Literature DB >> 10861776

On the inclusion of prevalent cases in HIV/AIDS natural history studies through a marker-based estimate of time since seroconversion.

R B Geskus1.   

Abstract

In most cohort studies of HIV infection and AIDS, seroprevalent cases provide a substantial amount of information. Inclusion of these people in natural history studies requires a fairly unbiased method to estimate their seroconversion distribution. When a cohort-based estimate is not feasible, an alternative is to estimate individual seroconversion distributions, based on marker values at entry. In this paper, a non-parametric marker-based estimation method is developed. The method is applied to data from the Amsterdam cohort study on homosexual men. For seroprevalent cases who entered the study between October 1984 and April 1985, individual seroconversion distributions are estimated based on their first measured CD4 count. In subsequent survival analyses, dates of seroconversion are estimated via conditional mean imputation. Inclusion of these seroprevalent cases greatly improves the quality of the data. Age at seroconversion is a significant cofactor for disease progression, a result not found when analysis is restricted to those who seroconvert. To incorporate the uncertainty in the imputed date of seroconversion, a bootstrap procedure is developed for the computation of p-values and confidence intervals. In our analyses, standard procedures, which ignore the uncertainty in the imputed date of seroconversion, perform almost as well. Copyright 2000 John Wiley & Sons, Ltd.

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Year:  2000        PMID: 10861776     DOI: 10.1002/1097-0258(20000715)19:13<1753::aid-sim487>3.0.co;2-f

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  11 in total

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6.  Imputation of the Date of HIV Seroconversion in a Cohort of Seroprevalent Subjects: Implications for Analysis of Late HIV Diagnosis.

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Journal:  AIDS Res Treat       Date:  2011-10-15

7.  Genome-wide association scan in HIV-1-infected individuals identifying variants influencing disease course.

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9.  The effect of Trim5 polymorphisms on the clinical course of HIV-1 infection.

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10.  The HIV RNA setpoint theory revisited.

Authors:  Ronald B Geskus; Maria Prins; Jean-Baptiste Hubert; Frank Miedema; Ben Berkhout; Christine Rouzioux; Jean-Francois Delfraissy; Laurence Meyer
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