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. 2023 Jul:159:309-318.
doi: 10.1016/j.jclinepi.2023.04.013. Epub 2023 May 4.

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 1: analysis methods are often substandard

Nadine Marlin  1 , Peter J Godolphin  2 , Richard L Hooper  3 , Richard D Riley  4 , Ewelina Rogozińska  2
Affiliations

Nonlinear effects and effect modification at the participant-level in IPD meta-analysis part 1: analysis methods are often substandard

Nadine Marlin et al. J Clin Epidemiol. 2023 Jul.

Abstract

Objectives: To review analysis methods used for linear effect modification (LEM), nonlinear covariate-outcome associations (NL) and nonlinear effect modification (NLEM) at the participant-level in individual participant data meta-analysis (IPDMA).

Study design and setting: We searched Medline, Embase, Web of Science, Scopus, PsycINFO and the Cochrane Library to identify IPDMA of randomized controlled trials (PROSPERO CRD42019126768). We investigated if and how IPDMA examined LEM, NL and NLEM, including whether aggregation bias was addressed and if power was considered.

Results: We screened 6,466 records, randomly sampled 207 and identified 100 IPDMA of LEM, NL or NLEM. Power for LEM was calculated a priori in 3 IPDMA. Of 100 IPDMA, 94 analyzed LEM, 4 NLEM and 8 NL. One-stage models were favoured for all three (56%, 100%, 50%, respectively). Two-stage models were used in 15%, 0% and 25% of IPDMA with unclear descriptions in 30%, 0% and 25%, respectively. Only 12% of one-stage LEM and NLEM IPDMA provided sufficient detail to confirm they had addressed aggregation bias.

Conclusion: Investigation of effect modification at the participant-level is common in IPDMA projects, but methods are often open to bias or lack detailed descriptions. Nonlinearity of continuous covariates and power of IPDMA are rarely assessed.

Keywords: Effect modification; Fractional polynomials; Individual participant data meta-analysis; Interaction; Nonlinear; One- and two-stage models; Restricted cubic splines; Sample size.

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Conflict of interest statement

Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests.

Figures

Fig. 1
Fig. 1
Flow diagram (*This is in the line with the procedure described a priori whereas only a subset of identified IPD research studies was considered in full text. Abbreviations: IPDMA, individual participant data meta-analysis; RCT, randomized controlled trial; LEM, linear effect modification; NL, nonlinear covariate-outcome associations; NLEM, nonlinear effect modification).
Fig. 2
Fig. 2. Number of datasets in each individual participant.
Fig. 3
Fig. 3. Number of participants in each individual participant dataset meta-analysis.
See this image and copyright information in PMC

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