Challenges of Modeling Biomarker Effects on Time-to-Event Outcomes

Biomarkers, which may offer insights into the potential benefit in the clinical outcome for an experimental treatment, play a critical role in early phase drug development before large, time-consuming, and expensive phase 3 trials are conducted. Evaluating the impact of a biomarker on a time-to-event clinical outcome could be challenging as it is difficult to model the temporal relationship between the biomarker and the clinical outcome. We demonstrate through simulation that directly incorporating the biomarker as a covariate into a Cox proportional hazards model may lead to an attenuated relationship between the biomarker and the clinical outcome when there is a delayed biomarker effect on the clinical outcome. Although we do not provide a sophisticated way to model the delayed temporal relationship between the biomarker and the clinical outcome, understanding the limitations of conventional methods should help guide decision-making. Future research is needed on how to improve statistical models in evaluating the impact of biomarkers on time-to-event clinical outcomes.