CUSUMIN Combination: A Cumulative Sum Interval Design for Phase I Cancer Drug‐Combination Trials
Year: 2025
Type: article
Abstract: Recently, model-assisted designs, including a Bayesian optimal interval (BOIN) design with optimal thresholds for determining the dose for the next cohort, have been proposed for Phase I cancer studies. Model-assisted designs are useful owing to their good performance in addition to their algorithm-based simplicity. In this era of precision medicine, drug combinations are widely used to enhance treatment efficacy and overcome resistance to monotherapies. However, identification of maximum tolerated dose (MTD) combinations is complicated because the joint toxicity order of paired doses is only partially known. BOIN and Keyboard combination designs are the only model-assisted designs developed to date. Further, both these combination designs show similar operational characteristics. Despite the simplicity and superior performance of model-assisted designs, they have not been sufficiently studied in Phase I drug combination trials. In this study, to provide a new design with simplicity and superior performance compared to model-assisted designs for dose-combination cancer Phase I studies, we extend the cumulative sum interval design (CUSUMIN) developed for single-agent dose-finding design based on statistical quality control methodology, which improves on BOIN and other representative model-assisted designs in terms of controlling overdosing rates while maintaining similar performance in determining the MTD. CUSUMIN can be expected to provide a safer assignment than that of BOIN in drug combination dose-finding studies while maintaining MTD selection performance, as shown in the single-agent dose-finding settings.
Source: Pharmaceutical Statistics
DOI: 10.1002/pst.70007
Authors: Tomoyoshi Hatayama, Seiichi Yasui
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409501846