Individual Participant Data Meta-Analysis - A Handbook for Healthcare Research

Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points.
 
Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data.
 
Intended for a broad audience, the book will enable the reader to:
* Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review
* Recognise the scope, resources and challenges of IPD meta-analysis projects
* Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators
* Understand how to obtain, check, manage and harmonise IPD from multiple studies
* Examine risk of bias (quality) of IPD and minimise potential biases throughout the project
* Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them
* Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research
* Critically appraise existing IPD meta-analysis projects
* Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models
Detailed examples and case studies are provided throughout.

List of contents

Acknowledgements xxiii
 
1 Individual Participant Data Meta-analysis for Healthcare Research 1
Richard D. Riley, Lesley A. Stewart, and Jayne F. Tierney
 
1.1 Introduction 1
 
1.2 What Is IPD and How Does It Differ from Aggregate Data? 1
 
1.3 IPD Meta-analysis: A New Era for Evidence Synthesis 2
 
1.4 Scope of This Book and Intended Audience 2
 
Part I Rationale, Planning, and Conduct 7
 
2 Rationale for Embarking on an IPD Meta-analysis Project 9
Jayne F. Tierney, Richard D. Riley, Catrin Tudur Smith, Mike Clarke, and Lesley A. Stewart
 
2.1 Introduction 9
 
2.2 How Does the Research Process Differ for IPD and Aggregate Data Meta-analysis Projects? 10
 
2.2.1 The Research Aims 10
 
2.2.2 The process and methods 10
 
2.3 What Are the Potential Advantages of an IPD Meta-analysis Project? 11
 
2.4 What Are the Potential Challenges of an IPD Meta-Analysis Project? 14
 
2.5 Empirical Evidence of Differences between Results of IPD and Aggregate Data Metaanalysis Projects 14
 
2.6 Guidance for Deciding When IPD Meta-analysis Projects Are Needed to Evaluate Treatment Effects from Randomised Trials 15
 
2.6.1 Are IPD Needed to Tackle the Research Question? 15
 
2.6.2 Are IPD Needed to Improve the Completeness and Uniformity of Outcomes and Participant-level Covariates? 17
 
2.6.3 Are IPD Needed to Improve the Information Size? 17
 
2.6.4 Are IPD Needed to Improve the Quality of Analysis? 18
 
2.7 Concluding Remarks 19
 
3 Planning and Initiating an IPD Meta-analysis Project 21
Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney
 
3.1 Introduction 22
 
3.2 Organisational Approach 22
 
3.2.1 Collaborative IPD Meta-analysis Project 22
 
3.2.2 IPD Meta-analysis Projects Using Data Repositories or Data-sharing Platforms 24
 
3.3 Developing a Project Scope 26
 
3.4 Assessing Feasibility and 'In Principle' Support and Collaboration 26
 
3.5 Establishing a Team with the Right Skills 29
 
3.6 Advisory and Governance Functions 30
 
3.7 Estimating How Long the Project Will Take 31
 
3.8 Estimating the Resources Required 33
 
3.9 Obtaining Funding 38
 
3.10 Obtaining Ethical Approval 39
 
3.11 Data-sharing Agreement 41
 
3.12 Additional Planning for Prospective Meta-analysis Projects 41
 
3.13 Concluding Remarks 43
 
4 Running an IPD Meta-analysis Project: From Developing the Protocol to Preparing Data for Meta-analysis 45
Jayne F. Tierney, Richard D. Riley, Larysa H.M. Rydzewska, and Lesley A. Stewart
 
4.1 Introduction 46
 
4.2 Preparing to Collect IPD 46
 
4.2.1 Defining the Objectives and Eligibility Criteria 46
 
4.2.2 Developing the Protocol for an IPD Meta-analysis Project 49
 
4.2.3 Identifying and Screening Potentially Eligible Trials 51
 
4.2.4 Deciding Which Information Is Needed to Summarise Trial Characteristics 51
 
4.2.5 Deciding How Much IPD Are Needed 52
 
4.2.6 Deciding Which Variables Are Needed in the IPD 52
 
4.2.7 Developing a Data Dictionary for the IPD 55
 
4.3 Initiating and Maintaining Collaboration 57
 
4.4 Obtaining IPD 59
 
4.4.1 Ensuring That IPD Are De-identified 59
 
4.4.2 Providing Data Transfer Guidance 60
 
4.4.3 Transferring trial IPD securely 61
 
4.4.4 Storing Trial IPD Securely 61
 
4.4.5 Making Best Use of IPD from Repositories 61
 
4.5 Checking and Harmonising Incoming IPD 62
 
4.5.1 The Process and Principles 63
 
4.5.2 Initial Checking of IPD for Each Trial 63
 
4.5.3 Ha

About the author

Richard D. Riley is Professor of Biostatistics in the School of Medicine, Keele University, UK.
Jayne F. Tierney is Professor of Evidence Synthesis at the MRC Clinical Trials Unit, University College London, UK.
Lesley A. Stewart is Professor of Evidence Synthesis and Director of the Centre for Reviews and Dissemination, University of York, UK.

Summary

Individual Participant Data Meta-Analysis: A Handbook for Healthcare Researchprovides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points.

Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data.

Intended for a broad audience, the book will enable the reader to:
* Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review
* Recognise the scope, resources and challenges of IPD meta-analysis projects
* Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators
* Understand how to obtain, check, manage and harmonise IPD from multiple studies
* Examine risk of bias (quality) of IPD and minimise potential biases throughout the project
* Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them
* Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research
* Critically appraise existing IPD meta-analysis projects
* Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models
Detailed examples and case studies are provided throughout.

Product details

• Authors: Rd Riley, Richar Riley, Richard Riley, Richard D Riley, Richard D. Riley, Richard D. (Keele University Riley, Richard D. Tierney Riley, Richard Tierney Riley, Lesley Stewart, Lesley A. Stewart, Jayn Tierney, Jayne Tierney, Jayne F Tierney, Jayne F. Tierney
• Assisted by: Lesley A Stewart (Editor), Jayn F Tierney (Editor), Jayne F Tierney (Editor), Richard D. Riley (Editor), Lesley A. Stewart (Editor), Stewart Lesley A. (Editor), Jayne F. Tierney (Editor)
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 31.05.2021
• EAN: 9781119333722
• ISBN: 978-1-119-33372-2
• No. of pages: 560
• Series: Statistics in Practice
• Subjects: Natural sciences, medicine, IT, technology > Mathematics; Statistik, Medizin, Medizinische Statistik, Statistics, Medical Science, Evidenzbasierte Forschung im Gesundheitswesen, Evidence-Based Health Care, Medical Statistics & Epidemiology, Medizinische Statistik u. Epidemiologie