Identifying treatment effect heterogeneity in clinical trials using subpopulations of events: STEPP.

ABSTRACT:

Background

Investigators conducting randomized clinical trials often explore treatment effect heterogeneity to assess whether treatment efficacy varies according to patient characteristics. Identifying heterogeneity is central to making informed personalized healthcare decisions. Treatment effect heterogeneity can be investigated using subpopulation treatment effect pattern plot (STEPP), a non-parametric graphical approach that constructs overlapping patient subpopulations with varying values of a characteristic. Procedures for statistical testing using subpopulation treatment effect pattern plot when the endpoint of interest is survival remain an area of active investigation.

Methods

A STEPP analysis was used to explore patterns of absolute and relative treatment effects fo

SUBMITTER: Lazar AA 

PROVIDER: S-EPMC5563513 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature