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A generalized phase 1-2-3 design integrating dose optimization with confirmatory treatment comparison.
Zang, Yong; Thall, Peter F; Yuan, Ying.
Affiliation
  • Zang Y; Department of Biostatistics and Health Data Science; Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN 46202, United States.
  • Thall PF; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
  • Yuan Y; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States.
Biometrics ; 80(1)2024 Jan 29.
Article in En | MEDLINE | ID: mdl-38364811
ABSTRACT
A generalized phase 1-2-3 design, Gen 1-2-3, that includes all phases of clinical treatment evaluation is proposed. The design extends and modifies the design of Chapple and Thall (2019), denoted by CT. Both designs begin with a phase 1-2 trial including dose acceptability and optimality criteria, and both select an optimal dose for phase 3. The Gen 1-2-3 design has the following key differences. In stage 1, it uses phase 1-2 criteria to identify a set of candidate doses rather than 1 dose. In stage 2, which is intermediate between phase 1-2 and phase 3, it randomizes additional patients fairly among the candidate doses and an active control treatment arm and uses survival time data from both stage 1 and stage 2 patients to select an optimal dose. It then makes a Go/No Go decision of whether or not to conduct phase 3 based on the predictive probability that the selected optimal dose will provide a specified substantive improvement in survival time over the control. A simulation study shows that the Gen 1-2-3 design has desirable operating characteristics compared to the CT design and 2 conventional designs.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Research Design Limits: Humans Language: En Journal: Biometrics Year: 2024 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Research Design Limits: Humans Language: En Journal: Biometrics Year: 2024 Document type: Article Affiliation country: