Literature DB >> 15493031

Accounting for leadtime in cohort studies: evaluating when to initiate HIV therapies.

Stephen R Cole1, Rui Li, Kathryn Anastos, Roger Detels, Mary Young, Joan S Chmiel, Alvaro Muñoz.   

Abstract

Commonly reported comparisons of differences in disease progression according to disease staging at therapy initiation may be subject to bias if they do not account for the time it took the deferred group to reach the latter stage (that is, leadtime) and for previous events in those who initiate therapy at late stage (that is, unseen fast progressors). To estimate the impact of deferring initiation of highly active antiretroviral therapies (HAART) on time to clinical AIDS in the context of data from observational cohort studies, we describe a method that capitalizes on data from a pre-HAART period to multiply impute estimated leadtimes and the unseen events among fast progressors. After accounting for leadtime and the unseen events, data from two large cohort studies (N=739) indicate that deferring HAART initiation until CD4 is below 200 cells/mm3 was detrimental compared to initiating between 201 and 350 (hazard ratio=1.97; 95 percent confidence interval [CI] 1.09, 3.54), and that failure to account for leadtime resulted in a 38 per cent higher hazard ratio. In contrast, initiating HAART between 201 and 350 did not increase the hazard of AIDS compared to initiating with CD4 between 351 and 500 cells/mm3 (hazard ratio=0.70; 95 per cent CI 0.35, 1.42). Methods presented here offer an approach to analysing prevalent cohort studies and provide procedures to maximize the usefulness of observational data. 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 15493031     DOI: 10.1002/sim.1579

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


  21 in total

1.  When to start treatment? A systematic approach to the comparison of dynamic regimes using observational data.

Authors:  Lauren E Cain; James M Robins; Emilie Lanoy; Roger Logan; Dominique Costagliola; Miguel A Hernán
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2.  Inference for mutually exclusive competing events through a mixture of generalized gamma distributions.

Authors:  William Checkley; Roy G Brower; Alvaro Muñoz
Journal:  Epidemiology       Date:  2010-07       Impact factor: 4.822

3.  Nonparametric tests for right-censored data with biased sampling.

Authors:  Jing Ning; Jing Qin; Yu Shen
Journal:  J R Stat Soc Series B Stat Methodol       Date:  2010-11-01       Impact factor: 4.488

Review 4.  When to start antiretroviral therapy.

Authors:  Cunlin Wang; Saba W Masho; Daniel E Nixon
Journal:  Curr HIV/AIDS Rep       Date:  2006-07       Impact factor: 5.071

5.  Timing of HAART initiation and clinical outcomes in human immunodeficiency virus type 1 seroconverters.

Authors: 
Journal:  Arch Intern Med       Date:  2011-09-26

6.  Initiating patients on antiretroviral therapy at CD4 cell counts above 200 cells/microl is associated with improved treatment outcomes in South Africa.

Authors:  Matthew P Fox; Ian M Sanne; Francesca Conradie; Jennifer Zeinecker; Catherine Orrell; Prudence Ive; Mohammed Rassool; Marjorie Dehlinger; Charles van der Horst; James McIntyre; Robin Wood
Journal:  AIDS       Date:  2010-08-24       Impact factor: 4.177

7.  Time at risk and intention-to-treat analyses: parallels and implications for inference.

Authors:  Sunni L Mumford; Enrique F Schisterman; Stephen R Cole; Daniel Westreich; Robert W Platt
Journal:  Epidemiology       Date:  2015-01       Impact factor: 4.822

8.  Estimating the optimal CD4 count for HIV-infected persons to start antiretroviral therapy.

Authors:  Bryan E Shepherd; Cathy A Jenkins; Peter F Rebeiro; Samuel E Stinnette; Sally S Bebawy; Catherine C McGowan; Todd Hulgan; Timothy R Sterling
Journal:  Epidemiology       Date:  2010-09       Impact factor: 4.822

9.  When should antiretroviral therapy be started in HIV-positive persons?

Authors:  Caroline A Sabin
Journal:  F1000 Med Rep       Date:  2010-11-24

10.  Long-term CD4+ lymphocyte response following HAART initiation in a U.S. Military prospective cohort.

Authors:  Alan R Lifson; Elizabeth M Krantz; Lynn E Eberly; Matthew J Dolan; Vincent C Marconi; Amy C Weintrob; Nancy F Crum-Cianflone; Anuradha Ganesan; Patricia L Grambsch; Brian K Agan
Journal:  AIDS Res Ther       Date:  2011-01-18       Impact factor: 2.250

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