ArticleClinical trials (London, England)2019
Shift models for dose-finding in partially ordered groups.
Article in Clinical trials (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Phase I design for partially ordered groups with late-onset toxicity.Clinical trials (London, England) · 2026Article
- Phase I/II Design for Selecting Subgroup-Specific Optimal Biological Doses for Prespecified Subgroups.Statistics in medicine · 2024Article
- Adaptive Bayesian information borrowing methods for finding and optimizing subgroup-specific doses.Clinical trials (London, England) · 2024Review
- Dose-finding based on feasibility and late-onset toxicity in adoptive cell therapy trials.Journal of biopharmaceutical statistics · 2024Article
- Concurrent dose-finding of a novel cancer drug with and without a second agent.Journal of clinical and translational science · 2023Article
- Stopping rules for phase I clinical trials with dose expansion cohorts.Statistical methods in medical research · 2022Article
- Bayesian Design for Identifying Cohort-Specific Optimal Dose Combinations Based on Multiple Endpoints: Application to a Phase I Trial in Non-Small Cell Lung Cancer.International journal of environmental research and public health · 2021Article
- Precision Bayesian phase I-II dose-finding based on utilities tailored to prognostic subgroups.Statistics in medicine · 2021Article
- Designing Dose-Finding Phase I Clinical Trials: Top 10 Questions That Should Be Discussed With Your Statistician.JCO precision oncology · 2021Article
- Tailoring early-phase clinical trial design to address multiple research objectives.Cancer immunology, immunotherapy : CII · 2020Article
- Consequences of Performing Parallel Dose Finding Trials in Heterogeneous Groups of Patients.JNCI cancer spectrum · 2019Article
- A model-assisted design for partially or completely ordered groups.Pharmaceutical statisticsArticle
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3 authors.
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Abstract
backgroundLimited options are available for dose-finding clinical trials requiring group-specific dose selection. While conducting parallel trials for groups is an accessible approach to group-specific dose selection, this approach allows for maximum tolerated dose selection that does not align with clinically meaningful group order information.
methodsThe two-stage continual reassessment method is developed for dose-finding in studies involving three or more groups where group frailty order is known between some but not all groups, creating a partial order. This is an extension of the existing continual reassessment method shift model for two ordered groups. This method allows for dose selection by group, where maximum tolerated dose selection follows the known frailty order among groups. For example, if a group is known to be the most frail, the recommended maximum tolerated dose for this group should not exceed the maximum tolerated dose recommended for any other group.
resultsWith limited alternatives for dose-finding in partially ordered groups, this method is compared to two alternatives: (1) an existing method for dose-finding in partially ordered groups which is less computationally accessible and (2) independent trials for each group using the two-stage continual reassessment method. Simulation studies show that when ignoring information on group frailty, using independent continual reassessment method trials by group, 30% of simulations would result in maximum tolerated dose selection that is out of order between groups. In addition, the two-stage continual reassessment method for partially ordered groups selects the maximum tolerated dose more often and assigns more patients to the maximum tolerated dose compared to using independent continual reassessment method trials within each group. Simulation results for the proposed method and the less computationally accessible approach are similar.
conclusionThe proposed continual reassessment method for partially ordered groups ensures appropriate maximum tolerated dose order and improves accuracy of maximum tolerated dose selection, while allowing for trial implementation that is computationally accessible.
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