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Optimal response‐adaptive randomized designs for multi‐armed survival trials
Author(s) -
Sverdlov Oleksandr,
Tymofyeyev Yevgen,
Wong Weng Kee
Publication year - 2011
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4331
Subject(s) - optimal design , computer science , sample size determination , robustness (evolution) , mathematical optimization , adaptive design , clinical trial , mathematics , statistics , medicine , machine learning , biochemistry , chemistry , pathology , gene
We considered design issues for multiple treatment arms in survival intervention trials and used optimal design theory to allocate patients adaptively in such trials. We proposed three types of optimal designs: one ensures that we have the most precise estimates of the treatment effects, another guarantees that we have the minimal sample size subject to user‐specified allocation ratio assignments among treatment arms, and the third ensures that the design has minimal total hazard for the cohort. The latter two types of optimal designs are also subject to user‐specified power constraints for testing contrasts among treatment effects. The operating characteristics of these optimal designs along with balanced designs are compared theoretically and by simulation, including their robustness properties with respect to model misspecifications. Our results show that the proposed optimal designs are frequently unbalanced and that they are generally more efficient and more ethical than the popular balanced designs. We also apply our response‐adaptive allocation strategy to redesign a three‐arm head and neck cancer trial and make comparisons. Copyright © 2011 John Wiley & Sons, Ltd.