Kiwuwa-Muyingo S., Walker A.S., Oja H., Levin J., Miiro G., Katabira E., Kityo C., Hakim J., Todd J.
School of Health Sciences, University of Tampere, Finland; MRC Uganda Virus Research Institute, Entebbe, Uganda; Medical Research Council Clinical Trials Unit, London, United Kingdom; Infectious Diseases Institute, Makerere University, Kampala, Uganda; Joint Clinical Research Centre, Kampala, Uganda; College of Health Sciences, University of Harare, Harare, Zimbabwe; London School of Hygiene and Tropical Medicine, London, United Kingdom
Kiwuwa-Muyingo, S., School of Health Sciences, University of Tampere, Finland, MRC Uganda Virus Research Institute, Entebbe, Uganda; Walker, A.S., Medical Research Council Clinical Trials Unit, London, United Kingdom; Oja, H., School of Health Sciences, University of Tampere, Finland; Levin, J., MRC Uganda Virus Research Institute, Entebbe, Uganda; Miiro, G., MRC Uganda Virus Research Institute, Entebbe, Uganda; Katabira, E., Infectious Diseases Institute, Makerere University, Kampala, Uganda; Kityo, C., Joint Clinical Research Centre, Kampala, Uganda; Hakim, J., College of Health Sciences, University of Harare, Harare, Zimbabwe; Todd, J., London School of Hygiene and Tropical Medicine, London, United Kingdom
Objectives To describe associations between different summaries of adherence in the first year on antiretroviral therapy (ART) and the subsequent risk of mortality, to identify patients at high risk because of early adherence behaviour. Methods We previously described an approach where adherence behaviour at successive clinic visits during the first year on ART was seen as a Markov chain (MC), and the individually estimated transition probabilities between 'good', 'poor' and 'non-response' adherence states were used to classify HIV-infected adults in the DART trial into subgroups with similar behaviour. The impact of this classification and classifications based on traditional 'averaged' measures [mean drug possession ratio (DPR) and self-reported adherence] were compared in terms of their impact on longer-term mortality over the 2-5years on ART using Cox proportional hazards models. Results Of 2960 participants in follow-up after 1year on ART, 29% had never missed pills in the last month and 11% had 100% DPR throughout the first year. The poorest adherers by self-reported measures were more likely to have only none/primary education (P<0.01). Being in the poorest adherence subgroup by MC and DPR was independently associated with increased mortality [HR=1.57 (95% CI 1.02, 2.42); 1.82 (1.32, 2.51) respectively]. Conclusions Classification based on dynamic adherence behaviour is associated with mortality independently of DPR. The classifications could be useful in understanding adherence, targeting focused interventions and improving longer-term adherence to therapy. © 2012 Blackwell Publishing Ltd.
abacavir; lamivudine plus zidovudine; nevirapine; tenofovir; antimicrobial activity; health risk; human immunodeficiency virus; immune system; infectivity; Markov chain; mortality; numerical model; risk factor; adult; antiretroviral therapy; antiviral therapy; article; CD4 lymphocyte count; classification; controlled study; drug monitoring; educational status; female; follow up; high risk patient; human; Human immunodeficiency virus infected patient; Human immunodeficiency virus infection; major clinical study; male; mortality; outcome assessment; patient compliance; questionnaire; self report; treatment refusal; Uganda; Zimbabwe; Adult; Anti-HIV Agents; Antiretroviral Therapy, Highly Active; Female; Follow-Up Studies; HIV Infections; Humans; Male; Markov Chains; Patient Compliance; Proportional Hazards Models; Questionnaires; Treatment Outcome; Uganda; Zimbabwe; Uganda; Zimbabwe