A Generalized Phase I/II Dose Optimization Trial Design With Multi‐Categorical and Multi‐Graded Outcomes
Pursuing accurate observations and rational assumptions always drives advances in clinical trial design. In recent years, more trials have begun to collect multi-graded outcomes for more informative analyses. At the same time, assumptions other than the traditional monotonicity relationship have been considered in the dose-efficacy curve to be more realistic. Inspired by these two trends, we propose a phase I/II design that simultaneously considers multi-categorical toxicity and efficacy with multi-graded outcomes, measured as quasi-continuous probability based on prespecified weight matrices of clinical significance. Following keyboard design, our approach aims to screen out overly toxic doses by the toxicity probability intervals and adaptively makes dose escalation or de-escalation decisions by comparing the posterior distributions of dose desirability (utility) among the adjacent levels of the current dose. It helps to more accurately identify the OBD in a non-monotonically increasing dose-efficacy relationship. We also comprehensively present the safety, accuracy and reliability performance through numerical simulations in multiple scenarios and compare the results with several already available designs. The benchmarking results of multiple operating characteristics convincingly support that our design leads in overall performance while ensuring robustness.
Authors
- Yichen Yan (ORCID: https://orcid.org/0000-0002-0717-3962)
- Ruitao Lin (ORCID: https://orcid.org/0000-0003-2244-131X)
- Xiaolei Lin (ORCID: https://orcid.org/0000-0003-2463-1272)
- Haolun Shi (ORCID: https://orcid.org/0000-0002-3620-9717)
- Tianyu Guan
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- Simon Fraser University (CA)
- York University (CA)
- Fudan University (CN)
Publication Details
- Journal
- Statistics in Medicine
- Published
- 2025-03-30
- DOI
- https://doi.org/10.1002/sim.70049
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Sciences and Engineering Research Council of Canada