Statistical inference for cancer trials with treatment switching.
In cancer clinical trials, it is not uncommon that some patients switched their treatments due to lack of efficacy and/or disease progression under ethical consideration. This treatment switch makes it difficult for the evaluation of the efficacy of the treatment under investigation. The current existing methods consider random treatment switch and do not take into consideration of prognosis and/or investigator's assessment that leads to patients' treatment switch. In this paper, we model patients' treatment switching effect in a latent event times model under parametric setting or a latent hazard rate model under the semi-parametric proportional hazard model. Statistical inference procedures under both models are provided. A simulation study is performed to investigate the performance of the proposed methods.
Shao
Jun
J
University of Wisconsin, Madison, WI 53706, USA. shao@stat.wisc.edu
Chang
Mark
M
Chow
Shein-Chung
SC
D000970:Antineoplastic Agents / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000941:ethics / Q000706:statistics & numerical data*; D015507:Drugs, Investigational / Q000627:therapeutic use; D006801:Humans; D009369:Neoplasms / Q000188:drug therapy*; D016016:Proportional Hazards Models; D016896:Treatment Outcome; D014481:United States; D028761:Withholding Treatment / Q000941:ethics
D000970:Antineoplastic Agents; D015507:Drugs, Investigational