双嵌套病例对照设计的绝对风险:使用和不使用增强估计方程的特定病因比例危险模型。

IF 1.4 4区 数学 Q3 BIOLOGY
Biometrics Pub Date : 2024-07-01 DOI:10.1093/biomtc/ujae062
Minjung Lee, Mitchell H Gail
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引用次数: 0

摘要

我们从双嵌套病例对照(DNCC)数据中,根据竞争风险的特定病因比例危险度模型估算相对危险度和绝对危险度(或累积发病率或粗风险)。在 DNCC 设计中,对照组不仅要与主要病因的病例进行时间匹配,还要与竞争风险的病例(第二阶段样本)进行时间匹配。第二阶段样本有完整的协变量数据,但其他队列成员只有生存结果和一些协变量信息。设计加权估计器使用的是根据 DNCC 的 Samuelsen 类型计算得出的反抽样概率。为了利用所有队列成员的额外信息,我们在估计方程中增加了一个对零无偏的项,但提高了特定成因比例危险模型的估计效率。我们建立了所建议的估计器(包括绝对风险估计器)的渐近特性,并推导出一致的方差估计器。我们表明,增强设计加权估计器比设计加权估计器更有效。通过模拟,我们表明所提出的渐近方法能在实际样本量中产生名义运行特征。我们使用美国国家癌症研究所的前列腺癌、肺癌、结肠直肠癌和卵巢癌筛查试验研究中的前列腺癌死亡率数据来说明这些方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Absolute risk from double nested case-control designs: cause-specific proportional hazards models with and without augmented estimating equations.

We estimate relative hazards and absolute risks (or cumulative incidence or crude risk) under cause-specific proportional hazards models for competing risks from double nested case-control (DNCC) data. In the DNCC design, controls are time-matched not only to cases from the cause of primary interest, but also to cases from competing risks (the phase-two sample). Complete covariate data are available in the phase-two sample, but other cohort members only have information on survival outcomes and some covariates. Design-weighted estimators use inverse sampling probabilities computed from Samuelsen-type calculations for DNCC. To take advantage of additional information available on all cohort members, we augment the estimating equations with a term that is unbiased for zero but improves the efficiency of estimates from the cause-specific proportional hazards model. We establish the asymptotic properties of the proposed estimators, including the estimator of absolute risk, and derive consistent variance estimators. We show that augmented design-weighted estimators are more efficient than design-weighted estimators. Through simulations, we show that the proposed asymptotic methods yield nominal operating characteristics in practical sample sizes. We illustrate the methods using prostate cancer mortality data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Study of the National Cancer Institute.

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来源期刊
Biometrics
Biometrics 生物-生物学
CiteScore
2.70
自引率
5.30%
发文量
178
审稿时长
4-8 weeks
期刊介绍: The International Biometric Society is an international society promoting the development and application of statistical and mathematical theory and methods in the biosciences, including agriculture, biomedical science and public health, ecology, environmental sciences, forestry, and allied disciplines. The Society welcomes as members statisticians, mathematicians, biological scientists, and others devoted to interdisciplinary efforts in advancing the collection and interpretation of information in the biosciences. The Society sponsors the biennial International Biometric Conference, held in sites throughout the world; through its National Groups and Regions, it also Society sponsors regional and local meetings.
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