ArticleStatistics in biopharmaceutical research2024
MT-Keyboard: A Bayesian Model-assisted Interval Design to Account for Toxicity Grades and Types for Phase I Trials.
Article in Statistics in biopharmaceutical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
3 authors.
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Abstract
Conventionally, dose finding trials are based on dose-limiting toxicity (DLT) that only captures the most severe toxicities, e.g., treatment related grade 3 or higher toxicity according to the NCI Common Terminology Criteria for Adverse Events. However, this approach is often problematic for certain novel targeted therapies and immunotherapies, which may not induce DLT within a clinically active dose range and are often characterized by low grade toxicities. This important issue has been highlighted and discussed in the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forums, and is also an important consideration of the Project Optimus initiated by FDA to "reform the dose optimization and dose selection paradigm in oncology drug development." In this paper, we propose an easy-to-implement model-assisted Bayesian design, known as multiple toxicity keyboard (MT-Keyboard) design, to incorporate toxicity grades and types into dose finding. The MT-Keyboard design is able to accommodate binary, quasi-binary and continuous toxicity endpoints that are constructed to account for toxicity grades and types. We further extend the MT-Keyboard design, referred to as TITE-MT-Keyboard, to accommodate late-onset toxicity using the approximated likelihood approach. Simulation shows that the MT-Keyboard and TITE-MT-Keyboard designs have desirable operating characteristics, comparable to or better than some existing designs. A web-based software to implement the design will be freely available at www.trialdesign.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.