标题： 混合生存模型方法：在临床试验中癌症免疫治疗评估的应用 显示英文标题

标题： Mixture survival models methodology: an application to cancer immunotherapy assessment in clinical trials

摘要： 免疫疗法的进步彻底改变了晚期肺癌的治疗格局，使患者的生存期望超过了以往对该疾病所预期的水平。 在本研究中，我们描述了在存在长期存活者的情况下，对两个群体的混合参数模型进行调整的方法，用于生存分析。 提出了一种分五个步骤的方法：首先，建议使用多峰性检验来决定模型中应考虑的亚群体数量；其次，调整简单的参数生存模型和混合分布模型，估计参数并选择最适合数据的模型；最后，在随机临床试验的背景下，测试假设以比较免疫疗法的有效性。 该方法通过一项评估治疗性疫苗CIMAvaxEGF与最佳支持治疗在晚期肺癌治疗中的有效性的临床试验数据进行了说明。 混合生存模型可以估计接种疫苗患者中长期存活亚群体的存在，比例为44%。 在两个亚群体中，治疗组和对照组之间的差异具有统计学意义（短期生存亚群体：p = 0.001，长期生存亚群体：p = 0.0002）。 对于癌症治疗而言，由于一部分患者能够实现疾病的长期控制，必须考虑人群的异质性。 相比于标准模型，混合参数模型可能更适合检测免疫疗法的效果。 显示英文摘要

摘要： Progress in immunotherapy revolutionized the treatment landscape for advanced lung cancer, raising survival expectations beyond those that were historically anticipated with this disease. In the present study, we describe the methods for the adjustment of mixture parametric models of two populations for survival analysis in the presence of long survivors. A methodology is proposed in several five steps: first, it is proposed to use the multimodality test to decide the number of subpopulations to be considered in the model, second to adjust simple parametric survival models and mixture distribution models, to estimate the parameters and to select the best model fitted the data, finally, to test the hypotheses to compare the effectiveness of immunotherapies in the context of randomized clinical trials. The methodology is illustrated with data from a clinical trial that evaluates the effectiveness of the therapeutic vaccine CIMAvaxEGF vs the best supportive care for the treatment of advanced lung cancer. The mixture survival model allows estimating the presence of a subpopulation of long survivors that is 44% for vaccinated patients. The differences between the treated and control group were significant in both subpopulations (population of short-term survival: p = 0.001, the population of long-term survival: p = 0.0002). For cancer therapies, where a proportion of patients achieves long-term control of the disease, the heterogeneity of the population must be taken into account. Mixture parametric models may be more suitable to detect the effectiveness of immunotherapies compared to standard models.