A proportional hazards model for multivariate interval-censored failure time data
A proportional hazards model for multivariate interval-censored failure time data
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DOI：
10.1111/j.0006-341x.2000.00940.x
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发表时间：
2000-09-01
期刊：
影响因子：
1.9
通讯作者：
Finkelstein, DM
中科院分区：
文献类型：
--
作者：
Goggins, WB;Finkelstein, DM
本文重点介绍了艾滋病观察性研究的多元区间删失数据集的分析方法。该研究的目的是确定机会性感染巨细胞病毒（CMV）在HIV感染者中的自然史。对于这项观察性研究，在计划的门诊访视时进行实验室检查，以检测血液和尿液中是否存在Ch IV病毒（称为血液和尿液中的CMV脱落）。研究人员感兴趣的是确定进入研究时的HIV疾病阶段是否预示着血液或尿液中CMV脱落的风险增加。如果所有患者都进行了每次门诊访视，则数据将是多变量分组失效时间数据，并且可以使用已发表的方法。然而，许多患者错过了几次访视，当他们返回时，他们的实验室检查表明他们的血液和/或尿液CMV脱落状态发生变化，导致间隔删失的失败时间数据。本文概述了一种方法，应用比例风险模型分析的多变量区间删失失效时间数据的研究CMV在HIV感染的患者。
This paper focuses on the methodology developed for analyzing a multivariate interval-censored data set from an AIDS observational study. A purpose of the study was to determine the natural history of the opportunistic infection cytomeglovirus (CMV) in an HIV-infected individual. For this observational study, laboratory tests were performed at scheduled clinic visits to test for the presence of the Ch IV virus in the blood and in the urine (called CMV shedding in the blood and urine). The study investigators were interested in determining whether the stage of HIV disease at study entry was predictive of an increased risk for CMV shedding in either the blood or the urine. If all patients had made each clinic visit, the data would be multivariate grouped failure time data and published methods could be used. However, many patients missed several visits, and when they returned, their lab tests indicated a change in their blood and/or urine CMV shedding status, resulting in interval-censored failure time data. This paper outlines a method for applying the proportional hazards model to the analysis of multivariate interval-censored failure time data from a study of CMV in HIV-infected patients.