Biostatistics and Bioinformatics Monthly Seminar with Peter F. Thall, PhD
Generalized Phase 1-2 Designs to Maximize Long Term Therapeutic Success Rate
Peter F. Thall, PhD
Anise J. Sorrell Professor
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
Meeting ID: 826 0218 1731
Passcode: 3YHck8g8
Abstract:
While phase 1-2 dose-finding designs are greatly superior to phase I designs due to the use of both response and toxicity, a severe limitation is that early response is not a surrogate for long-term therapeutic success in terms of remission duration, progression free survival, or overall survival time. In oncology, this typically is due to high rates of disease recurrence following response. This talk will present a new family of modular Bayesian “generalized phase 1-2” designs that address this problem. First, a conventional phase 1-2 design is used to identify a set of candidate doses, rather than selecting one dose, additional patients are randomized among the candidates, all patients are followed for a longer time period and a final dose is selected to maximize the long-term therapeutic success rate. The design was motivated by a trial of natural killer cells as targeted immunotherapy for recurrent or treatment-resistant B-cell hematologic malignancies. A simulation study shows that a generalized phase I-II design has much better performance than comparable conventional phase 1-2 designs.
This group meets monthly from Noon – 1 p.m.