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Abstract:
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The primary objective of phase I oncology studies is to establish the safety profile of a new treatment and determine the maximum tolerated dose (MTD). This is motivated by the development of cytotoxic agents based on the underlying assumption that the higher the dose, the greater the likelihood of efficacy and toxicity. However, evidence from the recent development of cancer immunotherapies that aim to stimulate patients’ immune systems to fight cancer challenges this assumption, particularly further escalation after certain dose level might not necessarily increase the efficacy. Dose escalation study of molecular targeted agents (MTA) often does not only rely on the safety profile. In this paper, we propose a simple and flexible model that uses multivariate Gaussian latent variable to integrate toxicity endpoint and efficacy biomarker. This model can be easily extended to incorporate additional immune biomarkers. By simultaneously considering multiple outcomes, the proposed method is better to identify the biologically optimal dose, which results in better decision-making. Simulation studies showed that the proposed method has desirable operating characteristics by determining the target dose with an optimal risk-benefit trade-off. We have also implemented our proposed method in a user-friendly R Shiny tool.
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