Suppr超能文献

在存在竞争风险的情况下对疾病发病年龄的家族关联进行建模。

Modeling familial association of ages at onset of disease in the presence of competing risk.

作者信息

Shih Joanna H, Albert Paul S

机构信息

Biometric Research Branch, National Cancer Institute, Rockville, Maryland 20852, USA.

出版信息

Biometrics. 2010 Dec;66(4):1012-23. doi: 10.1111/j.1541-0420.2009.01372.x.

Abstract

In genetic family studies, ages at onset of diseases are routinely collected. Often one is interested in assessing the familial association of ages at the onset of a certain disease type. However, when a competing risk is present and is related to the disease of interest, the usual measure of association by treating the competing event as an independent censoring event is biased. We propose a bivariate model that incorporates two types of association: one is between the first event time of paired members, and the other is between the failure types given the first event time. We consider flexible measures for both types of association, and estimate the corresponding association parameters by adopting the two-stage estimation of Shih and Louis (1995, Biometrics 51, 1384-1399) and Nan et al. (2006, Journal of the American Statistical Association 101, 65-77). The proposed method is illustrated using the kinship data from the Washington Ashkenazi Study.

摘要

在基因家族研究中,通常会收集疾病的发病年龄。人们常常对评估某一特定疾病类型发病年龄的家族关联性感兴趣。然而,当存在竞争风险且该风险与所关注的疾病相关时,将竞争事件视为独立删失事件的常用关联度量方法会产生偏差。我们提出了一个双变量模型,该模型纳入了两种关联类型:一种是配对成员的首次事件时间之间的关联,另一种是给定首次事件时间下的失败类型之间的关联。我们考虑了这两种关联类型的灵活度量方法,并采用施和路易斯(1995年,《生物统计学》51卷,1384 - 1399页)以及南等人(2006年,《美国统计协会杂志》101卷,65 - 77页)的两阶段估计方法来估计相应的关联参数。使用来自华盛顿阿什肯纳兹研究的亲属关系数据对所提出的方法进行了说明。

相似文献

1
Modeling familial association of ages at onset of disease in the presence of competing risk.
Biometrics. 2010 Dec;66(4):1012-23. doi: 10.1111/j.1541-0420.2009.01372.x.
2
A bivariate cure-mixture approach for modeling familial association in diseases.
Biometrics. 2001 Sep;57(3):779-86. doi: 10.1111/j.0006-341x.2001.00779.x.
3
Incorporation of the time aspect into the liability-threshold model for case-control-family data.
Stat Med. 2017 May 10;36(10):1599-1618. doi: 10.1002/sim.7229. Epub 2017 Jan 23.
4
Analysis of survival data from case-control family studies.
Biometrics. 2002 Sep;58(3):502-9. doi: 10.1111/j.0006-341x.2002.00502.x.
5
Two-stage pseudo maximum likelihood estimation of semiparametric copula-based regression models for semi-competing risks data.
Lifetime Data Anal. 2025 Jan;31(1):52-75. doi: 10.1007/s10985-024-09640-z. Epub 2024 Oct 23.
6
Association analyses of clustered competing risks data via cross hazard ratio.
Biostatistics. 2010 Jan;11(1):82-92. doi: 10.1093/biostatistics/kxp039. Epub 2009 Oct 13.
7
Estimation of time-dependent association for bivariate failure times in the presence of a competing risk.
Biometrics. 2014 Mar;70(1):10-20. doi: 10.1111/biom.12110. Epub 2013 Dec 18.
8
Accelerated failure time models for semi-competing risks data in the presence of complex censoring.
Biometrics. 2017 Dec;73(4):1401-1412. doi: 10.1111/biom.12696. Epub 2017 Apr 10.

引用本文的文献

1
Second-Order Estimating Equations for Clustered Current Status Data from Family Studies Using Response-Dependent Sampling.
Stat Biosci. 2018;10(1):160-183. doi: 10.1007/s12561-017-9201-4. Epub 2017 Jul 24.
2
Methods for generating paired competing risks data.
Comput Methods Programs Biomed. 2016 Oct;135:199-207. doi: 10.1016/j.cmpb.2016.07.027. Epub 2016 Jul 25.
3
Modelling the type and timing of consecutive events: application to predicting preterm birth in repeated pregnancies.
J R Stat Soc Ser C Appl Stat. 2015 Nov;64(5):711-730. doi: 10.1111/rssc.12100. Epub 2015 Apr 3.
4
Measuring early or late dependence for bivariate lifetimes of twins.
Lifetime Data Anal. 2015 Apr;21(2):280-99. doi: 10.1007/s10985-014-9309-5. Epub 2014 Sep 4.
5
Semicompeting risks in aging research: methods, issues and needs.
Lifetime Data Anal. 2014 Oct;20(4):538-62. doi: 10.1007/s10985-014-9295-7. Epub 2014 Apr 12.
6
Estimation of time-dependent association for bivariate failure times in the presence of a competing risk.
Biometrics. 2014 Mar;70(1):10-20. doi: 10.1111/biom.12110. Epub 2013 Dec 18.

本文引用的文献

2
Nonparametric association analysis of exchangeable clustered competing risks data.
Biometrics. 2009 Jun;65(2):385-93. doi: 10.1111/j.1541-0420.2008.01072.x. Epub 2008 May 11.
4
Adjustment for competing risk in kin-cohort estimation.
Genet Epidemiol. 2003 Dec;25(4):303-13. doi: 10.1002/gepi.10269.
6
The risk of cancer associated with specific mutations of BRCA1 and BRCA2 among Ashkenazi Jews.
N Engl J Med. 1997 May 15;336(20):1401-8. doi: 10.1056/NEJM199705153362001.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验