Literature DB >> 11242178

Public health consequences of screening patients for adherence to highly active antiretroviral therapy.

E Tchetgen1, E H Kaplan, G H Friedland.   

Abstract

Improvements in HIV antiretroviral therapy (ART) have been accompanied by increasing recognition of the importance of adherence to treatment regimens for maximizing patient benefits while minimizing the emergence of drug-resistant virus. Whether clinicians should screen patients for adherence and only administer therapy to those believed likely to adhere has not been resolved. We first examine the implications of data drawn from a recent study reporting physicians' ability to predict whether patients will adhere to highly active antiretroviral therapy (HAART) or not. We then extend previously developed mathematical models of ART to include screening for adherence and focus on resulting drug resistance as well as on HIV and AIDS incidence at the population level. We show that although screening for adherence is likely to reduce the level of drug resistance compared with a policy of treating all HIV patients with HAART, rates of new HIV infections and AIDS cases in the population would likely increase unless screening accuracy is extremely (perhaps implausibly) high.

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Year:  2001        PMID: 11242178     DOI: 10.1097/00042560-200102010-00003

Source DB:  PubMed          Journal:  J Acquir Immune Defic Syndr        ISSN: 1525-4135            Impact factor:   3.731


  10 in total

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2.  Adherence to antiretroviral HIV drugs: how many doses can you miss before resistance emerges?

Authors:  R J Smith
Journal:  Proc Biol Sci       Date:  2006-03-07       Impact factor: 5.349

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4.  Patient-reported and physician-estimated adherence to HAART: social and clinic center-related factors are associated with discordance.

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Journal:  J Gen Intern Med       Date:  2004-11       Impact factor: 5.128

Review 5.  What do mathematical models tell us about the emergence and spread of drug-resistant HIV?

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6.  Modeling HIV transmission risk among Mozambicans prior to their initiating highly active antiretroviral therapy.

Authors:  C R Pearson; A E Kurth; S Cassels; D P Martin; J M Simoni; P Hoff; E Matediana; S Gloyd
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Review 7.  Modelling sexual transmission of HIV: testing the assumptions, validating the predictions.

Authors:  Rebecca F Baggaley; Christophe Fraser
Journal:  Curr Opin HIV AIDS       Date:  2010-07       Impact factor: 4.283

8.  The epidemiological impact of antiretroviral use predicted by mathematical models: a review.

Authors:  Rebecca F Baggaley; Neil M Ferguson; Geoff P Garnett
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Review 9.  HIV treatment as prevention: contradictory perspectives from dynamic mathematical models.

Authors:  Jing Wu; Jessie L Norris; Yujiang Jia; Ning Wang
Journal:  ScientificWorldJournal       Date:  2014-12-15

10.  Modelling imperfect adherence to HIV induction therapy.

Authors:  Rachelle E Miron; Robert J Smith
Journal:  BMC Infect Dis       Date:  2010-01-12       Impact factor: 3.090

  10 in total

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