Individual Participant Data Meta-Analysis

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.

• Acknowledgements xxiii1 Individual Participant Data Meta-analysis for Healthcare Research 1Richard D. Riley, Lesley A. Stewart, and Jayne F. Tierney1.1 Introduction 11.2 What Is IPD and How Does It Differ from Aggregate Data? 11.3 IPD Meta-analysis: A New Era for Evidence Synthesis 21.4 Scope of This Book and Intended Audience 2Part I Rationale, Planning, and Conduct 72 Rationale for Embarking on an IPD Meta-analysis Project 9Jayne F. Tierney, Richard D. Riley, Catrin Tudur Smith, Mike Clarke, and Lesley A. Stewart2.1 Introduction 92.2 How Does the Research Process Differ for IPD and Aggregate Data Meta-analysis Projects? 102.3 What Are the Potential Advantages of an IPD Meta-analysis Project? 112.4 What Are the Potential Challenges of an IPD Meta-Analysis Project? 142.5 Empirical Evidence of Differences between Results of IPD and Aggregate Data Metaanalysis Projects 142.6 Guidance for Deciding When IPD Meta-analysis Projects Are Needed to Evaluate Treatment Effects from Randomised Trials 152.7 Concluding Remarks 193 Planning and Initiating an IPD Meta-analysis Project 21Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney3.1 Introduction 223.2 Organisational Approach 223.3 Developing a Project Scope 263.4 Assessing Feasibility and ‘In Principle’ Support and Collaboration 263.5 Establishing a Team with the Right Skills 293.6 Advisory and Governance Functions 303.7 Estimating How Long the Project Will Take 313.8 Estimating the Resources Required 333.9 Obtaining Funding 383.10 Obtaining Ethical Approval 393.11 Data-sharing Agreement 413.12 Additional Planning for Prospective Meta-analysis Projects 413.13 Concluding Remarks 434 Running an IPD Meta-analysis Project: From Developing the Protocol to Preparing Data for Meta-analysis 45Jayne F. Tierney, Richard D. Riley, Larysa H.M. Rydzewska, and Lesley A. Stewart4.1 Introduction 464.2 Preparing to Collect IPD 464.3 Initiating and Maintaining Collaboration 574.4 Obtaining IPD 594.5 Checking and Harmonising Incoming IPD 624.6 Checking the IPD to Inform Risk of Bias Assessments 664.7 Assessing and Presenting the Overall Quality of a Trial 764.8 Verification of Finalised Trial IPD 774.9 Merging IPD Ready for Meta-analysis 774.10 Concluding Remarks 80Part I References 81Part II Fundamental Statistical Methods and Principles 875 The Two-stage Approach to IPD Meta-analysis 89Richard D. Riley, Thomas P.A. Debray, Tim P. Morris, and Dan Jackson5.1 Introduction 905.2 First Stage of a Two-stage IPD Meta-analysis 905.3 Second Stage of a Two-stage IPD Meta-analysis 1065.4 Meta-regression and Subgroup Analyses 1205.5 The ipdmetan Software Package 1215.6 Combining IPD with Aggregate Data from non-IPD Trials 1245.7 Concluding Remarks 1256 The One-stage Approach to IPD Meta-analysis 127Richard D. Riley and Thomas P.A. Debray 1276.1 Introduction 1286.2 One-stage IPD Meta-analysis Models Using Generalised Linear Mixed Models 1296.3 One-stage Models for Time-to-event Outcomes 1526.4 One-stage Models Combining Different Sources of Evidence 1596.5 Reporting of One-stage Models in Protocols and Publications 1626.6 Concluding Remarks 1627 Using IPD Meta-analysis to Examine Interactions between Treatment Effect and Participant-level Covariates 163Richard D. Riley and David J. Fisher7.1 Introduction 1647.2 Meta-regression and Its Limitations 1667.3 Two-stage IPD Meta-analysis to Estimate Treatment-covariate Interactions 1687.4 The One-stage Approach 1747.5 Combining IPD and non-IPD Trials 1817.6 Handling of Continuous Covariates 1847.7 Handling of Categorical or Ordinal Covariates 1917.8 Misconceptions and Cautions 1917.9 Is My Identified Treatment-covariate Interaction Genuine? 