Department of Financial and Actuarial Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, Jiangsu, China.
Sci Rep. 2024 Feb 12;14(1):3483. doi: 10.1038/s41598-024-53155-4.
Combination drugs play an essential role in treating cancers. The challenging part of the combination drugs are to specify the dose-toxicity ordering, which means the sequences of dose escalation and de-escalation in process of dose findings should be pre-determined. In the paper, we extend a novel function of the continual reassessment method based on the combination of the normal distribution for drug-combination dose-finding trials and systematically evaluate its performance using a template of four performance measures EARS (Efficiency, Accuracy, Reliability, Selection). Dose escalation and deescalation rules are based on the nearest neighborhood continual reassessment method for a combination drug, and we specify all possible dose-toxicity orderings in the trial. Simulation demonstrates that the new design is efficient, accurate and reasonably reliable.
联合药物在癌症治疗中起着至关重要的作用。联合药物的挑战部分在于确定剂量-毒性顺序，这意味着在剂量发现过程中应该预先确定剂量递增和递减的顺序。在本文中，我们扩展了一种新的连续评估方法的功能，该方法基于正态分布的组合，用于药物联合剂量发现试验，并使用四个性能指标 EARS（效率、准确性、可靠性、选择）系统地评估其性能。剂量递增和递减规则基于联合药物的最近邻连续评估方法，我们在试验中指定了所有可能的剂量-毒性顺序。模拟表明，新设计是高效、准确和合理可靠的。
