Evaluation of treatment-effect heterogeneity using biomarkers measured on a continuous scale: subpopulation treatment effect pattern plot.

ABSTRACT: The discovery of biomarkers that predict treatment effectiveness has great potential for improving medical care, particularly in oncology. These biomarkers are increasingly reported on a continuous scale, allowing investigators to explore how treatment efficacy varies as the biomarker values continuously increase, as opposed to using arbitrary categories of expression levels resulting in a loss of information. In the age of biomarkers as continuous predictors (eg, expression level percentage rather than positive v negative), alternatives to such dichotomized analyses are needed. The purpose of this article is to provide an overview of an intuitive statistical approach-the subpopulation treatment effect pattern plot (STEPP)-for evaluating treatment-effect heterogeneity when a biomarker is m

SUBMITTER: Lazar AA 

PROVIDER: S-EPMC2988642 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature