Evidence map›Paper›PMID 32645021›Full record

ArticlePloS one2020

Marginal structural models for repeated measures where intercept and slope are correlated: An application exploring the benefit of nutritional supplements on weight gain in HIV-infected children initiating antiretroviral therapy.

Ruth E Farmer, Rhian Daniel, Deborah Ford, Adrian Cook, Victor Musiime, Mutsa Bwakura-Dangarembizi, Diana M Gibb, Andrew J Prendergast, A Sarah Walker, ARROW trial team

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 90% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Trial
  2. Article
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

10 authors at 6 institutions in 3 countries.

Ruth E FarmerMRC Clinical Trials Unit at UCL, UCL Institute for Clinical Trials and Methodology, London, England, United Kingdom.
Rhian DanielDivision of Population Medicine, University of Cardiff, Cardiff, Wales, United Kingdom.
Deborah FordMRC Clinical Trials Unit at UCL, UCL Institute for Clinical Trials and Methodology, London, England, United Kingdom.
Adrian CookMRC Clinical Trials Unit at UCL, UCL Institute for Clinical Trials and Methodology, London, England, United Kingdom.
Victor MusiimeJoint Clinical Research Center, Kampala, Uganda.
Mutsa Bwakura-DangarembiziUniversity of Zimbabwe Clinical Research Centre, Harare, Zimbabwe.
Diana M GibbMRC Clinical Trials Unit at UCL, UCL Institute for Clinical Trials and Methodology, London, England, United Kingdom.
Andrew J PrendergastQueen Mary University of London, London, England, United Kingdom.
A Sarah WalkerMRC Clinical Trials Unit at UCL, UCL Institute for Clinical Trials and Methodology, London, England, United Kingdom.ORCID 0000-0002-0412-8509
ARROW trial team
MRC Clinical Trials Unit at UCL · GBCardiff University · GBJoint Clinical Research Centre · UGLondon School of Hygiene & Tropical Medicine · GBQueen Mary University of London · GBUniversity of Zimbabwe · ZW

Funding

Medical Research Council MC_EX_G0300400Medical Research Council MC_U122886353Medical Research Council MC_UU_12023/17Medical Research Council MC_UU_12023/21Medical Research Council MC_UU_12023/26Medical Research Council PHSRN47Wellcome Trust 107617/Z/15/ZWellcome Trust 108065/Z/15/Z
6 · The paper itself

Abstract

backgroundThe impact of nutritional supplements on weight gain in HIV-infected children on antiretroviral treatment (ART) remains uncertain. Starting supplements depends upon current weight-for-age or other acute malnutrition indicators, producing time-dependent confounding. However, weight-for-age at ART initiation may affect subsequent weight gain, independent of supplement use. Implications for marginal structural models (MSMs) with inverse probability of treatment weights (IPTW) are unclear.

methodsIn the ARROW trial, non-randomised supplement use and weight-for-age were recorded monthly from ART initiation. The effect of supplements on weight-for-age over the first year was estimated using generalised estimating equation MSMs with IPTW, both with and without interaction terms between baseline weight-for-age and time. Separately, data were simulated assuming no supplement effect, with use depending on current weight-for-age, and weight-for-age trajectory depending on baseline weight-for-age to investigate potential bias associated with different MSM specifications.

resultsIn simulations, despite correctly specifying IPTW, omitting an interaction in the MSM between baseline weight-for-age and time produced increasingly biased estimates as associations between baseline weight-for-age and subsequent weight trajectory increased. Estimates were unbiased when the interaction between baseline weight-for-age and time was included, even if the data were simulated with no such interaction. In ARROW, without an interaction the estimated effect was +0.09 (95%CI +0.02,+0.16) greater weight-for-age gain per month's supplement use; this reduced to +0.03 (-0.04,+0.10) including the interaction. DISCUSSION: This study highlights a specific situation in which MSM model misspecification can occur and impact the resulting estimate. Since an interaction in the MSM (outcome) model does not bias the estimate of effect if the interaction does not exist, it may be advisable to include such a term when fitting MSMs for repeated measures.

Indexed as

Anti-Retroviral AgentsBody WeightChild, PreschoolDietary SupplementsFemaleHIVHIV InfectionsHumansInfantMaleModels, StatisticalNutritional SupportPatient-Specific ModelingResearch DesignWeight GainAnti-Retroviral Agents

Identifiers

PMID32645021
PMCPMC7347189
OpenAlexW3040753575

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.