Testing the proportional hazards assumption in case-cohort analysis.
Testing the proportional hazards assumption in case-cohort analysis.
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DOI：
10.1186/1471-2288-13-88
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发表时间：
2013-07-09
影响因子：
4
通讯作者：
Strickler HD
中科院分区：
文献类型：
--
作者：
Xue X;Xie X;Gunter M;Rohan TE;Wassertheil-Smoller S;Ho GY;Cirillo D;Yu H;Strickler HD
病例-队列研究在罕见病的流行病学研究中已经很常见，考克斯回归模型是其分析中使用的主要方法。然而，没有适当的程序来评估病例队列考克斯模型的比例风险的假设已经提出。我们扩展了基于Schoenfeld残差的相关性检验，这是一种用于评估标准考克斯模型中风险比例的方法。具体地，使用伪随机函数来定义“病例-队列Schoenfeld残差”，然后计算这些残差与事件时间的三个函数中的每一个的相关性（即，事件时间本身、等级顺序、Kaplan-Meier估计）。所提出的测试的性能进行了研究，使用模拟研究。然后，我们将这些方法应用于先前发表的胰岛素/IGF轴和结直肠癌病例队列研究的数据。模拟研究表明，这三个相关性测试中的每一个都准确地检测到了非比例性。将拟议检验应用于示例病例队列调查数据集表明，该研究中某些暴露变量不满足考克斯比例风险假设，我们通过使用可用的替代分析方法解决了这一问题。本文提出的相关性检验方法为病例-队列分析中考克斯模型的比例风险假设提供了一种简单而准确的检验方法。比例风险假设的评价是必不可少的，因为它的违反提出了关于考克斯模型结果的有效性的问题，如果不承认，可能会导致错误的科学发现的出版物。
Case-cohort studies have become common in epidemiological studies of rare disease, with Cox regression models the principal method used in their analysis. However, no appropriate procedures to assess the assumption of proportional hazards of case-cohort Cox models have been proposed. We extended the correlation test based on Schoenfeld residuals, an approach used to evaluate the proportionality of hazards in standard Cox models. Specifically, pseudolikelihood functions were used to define “case-cohort Schoenfeld residuals”, and then the correlation of these residuals with each of three functions of event time (i.e., the event time itself, rank order, Kaplan-Meier estimates) was determined. The performances of the proposed tests were examined using simulation studies. We then applied these methods to data from a previously published case-cohort investigation of the insulin/IGF-axis and colorectal cancer. Simulation studies showed that each of the three correlation tests accurately detected non-proportionality. Application of the proposed tests to the example case-cohort investigation dataset showed that the Cox proportional hazards assumption was not satisfied for certain exposure variables in that study, an issue we addressed through use of available, alternative analytical approaches. The proposed correlation tests provide a simple and accurate approach for testing the proportional hazards assumption of Cox models in case-cohort analysis. Evaluation of the proportional hazards assumption is essential since its violation raises questions regarding the validity of Cox model results which, if unrecognized, could result in the publication of erroneous scientific findings.
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影响因子：
4
作者：
Bellera CA;MacGrogan G;Debled M;de Lara CT;Brouste V;Mathoulin-Pélissier S
通讯作者：
Mathoulin-Pélissier S
影响因子：
1.9
作者：
ANDERSEN, PK
通讯作者：
ANDERSEN, PK
影响因子：
2.7
作者：
LIN, DY;WEI, LJ;YING, Z
通讯作者：
YING, Z
影响因子：
2.7
作者：
THERNEAU, TM;GRAMBSCH, PM;FLEMING, TR
通讯作者：
FLEMING, TR
影响因子：
10.3
作者：
Gunter, Marc J.;Hoover, Donald R.;Strickler, Howard D.
通讯作者：
Strickler, Howard D.