Analysis of time-to-event data using a flexible mixture model under a constraint of proportional hazards
Analysis of time-to-event data using a flexible mixture model under a constraint of proportional hazards
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DOI：
10.1080/10543406.2020.1783283
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发表时间：
2020-06-28
影响因子：
1.1
通讯作者：
Liao, Jason J. Z.
中科院分区：
文献类型：
--
作者：
Liu, Guanghan Frank;Liao, Jason J. Z.
Cox比例风险(PH)模型在PH假设下评估感兴趣的协变量的影响，而不指定基线风险。然而，在临床试验应用中，每个治疗组的明确估计的风险或累积生存函数有助于评估和解释治疗差异的意义。在本文中，我们提出了在PH约束下使用一种灵活的混合模型来拟合下划线生存函数。仿真结果表明，该混合PH模型在估计风险比、偏差、可信区间覆盖率、I类误差和检验功率等方面与Cox PH模型非常相似。对几个实际临床试验实例的应用表明，该方法得到的结果与COX PH模型的结果基本一致。每个处理组的明确估计的危险函数提供了额外的有用信息，并有助于解释危险比较。
Cox proportional hazards (PH) model evaluates the effects of interested covariates under PH assumption without specified the baseline hazard. In clinical trial applications, however, the explicitly estimated hazard or cumulative survival function for each treatment group helps to assess and interpret the meaning of treatment difference. In this paper, we propose to use a flexible mixture model under the PH constraint to fit the underline survival functions. Simulations are conducted to evaluate its performance and show that the proposed mixture PH model is very similar to the Cox PH model in terms of estimating the hazard ratio, bias, confidence interval coverage, type-I error and testing power. Application to several real clinical trial examples demonstrates that the results from this approach are almost identical to the results from Cox PH model. The explicitly estimated hazard function for each treatment group provides additional useful information and helps the interpretation of hazard comparisons.