Utility-based Bayesian personalized treatment selection for advanced breast cancer.

ABSTRACT: A Bayesian method is proposed for personalized treatment selection in settings where data are available from a randomized clinical trial with two or more outcomes. The motivating application is a randomized trial that compared letrozole plus bevacizimab to letrozole alone as first-line therapy for hormone receptor positive advanced breast cancer. The combination treatment arm had larger median progression-free survival time, but also a higher rate of severe toxicities. This suggests that the risk-benefit trade-off between these two outcomes should play a central role in selecting each patient's treatment, particularly since older patients are less likely to tolerate severe toxicities. To quantify the desirability of each possible outcome combination for an individual patient, we elicited f

SUBMITTER: Lee J 

PROVIDER: S-EPMC9880964 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature