Toxicity Adaptive Lists Design: A Practical Design for Phase I Drug Combination Trials in Oncology.
| Autor: | Russo M; Department of Statistics, The Ohio State University, Columbus, OH., Mariani F; Dipartimento di Scienze Statistiche, Sapienza University of Rome, Rome, Italy., Cleary JM; Dana-Farber Cancer Institute, Boston, MA.; Harvard Medical School, Boston, MA., Shapiro GI; Dana-Farber Cancer Institute, Boston, MA.; Harvard Medical School, Boston, MA., Coté GM; Harvard Medical School, Boston, MA.; Mass General Cancer Center, Boston, MA., Trippa L; Dana-Farber Cancer Institute, Boston, MA.; T.H. Chan School of Public Health, Harvard University, Cambridge, MA. |
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| Jazyk: | angličtina |
| Zdroj: | JCO precision oncology [JCO Precis Oncol] 2024 Oct; Vol. 8, pp. e2400275. Date of Electronic Publication: 2024 Oct 21. |
| DOI: | 10.1200/PO.24.00275 |
| Abstrakt: | Purpose: We introduce a novel algorithmic approach to design phase I trials for oncology drug combinations. Methods: Our proposed Toxicity Adaptive Lists Design (TALE) is straightforward to implement, requiring the prespecification of a small number of parameters that define rules governing dose escalation, de-escalation, or reassessment of previously explored dose levels. These rules effectively regulate dose exploration and control the number of toxicities. A key feature of TALE is the possibility of simultaneous assignment of multiple-dose combinations that are deemed safe by previously accrued data. Results: A numerical study shows that TALE shares comparable operative characteristics, in terms of identification of the maximum tolerated dose (MTD), to alternative approaches such as the Bayesian optimal interval design, the COPULA, the product of independent beta probabilities escalation, and the continual reassessment method for partial ordering designs while reducing the risk of overdosing patients. Conclusion: The proposed TALE design provides a favorable balance between maintaining patient safety and accurately identifying the MTD. To facilitate the use of TALE, we provide a user-friendly R Shiny application and an R package for computing relevant operating characteristics, such as the risk of assigning highly toxic dose combinations. |
| Databáze: | MEDLINE |
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