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Sample size calculation for the proportional hazards cure model

机译:比例危害治愈模型的样本量计算

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In clinical trials with time-to-event endpoints, it is not uncommon to see a significant proportion of patients being cured (or long-term survivors), such as trials for the non-Hodgkins lymphoma disease. The popularly used sample size formula derived under the proportional hazards (PH) model may not be proper to design a survival trial with a cure fraction, because the PH model assumption may be violated. To account for a cure fraction, the PH cure model is widely used in practice, where a PH model is used for survival times of uncured patients and a logistic distribution is used for the probability of patients being cured. In this paper, we develop a sample size formula on the basis of the PH cure model by investigating the asymptotic distributions of the standard weighted log-rank statistics under the null and local alternative hypotheses. The derived sample size formula under the PH cure model is more flexible because it can be used to test the differences in the short-term survival and/or cure fraction. Furthermore, we also investigate as numerical examples the impacts of accrual methods and durations of accrual and follow-up periods on sample size calculation. The results show that ignoring the cure rate in sample size calculation can lead to either underpowered or overpowered studies. We evaluate the performance of the proposed formula by simulation studies and provide an example to illustrate its application with the use of data from a melanoma trial.
机译:在具有到达事件发生时间终点的临床试验中,看到相当一部分患者被治愈(或长期幸存者)的情况并不少见,例如非霍奇金淋巴瘤疾病试验。在比例风险(PH)模型下得出的普遍使用的样本量公式可能不适用于设计具有治愈分数的生存试验,因为可能会违反PH模型的假设。为了解决治愈率问题,PH治愈模型在实践中被广泛使用,其中PH模型用于未治愈患者的生存时间,对数分布用于患者治愈的可能性。在本文中,我们通过调查在零假设和局部假设下标准加权对数秩统计量的渐近分布,在PH治愈模型的基础上建立了样本量公式。 PH固化模型下得出的样本量公式更灵活,因为它可用于测试短期存活率和/或固化分数的差异。此外,我们还以数值示例形式研究应计方法,应计持续时间和后续期间对样本量计算的影响。结果表明,在样本量计算中忽略治愈率可能导致研究不足或研究过重。我们通过仿真研究评估了拟议公式的性能,并提供了一个实例来说明其在黑色素瘤试验数据中的应用。

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