دورية أكاديمية

Use of Multiple Covariates in Assessing Treatment-Effect Modifiers: A Methodological Review of Individual Participant Data Meta-Analyses

التفاصيل البيبلوغرافية
العنوان: Use of Multiple Covariates in Assessing Treatment-Effect Modifiers: A Methodological Review of Individual Participant Data Meta-Analyses
اللغة: English
المؤلفون: Peter J. Godolphin (ORCID 0000-0003-0648-0992), Nadine Marlin (ORCID 0000-0002-2841-4825), Chantelle Cornett (ORCID 0000-0003-3789-0361), David J. Fisher (ORCID 0000-0002-2512-2296), Jayne F. Tierney (ORCID 0000-0002-4734-3014), Ian R. White (ORCID 0000-0002-6718-7661), Ewelina Rogozinska (ORCID 0000-0003-3455-0644)
المصدر: Research Synthesis Methods. 2024 15(1):107-116.
الإتاحة: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 10
تاريخ النشر: 2024
نوع الوثيقة: Journal Articles
Information Analyses
Descriptors: Meta Analysis, Randomized Controlled Trials, Statistical Analysis, Participant Characteristics, Interaction
DOI: 10.1002/jrsm.1674
تدمد: 1759-2879
1759-2887
مستخلص: Individual participant data (IPD) meta-analyses of randomised trials are considered a reliable way to assess participant-level treatment effect modifiers but may not make the best use of the available data. Traditionally, effect modifiers are explored one covariate at a time, which gives rise to the possibility that evidence of treatment-covariate interaction may be due to confounding from a different, related covariate. We aimed to evaluate current practice when estimating treatment-covariate interactions in IPD meta-analysis, specifically focusing on involvement of additional covariates in the models. We reviewed 100 IPD meta-analyses of randomised trials, published between 2015 and 2020, that assessed at least one treatment-covariate interaction. We identified four approaches to handling additional covariates: (1) Single interaction model (unadjusted): No additional covariates included (57/100 IPD meta-analyses); (2) Single interaction model (adjusted): Adjustment for the main effect of at least one additional covariate (35/100); (3) Multiple interactions model: Adjustment for at least one two-way interaction between treatment and an additional covariate (3/100); and (4) Three-way interaction model: Three-way interaction formed between treatment, the additional covariate and the potential effect modifier (5/100). IPD is not being utilised to its fullest extent. In an exemplar dataset, we demonstrate how these approaches lead to different conclusions. Researchers should adjust for additional covariates when estimating interactions in IPD meta-analysis providing they adjust their main effects, which is already widely recommended. Further, they should consider whether more complex approaches could provide better information on who might benefit most from treatments, improving patient choice and treatment policy and practice.
Abstractor: As Provided
Entry Date: 2024
رقم الأكسشن: EJ1405344
قاعدة البيانات: ERIC