Measuring differential treatment benefit across marker specific subgroups: The choice of outcome scale.

ABSTRACT: Clinical and epidemiological studies of anticancer therapies increasingly seek to identify predictive biomarkers to obtain insights into variation in treatment benefit. For time to event endpoints, a predictive biomarker is typically assessed using the interaction between the biomarker and treatment in a proportional hazards model. Interactions are contrasts of summaries of outcomes and depend upon the choice of the outcome scale. In this paper, we investigate interaction contrasts under three scales - the natural logarithm of hazard ratio, the natural logarithm of survival probability, and survival probability at a pre-specified time. We illustrate that we can have a non-zero interaction on survival or logarithm of survival probability scales even when there is no interaction on the logar

SUBMITTER: Satagopan JM 

PROVIDER: S-EPMC5568905 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature