Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA 30322, USA.
Contemp Clin Trials. 2012 Sep;33(5):949-58. doi: 10.1016/j.cct.2012.04.007. Epub 2012 Apr 25.
Escalation with overdose control (EWOC) is a Bayesian adaptive design for selecting dose levels in cancer Phase I clinical trials while controlling the posterior probability of exceeding the maximum tolerated dose (MTD). EWOC has been used by clinicians to design many cancer Phase I clinical trials, see e.g. [1-4]. However, this design treats the toxicity response as a binary indicator of dose limiting toxicity (DLT) and does not account for the number and specific grades of toxicities experienced by patients during the trial. Chen et al. (2010) proposed a novel toxicity score system to fully utilize all toxicity information using a normalized equivalent toxicity score (NETS). In this paper, we propose to incorporate NETS into EWOC using a quasi-Bernoulli likelihood approach to design cancer Phase I clinical trials. We call the design escalation with overdose control using normalized equivalent toxicity score (EWOC-NETS). Simulation results show that this design has good operating characteristics and improves the accuracy of MTD, trial efficiency, therapeutic effect, and overdose control relative to EWOC which is used as a representative of designs treating toxicity response as a binary indicator of DLT. We illustrate the performance of this design using real trial data in identifying the Phase II dose.
递增式超量控制(EWOC)是一种贝叶斯自适应设计,用于在癌症 I 期临床试验中选择剂量水平,同时控制超过最大耐受剂量(MTD)的后验概率。EWOC 已被临床医生用于设计许多癌症 I 期临床试验,例如 [1-4]。然而,该设计将毒性反应视为剂量限制性毒性(DLT)的二进制指标,并未考虑到患者在试验期间经历的毒性数量和具体等级。Chen 等人(2010 年)提出了一种新的毒性评分系统,通过使用归一化等效毒性评分(NETS)充分利用所有毒性信息。在本文中,我们建议使用拟贝叶斯似然方法将 NETS 纳入 EWOC 中,以设计癌症 I 期临床试验。我们将其称为使用归一化等效毒性评分的递增式超量控制(EWOC-NETS)。模拟结果表明,与将毒性反应视为 DLT 的二进制指标的 EWOC 相比,该设计具有良好的操作特性,并提高了 MTD、试验效率、治疗效果和超量控制的准确性。我们使用真实试验数据来确定 II 期剂量,说明了该设计的性能。