Cited by 348Meta-analysis and systematic reviewsStatistical Methods in Clinical TrialsAdvanced Causal Inference Techniques

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Get real in individual participant data (IPD) meta‐analysis: a review of the methodology

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Debray, Thomas P. A., Moons, Karel G. M., van Valkenhoef, Gert, Efthimiou, Orestis, Hummel, Noemi, Groenwold, Rolf H. H., Reitsma, Johannes B., on behalf of the GetReal methods review group·2015·Research Synthesis Methods

DOI 10.1002/jrsm.1160PMC PMC5042043

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Abstract

Individual participant data (IPD) meta‐analysis is an increasingly used approach for synthesizing and investigating treatment effect estimates. Over the past few years, numerous methods for conducting an IPD meta‐analysis (IPD‐MA) have been proposed, often making different assumptions and modeling choices while addressing a similar research question. We conducted a literature review to provide an overview of methods for performing an IPD‐MA using evidence from clinical trials or non‐randomized studies when investigating treatment efficacy. With this review, we aim to assist researchers in choosing the appropriate methods and provide recommendations on their implementation when planning and conducting an IPD‐MA. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.

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Efthimiou O, 2015, Methods for network meta‐analysis: a review, Research Synthesis Methods
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Authors: Debray, T. P. A., Moons, K. G. M., van Valkenhoef, G., Efthimiou, O., Hummel, N., Groenwold, R. H. H., Reitsma, J. B., & on behalf of the GetReal methods review group
Affiliations: University of Groningen (NL)
Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
University of Ioannina (GR)
University of Bern (CH)
University Medical Center Utrecht (NL)
Corresponding author: Debray, Thomas P. A.
ORCID: Debray, Thomas P. A.
Moons, Karel G. M.
Efthimiou, Orestis
Hummel, Noemi
Groenwold, Rolf H. H.
Reitsma, Johannes B.
Venue: Research Synthesis Methods
Publisher: Wiley
Published: 2015-08-19
Volume: 6
Issue: 4
Pages: 293-309
ISSN: 1759-2879 (ISSN-L)
1759-2887
DOI: 10.1002/jrsm.1160
PMC: PMC5042043
OpenAlex: W1841651683
Cited by: 348
References: 121
Citations by year: 2026: 28 · 2025: 28 · 2024: 24 · 2023: 36 · 2022: 45 · 2021: 47 · 2020: 35 · 2019: 40 · 2018: 33 · 2017: 16 · 2016: 13 · 2015: 2
FWCI: 3.53
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by-nc-nd
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)
Locations: Research Synthesis Methods (publishedVersion, cc-by-nc-nd)
PubMed Central (publishedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
Pure Amsterdam UMC (submittedVersion, other-oa)
Data Archiving and Networked Services (DANS) (submittedVersion)
BORIS (University Library Bern) (submittedVersion, cc-by-nc-nd)
Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
Open Access CRIS of the University of Bern
Funders: Innovative Medicines Initiative Joint Undertaking (115546)
European Union's Seventh Framework Programme (FP7/20072013)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Keywords: individual patient data meta-analysis, treatment effect estimation, clinical trials, non-randomized studies, methodological assumptions
MeSH terms: Data Interpretation, Statistical, Humans, Software, Meta-Analysis as Topic, Models, Statistical, Linear Models, Proportional Hazards Models, Randomized Controlled Trials as Topic, Treatment Outcome

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