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

Ronald S. Braithwaite, S. Shechter, M. S. Roberts, A. Schaefer, David Bangsberg, P. R. Harrigan, A. C. Justice

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

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). 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. The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.

Original languageEnglish (US)
Pages (from-to)1036-1043
Number of pages8
JournalJournal of Antimicrobial Chemotherapy
Volume58
Issue number5
DOIs
StatePublished - 2006
Externally publishedYes

Fingerprint

Computer Simulation
HIV
Mutation
Viral Load
Population
Mutation Accumulation

Keywords

  • AIDS
  • Effectiveness
  • Efficacy
  • HAART

ASJC Scopus subject areas

  • Pharmacology
  • Pharmacology (medical)
  • Infectious Diseases
  • Microbiology

Cite this

Braithwaite, R. S., Shechter, S., Roberts, M. S., Schaefer, A., Bangsberg, D., Harrigan, P. R., & Justice, A. C. (2006). Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation. Journal of Antimicrobial Chemotherapy, 58(5), 1036-1043. https://doi.org/10.1093/jac/dkl386

Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation. / Braithwaite, Ronald S.; Shechter, S.; Roberts, M. S.; Schaefer, A.; Bangsberg, David; Harrigan, P. R.; Justice, A. C.

In: Journal of Antimicrobial Chemotherapy, Vol. 58, No. 5, 2006, p. 1036-1043.

Research output: Contribution to journalArticle

Braithwaite, Ronald S. ; Shechter, S. ; Roberts, M. S. ; Schaefer, A. ; Bangsberg, David ; Harrigan, P. R. ; Justice, A. C. / Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation. In: Journal of Antimicrobial Chemotherapy. 2006 ; Vol. 58, No. 5. pp. 1036-1043.
@article{1d573268188443a3ad38469b042a449f,
title = "Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation",
abstract = "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). 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. The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.",
keywords = "AIDS, Effectiveness, Efficacy, HAART",
author = "Braithwaite, {Ronald S.} and S. Shechter and Roberts, {M. S.} and A. Schaefer and David Bangsberg and Harrigan, {P. R.} and Justice, {A. C.}",
year = "2006",
doi = "10.1093/jac/dkl386",
language = "English (US)",
volume = "58",
pages = "1036--1043",
journal = "Journal of Antimicrobial Chemotherapy",
issn = "0305-7453",
publisher = "Oxford University Press",
number = "5",

}

TY - JOUR

T1 - Explaining variability in the relationship between antiretroviral adherence and HIV mutation accumulation

AU - Braithwaite, Ronald S.

AU - Shechter, S.

AU - Roberts, M. S.

AU - Schaefer, A.

AU - Bangsberg, David

AU - Harrigan, P. R.

AU - Justice, A. C.

PY - 2006

Y1 - 2006

N2 - 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). 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. The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.

AB - 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). 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. The Author 2006. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved.

KW - AIDS

KW - Effectiveness

KW - Efficacy

KW - HAART

UR - http://www.scopus.com/inward/record.url?scp=34249319607&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34249319607&partnerID=8YFLogxK

U2 - 10.1093/jac/dkl386

DO - 10.1093/jac/dkl386

M3 - Article

C2 - 17023498

AN - SCOPUS:34249319607

VL - 58

SP - 1036

EP - 1043

JO - Journal of Antimicrobial Chemotherapy

JF - Journal of Antimicrobial Chemotherapy

SN - 0305-7453

IS - 5

ER -