Individual Participant Data Meta-Analysis

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

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17 Part V: References

18 Index

19 End User License Agreement

List of Tables

1 Chapter 2 Table 2.1 Key potential advantages of an IPD meta‐analysis project compared w... Table 2.2 Signalling questions to help decide when aggregate data are insuffi...

2 Chapter 3 Table 3.1 Consent sought to collaborate in an IPD analysis of predictive fact...

3 Chapter 4 Table 4.1 Excerpt from a data dictionary developed for an IPD meta‐analysis o... Table 4.2 Excerpt from a data dictionary developed for an IPD meta‐analysis p... Table 4.3 Example of items to include in a data transfer guide when requestin... Table 4.4 Domains in the Risk of Bias 2 tool 91(RoB 2) of particular relevanc... Table 4.5 Alleviating potential bias in trials that stopped early for perceiv... Table 4.6 Excerpt of a RoB2 table for an IPD meta‐analysis of adjuvant chemot...

4 Chapter 5 Table 5.1 Example of hypothetical IPD for one trial similar to those received... Table 5.2 Basic format of the regression model to be fitted separately within... Table 5.3 Example of aggregate data calculated for each trial in the first st...

5 Chapter 6Table 6.1 Basic format of the GLMM for one‐stage IPD meta‐analysis models of ...Table 6.2 Software for fitting one‐stage IPD meta‐analysis via the GLMM or su...

6 Chapter 8Table 8.1 Comparison of summary results from ML estimation of one‐stage and t...Table 8.2 Summary results from an IPD meta‐analysis of 10 randomised trials e...Table 8.3 Summary treatment effect results for the hypertension data to illus...Table 8.4 One‐stage and two‐stage REML results for the prognostic effect of s...Table 8.5 Summary results from one‐stage and two‐stage IPD meta‐analyses of 1...

7 Chapter 10Table 10.1 Title and Introduction sections of the PRISMA‐IPD Checklist as rep...Table 10.2 Methods section of the PRISMA‐IPD Checklist as reported by Stewart...Table 10.3 Results and discussion sections of the PRISMA‐IPD Checklist as rep...

8 Chapter 11Table 11.1 Summary of completion of the CheckMAP tool for an IPD meta‐analysi...

9 Chapter 12Table 12.1 Trial characteristics used in the power calculations of an IPD met...

10 Chapter 13Table 13.1 Summary results for the 10 trials included in the meta‐analysis of...Table 13.2 Bivariate and multivariate results for the IPD meta‐analysis of 10...Table 13.3 Results from two‐stage and one‐stage bivariate meta‐analysis of SB...Table 13.4 Results from one‐stage bivariate IPD meta‐analysis of 10 randomise...Table 13.5 Summary results following REML estimation of a two‐stage multivari...

11 Chapter 14Table 14.1 Trials in the thrombolytic network meta‐analysis summarised in ter...Table 14.2 Summary results from the thrombolytics network meta‐analysis compa...Table 14.3 Results reported by Donegan et al. 191after estimation of network ...Table 14.4 Baseline covariate summaries from the UNCOVER and FIXTURE trials. ...

12 Chapter 15Table 15.1 Cross classification of index test results and reference standard ...Table 15.2 Typical statistical measures of test accuracy in a single study i ...Table 15.3 Summary of 23 studies used by Riley et al. in an IPD meta‐analysis...

13 Chapter 16Table 16.1 Selected items of the CHARMS‐PF *checklist to be extracted when id...

14 Chapter 17Table 17.1 Domains and signalling questions within the first three domains of...Table 17.2 Selected items from the CHARMS checklist to be extracted when iden...Table 17.3 Relevant statistics to be estimated in the first stage of a two‐st...Table 17.4 Coefficients of eight prediction models for diagnosing DVT in pati...Table 17.5 Trivariate random‐effects meta‐analysis results for calibration (a...Table 17.6 Model parameter estimates for the fitted DVT model obtained in eac...Table 17.7 Trivariate meta‐analysis results *for the calibration and discrimi...Table 17.8 Preliminary version of the TRIPOD‐CLUSTER statement extended to si...

