One-stage individual participant data meta-analysis models: estimation of treatment-covariate interactions must avoid ecological bias by separating out within-trial and across-trial information: One-Stage IPD Meta-Analysis Models Must Avoid Ecological Bias
Open accessAbstract
Stratified medicine utilizes individual-level covariates that are associated with a differential treatment effect, also known as treatment-covariate interactions. When multiple trials are available, meta-analysis is used to help detect true treatment-covariate interactions by combining their data. Meta-regression of trial-level information is prone to low power and ecological bias, and therefore, individual participant data (IPD) meta-analyses are preferable to examine interactions utilizing individual-level information. However, one-stage IPD models are often wrongly specified, such that interactions are based on amalgamating within- and across-trial information. We compare, through simulations and an applied example, fixed-effect and random-effects models for a one-stage IPD meta-analysis of time-to-event data where the goal is to estimate a treatment-covariate interaction. We show that it is crucial to centre patient-level covariates by their mean value in each trial, in order to separate out within-trial and across-trial information. Otherwise, bias and coverage of interaction estimates may be adversely affected, leading to potentially erroneous conclusions driven by ecological bias. We revisit an IPD meta-analysis of five epilepsy trials and examine age as a treatment effect modifier. The interaction is -0.011 (95% CI: -0.019 to -0.003; p = 0.004), and thus highly significant, when amalgamating within-trial and across-trial information. However, when separating within-trial from across-trial information, the interaction is -0.007 (95% CI: -0.019 to 0.005; p = 0.22), and thus its magnitude and statistical significance are greatly reduced. We recommend that meta-analysts should only use within-trial information to examine individual predictors of treatment effect and that one-stage IPD models should separate within-trial from across-trial information to avoid ecological bias. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
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Meta-analysis of individual participant data: rationale, conduct, and reporting
Riley, R. D., Lambert, P. C., & Abo-Zaid, G. (2010) · BMJ · doi:10.1136/bmj.c221 · Cited by 1,701 · see citing works
Self-citationGet real in individual participant data (IPD) meta‐analysis: a review of the methodology
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 (2015) · Research Synthesis Methods · doi:10.1002/jrsm.1160 · Cited by 348 · see citing works
Can meta-analysis help target interventions at individuals most likely to benefit?
Thompson, S. G., & Higgins, J. P. (2005) · The Lancet · doi:10.1016/s0140-6736(05)70200-2 · Cited by 174 · see citing works
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Hayden, J. A., Wilson, M. N., Stewart, S., Cartwright, J. L., Smith, A. O., Riley, R. D., van Tulder, M., Bendix, T., Cecchi, F., Costa, L. O. P., et al. (2020) · British Journal of Sports Medicine · doi:10.1136/bjsports-2019-101205 · Cited by 146 · see citing works
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- Authors
- Hua, H., Burke, D. L., Crowther, M. J., Ensor, J., Tudur Smith, C., & Riley, R. D.
- Affiliations
- Boehringer Ingelheim (China) (CN)
- Keele University (GB)
- University of Leicester (GB)
- MRC North West Hub for Trials Methodology Research, Department of Biostatistics; University of Liverpool; Liverpool L69 3GL U.K.
- Corresponding author
- Riley, Richard D.
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2016-12-01
- Volume
- 36
- Issue
- 5
- Pages
- 772-789
- ISSN
- 0277-6715 (ISSN-L)
- PMC
- PMC5299543
- OpenAlex
- W2560126104
- Cited by
- 113
- References
- 3
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 5 · 2023: 14 · 2022: 10 · 2021: 35 · 2020: 8 · 2019: 11 · 2018: 8 · 2017: 4 · 2016: 1
- FWCI
- 2.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Statistics in Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Keele Research Repository (Keele University) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Leicester Research Archive (University of Leicester) (submittedVersion, cc-by)
- Funders
- MRC Network of Hubs for Trials Methodology Research (MR/K025635/1)
- 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-covariate interaction, ecological bias, stratified medicine, time-to-event data
- MeSH terms
- Age Factors, Anticonvulsants, Epilepsy, Female, Humans, Male, Sex Factors, Meta-Analysis as Topic, Models, Statistical, Bias, Confounding Factors, Epidemiologic, Randomized Controlled Trials as Topic, Treatment Outcome
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