1957.10 Reporting of Analyses of Treatment-covariate Interactions 1967.11 Can We Predict a New Patient’s Treatment Effect? 1967.11.1 Linking Predictions to Clinical Decision Making 1987.12 Concluding Remarks 1988 One-stage versus Two-stage Approach to IPD Meta-analysis: Differences and Recommendations 199Richard D. Riley, Danielle L. Burke, and Tim Morris8.1 Introduction 2008.2 One-stage and Two-stage Approaches Usually Give Similar Results 2008.3 Ten Key Reasons Why One-stage and Two-stage Approaches May Give Different Results 2038.4 Recommendations and Guidance 2168.5 Concluding Remarks 217Part II References 219Part III Critical Appraisal and Dissemination 2379 Examining the Potential for Bias in IPD Meta-analysis Results 239Richard D. Riley, Jayne F. Tierney, and Lesley A. Stewart9.1 Introduction 2409.2 Publication and Reporting Biases of Trials 2409.3 Biased Availability of the IPD from Trials 2449.4 Trial Quality (risk of bias) 2479.5 Other Potential Biases Affecting IPD Meta-analysis Results 2489.6 Concluding Remarks 25110 Reporting and Dissemination of IPD Meta-analyses 253Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney10.1 Introduction 25310.2 Reporting IPD Meta-analysis Projects in Academic Reports 25410.3 Additional Means of Disseminating Findings 26610.4 Concluding Remarks 27011 A Tool for the Critical Appraisal of IPD Meta-analysis Projects (CheckMAP) 271Jayne F. Tierney, Lesley A. Stewart, Claire L. Vale, and Richard D. Riley11.1 Introduction 27111.2 The CheckMAP Tool 27211.3 Was the IPD Meta-analysis Project Done within a Systematic Review Framework? 27211.4 Were the IPD Meta-analysis Project Methods Pre-specified in a Publicly Available Protocol? 27411.5 Did the IPD Meta-analysis Project Have a Clear Research Question Qualified by Explicit Eligibility Criteria? 27611.6 Did the IPD Meta-analysis Project Have a Systematic and Comprehensive Search Strategy? 27611.7 Was the Approach to Data Collection Consistent and Thorough? 27711.8 Were IPD Obtained from Most Eligible Trials and Their Participants? 27711.9 Was the Validity of the IPD Checked for Each Trial? 27811.10 Was the Risk of Bias Assessed for Each Trial and Its Associated IPD? 27811.10.1 Was the Randomisation Process Checked Based on IPD? 27811.11 Were the Methods of Meta-analysis Appropriate? 28011.12 Concluding Remarks 283Part III References 285Part IV Special Topics in Statistics 29112 Power Calculations for Planning an IPD Meta-analysis 293Richard D. Riley and Joie Ensor12.1 Introduction 29412.2 Motivating Example: Power of a Planned IPD Meta-analysis of Trials of Interventions to Reduce Weight Gain in Pregnant Women 29512.3 The Contribution of Individual Trials Toward Power 30112.4 The Impact of Model Assumptions on Power 30212.5 Extensions 30512.6 Concluding Remarks 30913 Multivariate Meta-analysis Using IPD 311Richard D. Riley, Dan Jackson, and Ian R. White13.1 Introduction 31213.2 General Two-stage Approach for Multivariate IPD Meta-analysis 31413.3 Application to an IPD Meta-analysis of Anti-hypertensive Trials 32913.4 Extension to Multivariate Meta-regression 33313.5 Potential Limitations of Multivariate Meta-analysis 33413.6 One-stage Multivariate IPD Meta-analysis Applications 33713.7 Special Applications of Multivariate Meta-analysis 34013.8 Concluding Remarks 34614 Network Meta-analysis Using IPD 347Richard D. Riley, David M. Phillippo, and Sofia Dias14.1 Introduction 34814.2 Rationale and Assumptions for Network Meta-analysis 34814.3 Network Meta-analysis Models Assuming Consistency 35014.4 Ranking Treatments 35714.5 How Do We Examine Inconsistency between Direct and Indirect Evidence? 