committee and piloted in a retrospective study of highly sensitized(SOS)/ matched control pairs. Collaborating centres were those represented on the UKTS Management Committee. We also report a subsequent validation exercise in the same centres plus Bristol.

2. Study method and Kalman filter

Seven centres completed retrospectively the specially designed records for their highly sensitized patients who had been transplanted under the UKTS SOS * Co-authors: K. Gordon & A. F. M. S. Smith, Department of Mathematics, Nottingham University.

254 Table 8.1. Fifteen SOS/Control pilot pairs SOS or control

Graft number

Cyclosporin

1 2 3 4 5 6 7 8

S

1 1 1 2 1 1 2 2

Y Y Y Y no data Y Y Y

F F M M

9 10 11 12

S

C

1 1 2 2

N N N N

10 10 84 20 02 85

F F

13 14

S C

3 3

Y Y

04 24 13 28

05 05 11 11

84 84 84 84

F F M M

15 16 17 18

S

1 1 1 1

Y Y Y Y

03 04 03 25 23 28

05 05 11 11 08 08

84 84 84 84 84 84*

M M F F F F

19 20 21 22 23 24

S

C

2 2 3 3 1 1

Y N Y Y N N

08 03 84 03 08 84

F F

25 26

S C

1 1

Y Y

19 19 20 28

F F M M

27 28 29 30

S

1 3 3 3

N Y Y Y

Centre

Date of index transplant dd mm yy

Sex

2

20 19 29 26 03 08 24 29

07 08 07 08 I1 11 11 11

84 84 84 84 84 84 84 84

M M M M F F M M

11 22 15 13

03 03 03 04

84 84 84 84

3

5

8

10

19

25

02 02 08 08

84 84 84 84*

Patient

C S C S C S C

C S

C S C

C S C S

C S

C

* Registered with UKTS as having more than 50% reactive antibody.

scheme and for matched control patients. Control patients were matched for centre, sex, graft number matched, and next recipient on UKTS records. The pilot study included 15 SOS/control pairs. A further 23 SOS/control pairs transplanted up to January 1986 in Management Committee centres and in Bristol were collected coincidentally through the Council of Europe Study.

255 Table 8.1. (continued) Kidney function: onset day

Reciprocal creatinine Grumbling or Upward slope

OUTCOME: DAYS POST-TRANSPLANT

-

G G

10 0 -

G

-

G

6

9 3

G G

49

I

G

Rejection therapy

I F

G

13

G

10

U U

6 8

1

U

11

0 0 0 0

U U

no data 0 0 no data no data 0

U U U U U G G G G

0 23 19

G G

1

F

0

F

10

29 37 11

I

*

D

**

U

9 2, 17

U

5

22 20 18 17 _

_

12 11 30 21

2, 17, 23, 28 6

9 4,8 19 no data 6

_

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2

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0

5 4

3, 9

U no data

0 9 0

Discharge

F Failure (non-immun.) I Immunological failure D Death

I

***

F

1

11 14 14 28 29 27 62 20 16 24 27 23

* Immunological failure at 5 months. ** Patient died at 2 months. *** Immunological failure at 3 months.

Serum creatinine, recorded daily from the day of transplant until discharge, was taken as the marker of post-transplant events and used for the statistical identification of rejection. The methodology (Kalman filter) exploits the fact that renal function, expressed as reciprocal serum creatinine, behaves as a series of approximately linear trends, whose direction (i.e. slope) changes as function

256 moves from improvement to deterioration. Other changes in renal function are induced by external events such as dialysis, which alters creatinine level, and rogue laboratory measurements, which result in transient changes, both of which the Kalman filter has been designed to 'filter' out analytically so that instabilitY in the series does not obscure salient slope changes indicative of rejection. The Kalman filter identification of rejection episodes is compared with the date of clinical intervention to increase immunosuppression. Weightcorrected reciprocal creatinine corrects for distortion of serum creatinine induced by changes of hydration and was analysed whenever possible in preference to unadjusted reciprocal creatinine.

3. Pilot study results

3.1. Design and data quality Two design problems were identified. Graft number matching failed in two pilot study pairs, whether by reason of carelessness, error in UKTS records or misreporting by centres, with the result that two first transplant SOS patients were paired with retransplant control recipients. We also failed in the pilot study (rectified at validation: see later) to exclude as potential control transplants other sensitized recipients with more than 50% reactive antibody against local panels. Table 8.1 documents the 15 SOS/control pilot pairs: three of the 15 control patients were registered with UKTS as having more than 50% reactive antibody. Nine of the 15 SOS patients received a first transplant and 21 of the 30 transplantees were given Cyclosporin. Missing data were few in respect of serum creatinine and immunosuppression; weight was less well documented because not all centres weigh recipients daily. Serum creatinine was taken as the marker of post-transplant events, because it is a generally accepted criterion and because Kalman filter analysis of (weight-corrected) reciprocal serum creatinine has been shown in one centre to be a successful monitor of rejection episodes in renal transplantation (Knapp M S et al, 1983).

3.2. Distinct post-transplant course for SOS patients: "grumbling start" Figure 8.1 shows the time series of reciprocal creatinine ( x 1000) for two SOS/ control pairs (A and B) from a single centre. Notice that as serum creatinine decreases from 500 to 200, reciprocal creatinine ( x 1000) increases from 1000/ 500 = 2 to 1000/200 = 5; thus increasing reciprocal creatinine is good for the patient. In Figure 8.1, both highly sensitized patients have a grumbling start to their creatinine profile, whereas reciprocal creatinine is increasing from the

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