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Impact of the PATH Statement on Analysis and Reporting of Heterogeneity of Treatment Effect in Clinical Trials: A Scoping Review.
Selby, Joe V; Maas, Carolien C H M; Fireman, Bruce H; Kent, David M.
Afiliação
  • Selby JV; Division of Research, Kaiser Permanente Northern California, Oakland, CA (emeritus).
  • Maas CCHM; Tufts Predictive Analytics and Comparative Effectiveness Center, Tufts University School of Medicine, Boston MA.
  • Fireman BH; Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands.
  • Kent DM; Division of Research, Kaiser Permanente Northern California, Oakland, CA.
medRxiv ; 2024 May 06.
Article em En | MEDLINE | ID: mdl-38766150
ABSTRACT

Background:

The Predictive Approaches to Treatment Effect Heterogeneity (PATH) Statement provides guidance for using predictive modeling to identify differences (i.e., heterogeneity) in treatment effects (benefits and harms) among participants in randomized clinical trials (RCTs). It distinguished risk modeling, which uses a multivariable model to predict risk of trial outcome(s) and then examines treatment effects within strata of predicted risk, from effect modeling, which predicts trial outcomes using models that include treatment, individual participant characteristics and interactions of treatment with selected characteristics.

Purpose:

To describe studies of heterogeneous treatment effects (HTE) that use predictive modeling in RCT data and cite the PATH Statement. Data Sources The Cited By functions in PubMed, Google Scholar, Web of Science and SCOPUS databases (Jan 7, 2020 - June 5, 2023). Study Selection 42 reports presenting 45 predictive models. Data Extraction Double review with adjudication to identify risk and effect modeling and examine consistency with Statement consensus statements. Credibility of HTE findings was assessed using criteria adapted from the Instrument to assess Credibility of Effect Modification Analyses (ICEMAN). Clinical importance of credible HTE findings was also assessed. Data

Synthesis:

The numbers of reports, especially risk modeling reports, increased year-on-year. Consistency with consensus statements was high, except for two only 15 of 32 studies with positive overall findings included a risk model; and most effect models explored many candidate covariates with little prior evidence for effect modification. Risk modeling was more likely than effect modeling to identify both credible HTE (14/19 vs 5/26) and clinically important HTE (10/19 vs 4/26).

Limitations:

Risk of reviewer bias reviewers assessing credibility and clinical importance were not blinded to adherence to PATH recommendations.

Conclusions:

The PATH Statement appears to be influencing research practice. Risk modeling often uncovered clinically important HTE; effect modeling was more often exploratory.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: MedRxiv Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: MedRxiv Ano de publicação: 2024 Tipo de documento: Article