15 Chapter 18Table 18.1 Summary of five IPD studies from the IPPIC network that were used ...Table 18.2 Example of sporadically missing predictors (previous pre‐eclampsia...Table 18.3 Summary statistics for participants with complete data, and for pa...Table 18.4 A summary of the results at each stage of the multiple imputation ...Table 18.5 Description of variables and missing data (NA) in the simulated IP...Table 18.6 Key advantages and limitations of the multilevel joint modelling a...

List of Illustrations

1 Chapter 1 Figure 1.1 Number of published IPD meta‐analysis articles over time, based o...

2 Chapter 2 Figure 2.1 Key differences between the process for a IPD meta‐analysis proje...

3 Chapter 3 Figure 3.1 Typical phases of an IPD meta‐analysis project.

4 Chapter 4 Figure 4.1 Overview of key steps involved in obtaining, managing and checkin... Figure 4.2 PICOS example: objective and eligibility criteria for an IPD meta... Figure 4.3 Excerpt from a trial‐level data collection form for the STOPCAP M... Figure 4.4 Excerpts from the website https://www.york.ac.uk/crd/research/epp... Figure 4.5 Median follow‐up based on published aggregate data compared to up... Figure 4.6 Summary of the data validity, range and consistency checks on IPD... Figure 4.7 The cumulative number of participants randomised to the intervent... Figure 4.8 The cumulative number of participants allocated to chemotherapy o... Figure 4.9 Date (shown by year‐month) participants were allocated to treatme... Figure 4.10 Days of the week participants were allocated to treatment and co... Figure 4.11 Percentage of participants excluded from the original analyses o... Figure 4.12 ‘Reverse’ Kaplan‐Meier analysis of participants who are event‐fr... Figure 4.13 Example of items to include in summary of finalised trial IPD fo...

5 Chapter 5Figure 5.1 Posterior distributions after applying a Bayesian random treatmen...Figure 5.2 Forest plots of two hypothetical meta‐analyses that give the same...

6 Chapter 6Figure 6.1 Results of the simulation study of Abo‐Zaid et al., 3comparing (a...Figure 6.2 Simulation results for binary outcomes from Riley et al. 181for s...Figure 6.3 Baseline hazard functions from ML estimation of a one‐stage IPD m...Figure 6.4 Estimated baseline hazard rate for one of the 10 trials included ...

7 Chapter 7Figure 7.1 Scatter plot (on logit scale) of p ‐values from 31 re‐analyses of ...Figure 7.2 A two‐stage IPD meta‐analysis of treatment‐sex interactions, summ...Figure 7.3 Is blood pressure–lowering treatment more effective amongst women...Figure 7.4 Bland‐Altman plot showing level of agreement between treatment‐co...Figure 7.5 PORT meta‐analysis results for the interaction between treatment ...Figure 7.6 Representations of how the effect of an early supported hospital ...Figure 7.7 Evidence for a potential non‐linear interaction between age and t...Figure 7.8 Evidence of a potential non‐linear interaction between baseline S...Figure 7.9 The predicted effect of anti‐hypertensive treatment on SBP condit...

8 Chapter 8Figure 8.1 One‐stage and two‐stage IPD meta‐analysis summary results from 10...Figure 8.2 Forest plot showing the one‐stage and two‐stage IPD meta‐analysis...Figure 8.3 Forest plot showing one‐stage and two‐stage IPD meta‐analysis res...Figure 8.4 Summary treatment effect estimates and 95% confidence intervals f...

9 Chapter 9Figure 9.1 Examination of small‐study effects in an IPD meta‐analysis to eva...Figure 9.2 Forest plot of the IPD meta‐analysis *of Martineau et al. 24, with...Figure 9.3 Example of combining IPD and non‐IPD trials in an IPD meta‐analys...Figure 9.4 Contour‐enhanced funnel plots for the IPD meta‐analysis of Rogozi...

10 Chapter 10Figure 10.1 Example of the PRISMA‐IPD flowchart applied to an IPD meta‐analy...Figure 10.2 Example of a figure displaying the extent and pattern of missing...

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