Literature DB >> 19880284

A comparison of ad hoc methods to account for non-cancer AIDS and deaths as competing risks when estimating the effect of HAART on incident cancer AIDS among HIV-infected men.

Meredith S Shiels1, Stephen R Cole, Joan S Chmiel, Joseph Margolick, Jeremy Martinson, Zuo-Feng Zhang, Lisa P Jacobson.   

Abstract

OBJECTIVE: To compare three ad hoc methods to estimate the marginal hazard of incident cancer acquired immune deficiency syndrome (AIDS) in a highly active antiretroviral therapy (1996-2006) relative to a monotherapy/combination therapy (1990-1996) calendar period, accounting for other AIDS events and deaths as competing risks. STUDY DESIGN AND
SETTING: Among 1,911 human immunodeficiency virus (HIV)-positive men from the Multicenter AIDS Cohort Study, 228 developed cancer AIDS and 745 developed competing risks in 14,202 person-years from 1990 to 2006. Method 1 censored competing risks at the time they occurred, method 2 excluded competing risks, and method 3 censored competing risks at the date of analysis.
RESULTS: The age, race, and infection duration adjusted hazard ratios (HRs) for cancer AIDS were similar for all methods (HR approximately 0.15). We estimated bias and confidence interval coverage of each method with Monte Carlo simulation. On average, across 24 scenarios, method 1 produced less-biased estimates than methods 2 or 3.
CONCLUSIONS: When competing risks are independent of the event of interest, only method 1 produced unbiased estimates of the marginal HR, although independence cannot be verified from the data. When competing risks are dependent, method 1 generally produced the least-biased estimates of the marginal HR for the scenarios explored; however, alternative methods may be preferred. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2009        PMID: 19880284      PMCID: PMC2837111          DOI: 10.1016/j.jclinepi.2009.08.003

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  39 in total

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3.  Effect of highly active antiretroviral therapy on multiple AIDS-defining illnesses among male HIV seroconverters.

Authors:  Lauren E Cain; Stephen R Cole; Joan S Chmiel; Joseph B Margolick; Charles R Rinaldo; Roger Detels
Journal:  Am J Epidemiol       Date:  2005-12-21       Impact factor: 4.897

4.  Effectiveness of highly active antiretroviral therapy among HIV-1 infected women.

Authors:  S J Gange; Y Barrón; R M Greenblatt; K Anastos; H Minkoff; M Young; A Kovacs; M Cohen; W A Meyer; A Muñoz
Journal:  J Epidemiol Community Health       Date:  2002-02       Impact factor: 3.710

5.  Comparison of risk factors for the competing risks of coronary heart disease, stroke, and venous thromboembolism.

Authors:  Robert J Glynn; Bernard Rosner
Journal:  Am J Epidemiol       Date:  2005-10-05       Impact factor: 4.897

6.  The importance of critically interpreting simulation studies.

Authors:  G Maldonado; S Greenland
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7.  Applying Cox regression to competing risks.

Authors:  M Lunn; D McNeil
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8.  Estimation of HIV incidence in the United States.

Authors:  H Irene Hall; Ruiguang Song; Philip Rhodes; Joseph Prejean; Qian An; Lisa M Lee; John Karon; Ron Brookmeyer; Edward H Kaplan; Matthew T McKenna; Robert S Janssen
Journal:  JAMA       Date:  2008-08-06       Impact factor: 56.272

9.  Effect of HAART on incident cancer and noncancer AIDS events among male HIV seroconverters.

Authors:  Meredith S Shiels; Stephen R Cole; Scott Wegner; Haroutune Armenian; Joan S Chmiel; Anuradha Ganesan; Vincent C Marconi; Otoniel Martinez-Maza; Jeremy Martinson; Amy Weintrob; Lisa P Jacobson; Nancy F Crum-Cianflone
Journal:  J Acquir Immune Defic Syndr       Date:  2008-08-01       Impact factor: 3.731

10.  Effect of highly active antiretroviral therapy on incident AIDS using calendar period as an instrumental variable.

Authors:  Lauren E Cain; Stephen R Cole; Sander Greenland; Todd T Brown; Joan S Chmiel; Lawrence Kingsley; Roger Detels
Journal:  Am J Epidemiol       Date:  2009-03-24       Impact factor: 4.897

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  4 in total

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Journal:  AIDS       Date:  2012-05-15       Impact factor: 4.177

2.  Baseline kidney function as predictor of mortality and kidney disease progression in HIV-positive patients.

Authors:  Fowzia Ibrahim; Lisa Hamzah; Rachael Jones; Dorothea Nitsch; Caroline Sabin; Frank A Post
Journal:  Am J Kidney Dis       Date:  2012-04-21       Impact factor: 8.860

3.  Prognosis in HIV-infected patients with non-small cell lung cancer.

Authors:  K Sigel; K Crothers; R Dubrow; K Krauskopf; J Jao; C Sigel; A Moskowitz; J Wisnivesky
Journal:  Br J Cancer       Date:  2013-09-10       Impact factor: 7.640

4.  The Effect of MSM and CD4+ Count on the Development of Cancer AIDS (AIDS-defining Cancer) and Non-cancer AIDS in the HAART Era.

Authors:  Prosanta Mondal; Hyun J Lim
Journal:  Curr HIV Res       Date:  2018       Impact factor: 1.581

  4 in total

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