Barnett, Helen and Boix, Oliver and Kontos, Dimitris and Jaki, Thomas (2022) Dose finding studies for therapies with late-onset toxicities: A comparison study of designs. STATISTICS IN MEDICINE, 41 (30). pp. 5767-5788. ISSN 0277-6715, 1097-0258
Full text not available from this repository. (Request a copy)Abstract
An objective of phase I dose-finding trials is to find the maximum tolerated dose; the dose with a particular risk of toxicity. Frequently, this risk is assessed across the first cycle of therapy. However, in oncology, a course of treatment frequently consists of multiple cycles of therapy. In many cases, the overall risk of toxicity for a given treatment is not fully encapsulated by observations from the first cycle, and hence it is advantageous to include toxicity outcomes from later cycles in phase I trials. Extending the follow up period in a trial naturally extends the total length of the trial which is undesirable. We present a comparison of eight methods that incorporate late onset toxicities while not extensively extending the trial length. We conduct simulation studies over a number of scenarios and in two settings; the first setting with minimal stopping rules and the second setting with a full set of standard stopping rules expected in such a dose finding study. We find that the model-based approaches in general outperform the model-assisted approaches, with an interval censored approach and a modified version of the time-to-event continual reassessment method giving the most promising overall performance in terms of correct selections and trial length. Further recommendations are made for the implementation of such methods.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | PHASE-I TRIALS; BAYESIAN-APPROACH; dose-finding; late-onset toxicities; model-assisted; model-based; phase I trials |
| Subjects: | 000 Computer science, information & general works > 004 Computer science |
| Divisions: | Informatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 22 Feb 2024 13:54 |
| Last Modified: | 22 Feb 2024 13:54 |
| URI: | https://pred.uni-regensburg.de/id/eprint/57743 |
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