Adaptive Design with Bayesian Informed Interim Decisions: Application To a Randomized Trial of Mechanical Circulatory Support
For clinical trials with time-to-event endpoints and where crossing of survival curves might be anticipated at the planning stage, flexible modeling along with wholesome use of patient-level data such as the calculation of predictive power as proposed here, may be more robust and efficient in making interim decisions such as sample size increase than the traditional use of the conditional power based on summary statistics and proportional hazards assumption.
Authors
- C R Mehta (ORCID: https://orcid.org/0000-0002-5468-1185)
- Gregg W. Stone (ORCID: https://orcid.org/0000-0002-3416-8210)
- Rajat Mukherjee (ORCID: https://orcid.org/0000-0001-7905-2767)
- Yi Qin Gao (ORCID: https://orcid.org/0000-0002-4309-9376)
- Natalia Muehlemann (ORCID: https://orcid.org/0000-0001-5167-904X)
Institutions
- Boston University (US)
- Harvard University (US)
- Cardiovascular Institute of the South (US)
- Mount Sinai Hospital (US)
- Museu d'Arqueologia de Catalunya (ES)
- Abiomed (United States) (US)
- Cytel (United States) (US)
Publication Details
- Journal
- Therapeutic Innovation & Regulatory Science
- Published
- 2025-08-16
- DOI
- https://doi.org/10.1007/s43441-025-00861-4
- Primary Topic
- Statistical Methods in Clinical Trials
- Type
- article
- Field-Weighted Citation Impact
- 0.00