Cox model inference for relative hazard and pure risk from stratified weight-calibrated case-cohort data

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
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引用次数: 0

Abstract

The case-cohort design obtains complete covariate data only on cases and on a random sample (the subcohort) of the entire cohort. Subsequent publications described the use of stratification and weight calibration to increase efficiency of estimates of Cox model log-relative hazards, and there has been some work estimating pure risk. Yet there are few examples of these options in the medical literature, and we could not find programs currently online to analyze these various options. We therefore present a unified approach and R software to facilitate such analyses. We used influence functions adapted to the various design and analysis options together with variance calculations that take the two-phase sampling into account. This work clarifies when the widely used “robust” variance estimate of Barlow (Biometrics 50:1064–1072, 1994) is appropriate. The corresponding R software, CaseCohortCoxSurvival, facilitates analysis with and without stratification and/or weight calibration, for subcohort sampling with or without replacement. We also allow for phase-two data to be missing at random for stratified designs. We provide inference not only for log-relative hazards in the Cox model, but also for cumulative baseline hazards and covariate-specific pure risks. We hope these calculations and software will promote wider use of more efficient and principled design and analysis options for case-cohort studies.

从分层体重校准的病例队列数据中推断相对危险度和纯风险的 Cox 模型
摘要 病例队列设计只获得病例和整个队列的随机样本(子队列)的完整协变量数据。随后发表的文章介绍了如何使用分层和权重校准来提高 Cox 模型对数相关危险度估计的效率,并对纯风险进行了一些估计。然而,这些方案在医学文献中鲜有实例,我们目前也无法在网上找到分析这些不同方案的程序。因此,我们提出了一种统一的方法和 R 软件,以方便进行此类分析。我们使用了与各种设计和分析方案相适应的影响函数以及考虑到两阶段采样的方差计算。这项工作明确了巴洛(Barlow,《生物统计学》50:1064-1072,1994 年)广泛使用的 "稳健 "方差估计何时合适。相应的 R 软件 CaseCohortCoxSurvival 可以在分层和/或权重校准的情况下进行分析,也可以在有或没有替换的子队列抽样中进行分析。对于分层设计,我们还允许第二阶段数据随机缺失。我们不仅提供了 Cox 模型中的对数相对危险度推断,还提供了累积基线危险度和共变量特异性纯危险度推断。我们希望这些计算和软件能促进病例队列研究更广泛地使用更高效、更有原则的设计和分析方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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