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Meta-analysis for individual participant data with a continuous exposure: A case study

Darssan, Darsy
Mishra, Gita D.
Greenwood, Darren C.
Sandin, Sven
Brunner, Eric J.
Crawford, Sybil L.
El Khoudary, Samar R.
Brooks, Maria Mori
Gold, Ellen
Simonsen, Mette Kildevaeld
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Abstract

OBJECTIVE: Methods for meta-analysis of studies with individual participant data and continuous exposure variables are well described in the statistical literature but are not widely used in clinical and epidemiological research. The purpose of this case study is to make the methods more accessible.

STUDY DESIGN AND SETTING: A two-stage process is demonstrated. Response curves are estimated separately for each study using fractional polynomials. The study-specific curves are then averaged pointwise over all studies at each value of the exposure. The averaging can be implemented using fixed effects or random effects methods.

RESULTS: The methodology is illustrated using samples of real data with continuous outcome and exposure data and several covariates. The sample data set, segments of Stata and R code, and outputs are provided to enable replication of the results.

CONCLUSION: These methods and tools can be adapted to other situations, including for time-to-event or categorical outcomes, different ways of modelling exposure-outcome curves, and different strategies for covariate adjustment.

Source

Darssan D, Mishra GD, Greenwood DC, Sandin S, Brunner EJ, Crawford SL, El Khoudary SR, Brooks MM, Gold EB, Simonsen MK, Chung HF, Weiderpass E, Dobson AJ. Meta-analysis for individual participant data with a continuous exposure: A case study. J Clin Epidemiol. 2021 Dec;140:79-92. doi: 10.1016/j.jclinepi.2021.08.033. Epub 2021 Sep 4. PMID: 34487835; PMCID: PMC9263279.

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DOI
10.1016/j.jclinepi.2021.08.033
PubMed ID
34487835
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© 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)