Individual Participant Data (IPD) Meta-analyses of Randomised Controlled Trials: Guidance on Their Use

Tierney, Jayne; Vale, Claire; Riley, Richard D; Smith, Catrin Tudur; Stewart, Lesley; Clarke, Mike; Rovers, Maroeska M.

doi:10.1371/journal.pmed.1001855

Cited by 268 publications

(301 citation statements)

References 61 publications

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“…For example, Debray et al found that erythema was a statistically significant predictor of deep vein thrombosis (DVT) in a one‐stage analysis ( p = 0.03), but not a two‐stage analysis ( p = 0.12) 3. For this reason, Tierney et al advise, ‘It is important, therefore, that the choice of one or two‐stage analysis is specified in advance or that results for both approaches are reported’ 13.…”

Section: Introductionmentioning

confidence: 99%

“…To illustrate this, Tierney et al give a binary outcome example where the effects of anti‐platelets on pre‐eclampsia in pregnancy from two‐stage (relative risk = 0.90, 95% CI = 0.83 to 0.96) and one‐stage (relative risk = 0.90, 95% CI = 0.83 to 0.97) analyses were almost identical 2, 13.…”

Section: An Introduction To One‐stage and Two‐stage Ipd Meta‐analysismentioning

confidence: 99%

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Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ

2016

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Meta‐analysis using individual participant data (IPD) obtains and synthesises the raw, participant‐level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta‐analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual‐level interactions, such as treatment‐effect modifiers. There are two statistical approaches for conducting an IPD meta‐analysis: one‐stage and two‐stage. The one‐stage approach analyses the IPD from all studies simultaneously, for example, in a hierarchical regression model with random effects. The two‐stage approach derives aggregate data (such as effect estimates) in each study separately and then combines these in a traditional meta‐analysis model. There have been numerous comparisons of the one‐stage and two‐stage approaches via theoretical consideration, simulation and empirical examples, yet there remains confusion regarding when each approach should be adopted, and indeed why they may differ.In this tutorial paper, we outline the key statistical methods for one‐stage and two‐stage IPD meta‐analyses, and provide 10 key reasons why they may produce different summary results. We explain that most differences arise because of different modelling assumptions, rather than the choice of one‐stage or two‐stage itself. We illustrate the concepts with recently published IPD meta‐analyses, summarise key statistical software and provide recommendations for future IPD meta‐analyses. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

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Section: Introductionmentioning

confidence: 99%

Section: An Introduction To One‐stage and Two‐stage Ipd Meta‐analysismentioning

confidence: 99%

Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ

2016

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“…Studies investigating moderators of the exercise intervention effects on physical fitness are scarce, and single RCTs are generally underpowered to investigate such moderator effects. The use of IPD from multiple RCTs allows testing of moderators with interaction tests in larger samples 30. Therefore, we aimed to identify demographic, clinical, intervention-related and exercise-related moderators of the exercise intervention effect on UBMS, LBMS, LBMF and aerobic fitness using IPD available in the POLARIS database 29…”

Section: Introductionmentioning

confidence: 99%

Effects and moderators of exercise on muscle strength, muscle function and aerobic fitness in patients with cancer: a meta-analysis of individual patient data

Sweegers¹,

Altenburg

Brug

et al. 2018

Br J Sports Med

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“…17 Our output complied with the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) reporting guidelines for IPD meta-analysis. 18 …”

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confidence: 99%

Effects of antenatal diet and physical activity on maternal and fetal outcomes: individual patient data meta-analysis and health economic evaluation

Rogozińska

Marlin

Jackson

et al. 2017

Health Technol Assess

231

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BackgroundDiet- and physical activity-based interventions in pregnancy have the potential to alter maternal and child outcomes.ObjectivesTo assess whether or not the effects of diet and lifestyle interventions vary in subgroups of women, based on maternal body mass index (BMI), age, parity, Caucasian ethnicity and underlying medical condition(s), by undertaking an individual patient data (IPD) meta-analysis. We also evaluated the association of gestational weight gain (GWG) with adverse pregnancy outcomes and assessed the cost-effectiveness of the interventions.Data sourcesMEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects and Health Technology Assessment database were searched from October 2013 to March 2015 (to update a previous search).Review methodsResearchers from the International Weight Management in Pregnancy Collaborative Network shared the primary data. For each intervention type and outcome, we performed a two-step IPD random-effects meta-analysis, for all women (except underweight) combined and for each subgroup of interest, to obtain summary estimates of effects and 95% confidence intervals (CIs), and synthesised the differences in effects between subgroups. In the first stage, we fitted a linear regression adjusted for baseline (for continuous outcomes) or a logistic regression model (for binary outcomes) in each study separately; estimates were combined across studies using random-effects meta-analysis models. We quantified the relationship between weight gain and complications, and undertook a decision-analytic model-based economic evaluation to assess the cost-effectiveness of the interventions.ResultsDiet and lifestyle interventions reduced GWG by an average of 0.70 kg (95% CI –0.92 to –0.48 kg; 33 studies, 9320 women). The effects on composite maternal outcome [summary odds ratio (OR) 0.90, 95% CI 0.79 to 1.03; 24 studies, 8852 women] and composite fetal/neonatal outcome (summary OR 0.94, 95% CI 0.83 to 1.08; 18 studies, 7981 women) were not significant. The effect did not vary with baseline BMI, age, ethnicity, parity or underlying medical conditions for GWG, and composite maternal and fetal outcomes. Lifestyle interventions reduce Caesarean sections (OR 0.91, 95% CI 0.83 to 0.99), but not other individual maternal outcomes such as gestational diabetes mellitus (OR 0.89, 95% CI 0.72 to 1.10), pre-eclampsia or pregnancy-induced hypertension (OR 0.95, 95% CI 0.78 to 1.16) and preterm birth (OR 0.94, 95% CI 0.78 to 1.13). There was no significant effect on fetal outcomes. The interventions were not cost-effective. GWG, including adherence to the Institute of Medicine-recommended targets, was not associated with a reduction in complications. Predictors of GWG were maternal age (summary estimate –0.10 kg, 95% CI –0.14 to –0.06 kg) and multiparity (summary estimate –0.73 kg, 95% CI –1.24 to –0.23 kg).LimitationsThe findings were limited by the lack of standardisation in the components of intervention, residual heterogeneity in effects across studies for most analyses and the unavailability of IPD in some studies.ConclusionDiet and lifestyle interventions in pregnancy are clinically effective in reducing GWG irrespective of risk factors, with no effects on composite maternal and fetal outcomes.Future workThe differential effects of lifestyle interventions on individual pregnancy outcomes need evaluation.Study registrationThis study is registered as PROSPERO CRD42013003804.FundingThe National Institute for Health Research Health Technology Assessment programme.

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Individual Participant Data (IPD) Meta-analyses of Randomised Controlled Trials: Guidance on Their Use

Abstract: Jayne Tierney and colleagues offer guidance on how to spot a well-designed and well-conducted individual participant data meta-analysis.

Cited by 268 publications

References 61 publications

Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ

Meta-analysis using individual participant data: one-stage and two-stage approaches, and why they may differ

Effects and moderators of exercise on muscle strength, muscle function and aerobic fitness in patients with cancer: a meta-analysis of individual patient data

Effects of antenatal diet and physical activity on maternal and fetal outcomes: individual patient data meta-analysis and health economic evaluation

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