A general framework for parametric survival analysis
A general framework for parametric survival analysis
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DOI：
10.1002/sim.6300
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发表时间：
2014-12-01
影响因子：
2
通讯作者：
Lambert, Paul C.
中科院分区：
文献类型：
--
作者：
Crowther, Michael J.;Lambert, Paul C.
在生物医学研究中，参数生存模型越来越多地被用作考克斯模型的替代。通过对基线风险函数的直接建模，我们可以更好地了解患者随时间推移的风险状况，获得风险的绝对测量值。常用的参数生存模型（如Weibull）对基线风险函数（如单调性）进行了限制性假设，这在临床数据集中经常被违反。在这篇文章中，我们扩展了Crowther和Lambert提出的参数生存模型的一般框架（Journal of Statistical Software 53：12，2013），以纳入相对生存，稳健和聚类稳健标准误差。我们通过三个临床数据集的应用程序来描述总体框架，特别是说明了使用限制性三次样条，以日志危害尺度为模型，提供了一个高度灵活的生存建模框架。通过使用限制三次样条，我们可以推导出的累积风险函数解析超出边界节点，导致在一个组合的分析/数值方法，这大大提高了估计过程相比，只使用数值积分。提供了用户友好的Stata软件，显着扩展了标准软件中可用的参数生存模型。版权所有（c）2014约翰威利父子有限公司
Parametric survival models are being increasingly used as an alternative to the Cox model in biomedical research. Through direct modelling of the baseline hazard function, we can gain greater understanding of the risk profile of patients over time, obtaining absolute measures of risk. Commonly used parametric survival models, such as the Weibull, make restrictive assumptions of the baseline hazard function, such as monotonicity, which is often violated in clinical datasets. In this article, we extend the general framework of parametric survival models proposed by Crowther and Lambert (Journal of Statistical Software 53:12, 2013), to incorporate relative survival, and robust and cluster robust standard errors. We describe the general framework through three applications to clinical datasets, in particular, illustrating the use of restricted cubic splines, modelled on the log hazard scale, to provide a highly flexible survival modelling framework. Through the use of restricted cubic splines, we can derive the cumulative hazard function analytically beyond the boundary knots, resulting in a combined analytic/numerical approach, which substantially improves the estimation process compared with only using numerical integration. User-friendly Stata software is provided, which significantly extends parametric survival models available in standard software. Copyright (c) 2014 John Wiley & Sons, Ltd.