Investigating treatment-effect modification by a continuous covariate in IPD meta-analysis: an approach using fractional polynomials.

ABSTRACT:

Background

In clinical trials, there is considerable interest in investigating whether a treatment effect is similar in all patients, or that one or more prognostic variables indicate a differential response to treatment. To examine this, a continuous predictor is usually categorised into groups according to one or more cutpoints. Several weaknesses of categorization are well known. To avoid the disadvantages of cutpoints and to retain full information, it is preferable to keep continuous variables continuous in the analysis. To handle this issue, the Subpopulation Treatment Effect Pattern Plot (STEPP) was proposed about two decades ago, followed by the multivariable fractional polynomial interaction (MFPI) approach. Provided individual patient data (IPD) from several studies are a

SUBMITTER: Sauerbrei W 

PROVIDER: S-EPMC8985287 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature