Bayesian Dose-Finding Phase I Trial Design Incorporating Historical Data from a Preceding Trial. Takeda, K. and Morita, S. Pharm Stat.
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We consider the problem of incorporating historical data from a preceding trial to design and conduct a subsequent dose-finding trial in a possibly different population of patients. In oncology, for example, after a phase I dose-finding trial is completed in Caucasian patients, investigators often conduct a further phase I trial to determine the maximum tolerated dose in Asian patients. This may be due to concerns about possible differences in treatment tolerability between populations. In this study, we propose to adaptively incorporate historical data into prior distributions assumed in a new dose-finding trial. Our proposed approach aims to appropriately borrow strength from a previous trial to improve the maximum tolerated dose determination in another patient population. We define a '' historical-to-current (H-C)'' parameter representing the degree of borrowing based on a retrospective analysis of previous trial data. In simulation studies, we examine the operating characteristics of the proposed method in comparison with 3 alternative approaches and assess how the H-C parameter functions across a variety of realistic settings.
@article{tak18bay,
  title = {Bayesian Dose-Finding Phase {{I}} Trial Design Incorporating Historical Data from a Preceding Trial},
  abstract = {We consider the problem of incorporating historical data from a preceding trial to design and conduct a subsequent dose-finding trial in a possibly different population of patients. In oncology, for example, after a phase I dose-finding trial is completed in Caucasian patients, investigators often conduct a further phase I trial to determine the maximum tolerated dose in Asian patients. This may be due to concerns about possible differences in treatment tolerability between populations. In this study, we propose to adaptively incorporate historical data into prior distributions assumed in a new dose-finding trial. Our proposed approach aims to appropriately borrow strength from a previous trial to improve the maximum tolerated dose determination in another patient population. We define a '' historical-to-current (H-C)'' parameter representing the degree of borrowing based on a retrospective analysis of previous trial data. In simulation studies, we examine the operating characteristics of the proposed method in comparison with 3 alternative approaches and assess how the H-C parameter functions across a variety of realistic settings.},
  journal = {Pharm Stat},
  doi = {10.1002/pst.1850},
  author = {Takeda, Kentaro and Morita, Satoshi},
  keywords = {bayes,bayesian-inference,drug-development,dose-response,historical-data},
  pages = {n/a},
  citeulike-article-id = {14523898},
  citeulike-linkout-0 = {http://dx.doi.org/10.1002/pst.1850},
  posted-at = {2018-01-26 19:15:59},
  priority = {2}
}
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