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JAC Advance Access originally published online on October 5, 2006
Journal of Antimicrobial Chemotherapy 2006 58(5):1036-1043; doi:10.1093/jac/dkl386
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© The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation

R. S. Braithwaite1,*, S. Shechter2, M. S. Roberts2,3, A. Schaefer2,3, D. R. Bangsberg4, P. R. Harrigan5 and A. C. Justice1

1 Section of General Internal Medicine, Yale University School of Medicine and VA Connecticut Healthcare System New Haven, CT, USA 2 Department of Industrial Engineering, School of Engineering, University of Pittsburgh Pittsburgh, PA, USA 3 Section of Decision Sciences and Clinical Systems Modeling, University of Pittsburgh School of Medicine Pittsburgh, PA, USA 4 Epidemiology and Prevention Interventions Center, Division of Infectious Diseases, Positive Health Program, University of California at San Francisco San Francisco, CA, USA 5 Department of Medicine, University of British Columbia Vancouver, Canada

Received 28 April 2006; returned 8 June 2006; revised 29 August 2006; accepted 30 August 2006

*Corresponding author. Tel: +1-203-932-5711; Fax: +1-203-937-4926; E-mail: ronald.braithwaite{at}va.gov

Objectives: Determining the relationship between antiretroviral adherence and resistance accumulation is important for the design and evaluation of adherence interventions. Our objective was to explain heterogeneity observed in this relationship.

Methods: We first conducted a systematic review to locate published reports describing the relationship between adherence and resistance. We then used a validated computer simulation to simulate the patient populations in these reports, exploring the impact of changes in individual patient characteristics (age, CD4, viral load, prior antiretroviral experience) on the shape of the adherence–resistance (A–R) curve.

Results: The search identified 493 titles, of which 3 contained relevant primary data and 2 had sufficient follow-up for inclusion (HOMER and REACH cohorts). When simulating HOMER, the A–R curve had a high peak with a greatly increased hazard ratio (HR) of accumulating mutations at partial compared to complete adherence (simulation, HR 2.9; HOMER, HR 2.7). When simulating REACH, the A–R curve had a shallow peak with a slightly increased hazard of accumulating mutations at partial adherence (simulation, HR 1.2; REACH, HR 1.4). This heterogeneity was primarily attributable to differences in antiretroviral experience between the cohorts.

Conclusions: Our computer simulation was able to explain much of the heterogeneity in observed A–R curves.

Keywords: AIDS , HAART , effectiveness , efficacy


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