Bayesian Nonparametric Estimation for Dynamic Treatment Regimes with Sequential Transition Times.

ABSTRACT: We analyze a dataset arising from a clinical trial involving multi-stage chemotherapy regimes for acute leukemia. The trial design was a 2 × 2 factorial for frontline therapies only. Motivated by the idea that subsequent salvage treatments affect survival time, we model therapy as a dynamic treatment regime (DTR), that is, an alternating sequence of adaptive treatments or other actions and transition times between disease states. These sequences may vary substantially between patients, depending on how the regime plays out. To evaluate the regimes, mean overall survival time is expressed as a weighted average of the means of all possible sums of successive transitions times. We assume a Bayesian nonparametric survival regression model for each transition time, with a dependent Dirichlet pr

SUBMITTER: Xu Y 

PROVIDER: S-EPMC5175473 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature