title: Adherence to antiretroviral therapy and its impact on clinical outcome in HIV-infected patients.
abstract: We analyse data on patient adherence to prescribed regimens and surrogate markers of clinical outcome for 168 human immunodeficiency virus infected patients treated with antiretroviral therapy. Data on patient adherence consisted of dose-timing measurements collected for an average of 12 months per patient via electronic monitoring of bottle opening events. We first discuss how such data can be presented to highlight suboptimal adherence patterns and between-patient differences, before introducing two novel methods by which such data can be statistically modelled. Correlations between adherence and subsequent measures of viral load and CD4+T-cell counts are then evaluated. We show that summary measures of short-term adherence, which incorporate pharmacokinetic and pharmacodynamic data on the monitored regimen, predict suboptimal trends in viral load and CD4+T-cell counts better than measures based on adherence data alone.
authors.affiliation: Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College London, Norfolk Place, London W2 1PG, UK. neil.ferguson@ic.ac.uk
authors.forename: N M
authors.initials: NM
authors.lastname: Ferguson
authors.forename: C A
authors.initials: CA
authors.lastname: Donnelly
authors.forename: J
authors.initials: J
authors.lastname: Hooper
authors.forename: A C
authors.initials: AC
authors.lastname: Ghani
authors.forename: C
authors.initials: C
authors.lastname: Fraser
authors.forename: L M
authors.initials: LM
authors.lastname: Bartley
authors.forename: R A
authors.initials: RA
authors.lastname: Rode
authors.forename: P
authors.initials: P
authors.lastname: Vernazza
authors.forename: D
authors.initials: D
authors.lastname: Lapins
authors.forename: S L
authors.initials: SL
authors.lastname: Mayer
authors.forename: R M
authors.initials: RM
authors.lastname: Anderson
mesh_terms: D023241:Antiretroviral Therapy, Highly Active / Q000706:statistics & numerical data*; D018791:CD4 Lymphocyte Count / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015658:HIV Infections / Q000453:epidemiology* / Q000276:immunology / Q000628:therapy*; D006801:Humans; D008954:Models, Biological; D017063:Outcome Assessment, Health Care / Q000379:methods*; D010349:Patient Compliance / Q000706:statistics & numerical data*; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D016896:Treatment Outcome; D014481:United States / Q000453:epidemiology