A sequentially adaptive Bayesian design is presented for a clinical trial of cord blood derived natural killer cells to treat severe hematologic malignancies. Given six prognostic subgroups defined by disease type and severity, the goal is to optimize cell dose in each subgroup. The trial has five co-primary outcomes, the times to severe toxicity, cytokine release syndrome, disease progression or response, and death. The design assumes a multivariate Weibull regression model, with marginals depending on dose, subgroup, and patient frailties that induce association among the event times. Utilities of all possible combinations of the nonfatal outcomes over the first 100 days following cell infusion are elicited, with posterior mean utility used as a criterion to optimize dose. For each subgroup, the design stops accrual to doses having an unacceptably high death rate, and at the end of the trial selects the optimal safe dose. A simulation study is presented to validate the design's safety, ability to identify optimal doses, and robustness, and to compare it to a simplified design that ignores patient heterogeneity.

中文翻译：

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根据多个事件时间优化异质癌症患者的自然杀伤细胞剂量。

提出了一种连续自适应贝叶斯设计，用于脐带血衍生的自然杀伤细胞治疗严重血液恶性肿瘤的临床试验。鉴于根据疾病类型和严重程度定义的六个预后亚组，目标是优化每个亚组中的细胞剂量。该试验有五个共同主要结果：严重毒性的时间、细胞因子释放综合征、疾病进展或反应以及死亡。该设计假设采用多元威布尔回归模型，其边际取决于引起事件时间之间关联的剂量、亚组和患者虚弱程度。得出细胞输注后前 100 天内非致命结果的所有可能组合的效用，并使用后验平均效用作为优化剂量的标准。对于每个亚组，设计停止累积具有不可接受的高死亡率的剂量，并在试验结束时选择最佳安全剂量。提出了一项模拟研究来验证该设计的安全性、确定最佳剂量的能力和稳健性，并将其与忽略患者异质性的简化设计进行比较。