35914.6 Benefits of IPD for Network Meta-analysis 36114.7 Combining IPD and Aggregate Data in Network Meta-analysis 36514.8 Further Topics 37014.9 Concluding Remarks 372Part IV References 375Part V Diagnosis, Prognosis and Prediction 38715 IPD Meta-analysis for Test Accuracy Research 389Richard D. Riley, Brooke Levis, and Yemisi Takwoingi 38915.1 Introduction 39015.2 Motivating Example: Diagnosis of Fever in Children Using Ear Temperature 39415.3 Key Steps Involved in an IPD Meta-analysis of Test Accuracy Studies 39715.4 IPD Meta-analysis of Test Accuracy at Multiple Thresholds 41015.5 IPD Meta-analysis for Examining a Test’s Clinical Utility 41415.6 Comparing Tests 41815.7 Concluding Remarks 42016 IPD Meta-analysis for Prognostic Factor Research 421Richard D. Riley, Karel G.M. Moons, and Thomas P.A. Debray16.1 Introduction 42216.2 Potential Advantages of an IPD Meta-analysis 42416.3 Key Steps Involved in an IPD Meta-analysis of Prognostic Factor Studies 42716.4 Software 44416.5 Concluding Remarks 44417 IPD Meta-analysis for Clinical Prediction Model Research 447Richard D. Riley, Kym I.E. Snell, Laure Wynants, Valentijn M.T. de Jong, Karel G.M. Moons, and Thomas P.A. Debray17.1 Introduction 44817.2 IPD Meta-analysis for Prediction Model Research 44817.3 External Validation of an Existing Prediction Model Using IPD Meta-analysis 45517.4 Updating and Tailoring of a Prediction Model Using IPD Meta-analysis 47017.5 Comparison of Multiple Existing Prediction Models Using IPD Meta-analysis 47217.6 Using IPD Meta-analysis to Examine the Added Value of a New Predictor to an Existing Prediction Model 47817.7 Developing a New Prediction Model Using IPD Meta-analysis 47917.8 Examining the Utility of a Prediction Model Using IPD Meta-analysis 49117.9 Software 49417.10 Reporting 49517.11 Concluding Remarks 49518 Dealing with Missing Data in an IPD Meta-analysis 499Thomas Debray, Kym I.E. Snell, Matteo Quartagno, Shahab Jolani, Karel G.M. Moons, and Richard D. Riley 49918.1 Introduction 50018.2 Motivating Example: IPD Meta-analysis Validating Prediction Models for Risk of Preeclampsia in Pregnancy 50018.3 Types of Missing Data in an IPD Meta-analysis 50218.4 Recovering Actual Values of Missing Data within IPD 50218.5 Mechanisms and Patterns of Missing Data in an IPD Meta-analysis 50218.6 Multiple Imputation to Deal with Missing Data in a Single Study 50618.7 Ensuring Congeniality of Imputation and Analysis Models 50918.8 Dealing with Sporadically Missing Data in an IPD Meta-analysis by Applying Multiple Imputation for Each Study Separately 50918.9 Dealing with Systematically Missing Data in an IPD Meta-analysis Using a Bivariate Metaanalysis of Partially and Fully Adjusted Results 51118.10 Dealing with Both Sporadically and Systematically Missing Data in an IPD Meta-analysis Using Multilevel Modelling 51418.11 Comparison of Methods and Recommendations 52118.12 Software 52318.13 Concluding Remarks 524Part V References 525Index 000