A proportional hazards model for multivariate interval-censored failure time data.

Abstract:

: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 CMV 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.

journal_name

Biometrics

journal_title

Biometrics

authors

Goggins WB,Finkelstein DM

doi

10.1111/j.0006-341x.2000.00940.x

subject

Has Abstract

pub_date

2000-09-01 00:00:00

pages

940-3

issue

3

eissn

0006-341X

issn

1541-0420

journal_volume

56

pub_type

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