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Estimating baseline distribution in proportional hazards cure models

机译:在比例风险治愈模型中估计基线分布

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Semiparametric proportional hazards cure models have been proposed recently for survival data from some clinical trials where cure is a possibility. However, it is known that the estimated baseline distribution in the proposed methods will not be proper if there is no restriction on the tail of the distribution, which leads to the identifiability problem. IN this work, we investigate several methods that impose restrictions on the tail of the baseline distribution. A simulation study shows that the proposed methods are useful in reducing estimation errors in the cure models. The impact of the different methods on the estimation of regression parameters and survival probabilities of patients who are not cured is detailed in the paper. The results provide useful guidelines for practitioners to select appropriate estimation methods for the semiparametric cure model. The application of the results is illustrated with a real data set from a clinical trial of breast cancer.
机译:最近已经提出了半参数比例风险治愈模型,用于一些可能治愈的临床试验中的生存数据。然而,众所周知,如果对分布的尾部没有限制,则在所提出的方法中估计的基线分布将是不合适的,这导致了可识别性问题。在这项工作中,我们研究了对基线分布的尾部施加限制的几种方法。仿真研究表明,所提出的方法可用于减少固化模型中的估计误差。本文详细介绍了不同方法对未治愈患者的回归参数和生存率估计的影响。该结果为从业人员选择适用于半参数固化模型的估计方法提供了有用的指导。结果的应用通过乳腺癌临床试验的真实数据集进行了说明。

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