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.

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，但未指定基线风险。然而，在临床试验应用中，每个治疗组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含义。在本文中，我们建议在 PH 约束下使用灵活的混合模型来拟合下划线生存函数。进行了模拟以评估其性能，并表明所提出的混合 PH 模型在估计风险比、偏差、置信区间覆盖率、I 类错误和测试能力方面与 Cox PH 模型非常相似。应用于几个真实的临床试验实例表明，这种方法的结果与 Cox PH 模型的结果几乎相同。