Bibliographic Details
| Title: |
U-MET: Utility-Based Dose Optimization Approach for Multiple-Dose Randomized Trial Designs. |
| Authors: |
D’Angelo, Gina1 (AUTHOR) gina.dangelo@astrazeneca.com, Gong, Maozhen2 (AUTHOR), Marshall, Jayne2 (AUTHOR), Yuan, Ying3 (AUTHOR), Li, Xia2 (AUTHOR) |
| Source: |
Statistics in Biopharmaceutical Research. Jun2024, p1-11. 11p. 3 Illustrations, 9 Charts. |
| Abstract: |
AbstractThe advent of dose optimization has led to a paradigm shift in oncology clinical trials to find the optimal biologic dose (OBD). Phase 1/2 trials with randomized doses can facilitate additional investigation of the identified OBD in a targeted population by incorporating safety and efficacy data. We propose to compare randomized doses by extending the Bayesian optimal interval phase 1/2 (BOIN12) approach, an OBD-finding design in which a utility is used to account for risk-benefit tradeoffs. Specifically, we used the BOIN12 standardized mean utilities in a hypothesis testing framework, in which frequentist and Bayesian inference were evaluated to compare the standardized mean utilities across doses and identify the OBD. We performed simulation studies and a hypothetical oncology study to compare the proposed BOIN12 utility-based extension (U-MET) design with an empirical design. The results demonstrated that the U-MET design has satisfactory operating characteristics for selecting the OBD. We recommend using the U-MET design as the primary dose comparison approach, or alternatively as supportive evidence, for optimal dose selection. [ABSTRACT FROM AUTHOR] |
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| Database: |
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