Adaptive Optimal Designs for Dose-Finding Studies with Time-to-Event Outcomes

Yevgen Ryeznik, Oleksandr Sverdlov, Andrew C. Hooker
2017 AAPS Journal  
We consider optimal design problems for dose-finding studies with censored Weibull time-to-event outcomes. Locally D-optimal designs are investigated for a quadratic dose-response model for log-transformed data subject to right censoring. Two-stage adaptive D-optimal designs using maximum likelihood estimation (MLE) model updating are explored through simulation for a range of different dose-response scenarios and different amounts of censoring in the model. The adaptive optimal designs are
more » ... d to be nearly as efficient as the locally D-optimal designs. A popular equal allocation design can be highly inefficient when the amount of censored data is high and when the Weibull model hazard is increasing. The issues of sample size planning/early stopping for an adaptive trial are investigated as well. The adaptive D-optimal design with early stopping can potentially reduce study size while achieving similar estimation precision as the fixed allocation design.
doi:10.1208/s12248-017-0166-5 pmid:29285730 fatcat:as4felkndrf67abx2o4h2neuza