Evidence map›Paper›PMID 37146661›Full record

ArticleJournal of clinical epidemiology2023

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

Nadine Marlin, Peter J Godolphin, Richard L Hooper, Richard D Riley, Ewelina Rogozińska

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In one paragraph

Article in Journal of clinical epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nadine MarlinMethodology Research Unit, Centre for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK. Electronic address: n.marlin@qmul.ac.uk.
Peter J GodolphinMRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.
Richard L HooperMethodology Research Unit, Centre for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK.
Richard D RileyInstitute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham B15 2TT, UK.
Ewelina RogozińskaMRC Clinical Trials Unit at University College London, Institute of Clinical Trials and Methodology, 90 High Holborn, London WC1V 6LJ, UK.

Funding

Department of Health DRF-2018-11-ST2-077Department of Health NIHR301653Medical Research Council MC_UU_00004/06
6 · The paper itself

Abstract

objectivesTo 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

settingWe 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.

resultsWe 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.

conclusionInvestigation 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.

Indexed as

BiasMeta-Analysis as TopicHumansEffect modificationFractional polynomialsIndividual participant data meta-analysisInteractionNonlinearOne- and two-stage modelsRestricted cubic splinesSample size

Identifiers

PMID37146661
PMCPMC7616832

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.