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Library of Congress Cataloging‐in‐Publication Data
Names: Riley, Richard D., editor. | Tierney, Jayne F., editor. | Stewart, Lesley A., editor.
Title: Individual participant data meta-analysis : a handbook for healthcare research / edited by Richard D. Riley, Jayne F. Tierney, Lesley A. Stewart.
Other titles: Statistics in practice.
Description: Hoboken, NJ : Wiley, 2021. | Series: Wiley series in statistics in practice | Includes bibliographical references and index. | Contents: Individual Participant Data Meta‐Analysis for Healthcare Research / Richard D. Riley, Lesley A. Stewart, Jayne F. Tierney – Rationale for Embarking on an IPD Meta-Analysis Project / Jayne F. Tierney, Richard D. Riley, Catrin Tudur Smith, Mike Clarke, and Lesley A. Stewart – Planning and Initiating an IPD Meta-Analysis Project / Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney – Running an IPD Meta-Analysis Project : From Developing the Protocol to Preparing Data for Metaanalysis / Jayne F. Tierney, Richard D. Riley, Larysa H.M. Rydzewska, and Lesley A. Stewart – The Two-stage Approach to IPD Meta-Analysis / Richard D. Riley, Thomas P.A. Debray, Tim P. Morris, and Dan Jackson – The One-stage Approach to IPD Meta-Analysis / Richard D. Riley and Thomas P.A. Debray – Using IPD Meta-Analysis to Examine Interactions between Treatment Effect and Participant-level Covariates / Richard D. Riley and David J. Fisher – One-stage versus Two-stage Approach to IPD Meta-Analysis : Differences and Recommendations / Richard D. Riley, Danielle L. Burke, and Tim Morris – Examining the Potential for Bias in IPD Meta-Analysis Results / Richard D. Riley, Jayne F. Tierney, and Lesley A. Stewart – Reporting and Dissemination of IPD Meta-Analyses / Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney – A Tool for the Critical Appraisal of IPD Meta-Analysis Projects (CheckMAP) / Jayne F. Tierney, Lesley A. Stewart, Claire L. Vale, and Richard D. Riley – Power Calculations for Planning an IPD Meta-Analysis / Richard D. Riley and Joie Ensor – Multivariate Meta-Analysis Using IPD / Richard D. Riley, Dan Jackson, and Ian R. White – Network Meta-Analysis Using IPD / Richard D. Riley, David M Phillippo, and Sofia Dias – IPD Meta-Analysis for Test Accuracy Research / Richard D. Riley, Brooke Levis, and Yemisi Takwoingi – IPD Meta-Analysis for Prognostic Factor Research / Richard D. Riley, Karel G.M. Moons, and Thomas P.A. Debray – IPD Meta-Analysis for Clinical Prediction Model Research / Richard D. Riley, Kym I.E. Snell, Laure Wynants, Valentijn M.T. de Jong, Karel G.M. Moons, and Thomas P.A. Debray – Dealing with Missing Data in an IPD Meta-Analysis / Thomas P.A. Debray, Kym I.E. Snell, Matteo Quartagno, Shahab Jolani, Karel G.M. Moons, and Richard D. Riley.
Identifiers: LCCN 2021000638 (print) | LCCN 2021000639 (ebook) | ISBN 9781119333722 (cloth) | ISBN 9781119333760 (adobe pdf) | ISBN 9781119333753 (epub) | ISBN 9781119333784 (oBook)
Subjects: MESH: Meta-Analysis as Topic | Data Interpretation, Statistical | Models, Statistical | Randomized Controlled Trials as Topic
Classification: LCC R853.S7 (print) | LCC R853.S7 (ebook) | NLM WA 950 | DDC 610.72/7–dc23
LC record available at https://lccn.loc.gov/2021000638 LC ebook record available at https://lccn.loc.gov/2021000639
Cover Design: Wiley
Cover Image: © Zaie/Shutterstock
To Lorna, Sebastian and ImogenTo Phil and EllieTo Simon, Catriona and Kirstin
Acknowledgements
The Editors would like to acknowledge the support of their colleagues in their host institutions and departments: the School of Medicine, Keele University; the Centre for Reviews and Dissemination, University of York; and the MRC Clinical Trials Unit at University College London. Particular thanks to Lucinda Archer, John Allotey, Sarah Burdett, Thomas Debray, Miriam Hattle, Mel Holden, Carl Moons, Max Parmar, Bob Phillips, Larysa Rydewska, Mark Simmonds, Kym Snell, Shakila Thangaratinam, and Claire Vale, who have worked with us on many of our applied IPD meta‐analysis projects, and to Danielle Burke and Joie Ensor for organising the Statistical Methods for IPD Meta‐Analysis course at Keele. We are particularly grateful to Mike Clarke who has shared the IPD journey from the start and has contributed so much to the field. We also recognise the contributions by the convenors and other members of the Cochrane IPD Meta‐Analysis Methods Group over many years, and acknowledge stimulating discussions with participants at our various workshops and training courses. We thank our colleagues and research collaborators on the various applied and methodological IPD meta‐analysis projects we have been involved in, many of which formed motivating examples and case studies in the book chapters. In particular, we are indebted to the participants in the various trials and studies, and the associated investigators, without whom IPD meta‐analysis projects would not be possible.
1 Individual Participant Data Meta‐Analysis for Healthcare Research
Richard D. Riley, Lesley A. Stewart, and Jayne F. Tierney
1.1 Introduction
Healthcare and clinical decision‐making should be guided by the evidence arising from high‐quality research studies. Often a single study is insufficient to make firm recommendations, and so multiple studies are conducted to address the same research question. This motivates the need for evidence synthesis: the combination of data from multiple studies to provide an overall summary of current knowledge. For example, when multiple randomised trials have examined the effect of a particular treatment, evidence syntheses are needed to combine and summarise the information from these trials, in order to establish whether the treatment is effective or not.
Systematic reviews are the cornerstone of evidence synthesis and evidence‐based decision‐making in healthcare. They use transparent methods to identify, appraise and combine a body of research evidence, with the goal of producing summary results that guide best practices for stakeholders including patients, clinicians, health professionals, and policy‐makers. Systematic review methodology has been championed by organisations such as Cochrane, who publish systematic reviews in the Cochrane Library summarising the effects of interventions,1 the accuracy of diagnostic tests,2 the prognostic effect of particular factors,3 and the performance of risk prediction models.4 Most systematic reviews include a meta‐analysis,5 which is a statistical technique for combining (synthesising) quantitative data obtained from multiple research studies. Traditionally, most meta‐analyses have used aggregate data extracted from study publications, but there is growing demand for meta‐analyses that utilise individual participant data (IPD).6–9
This
