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 2-5 years on ART using Cox proportional hazards models. RESULTS: Of 2960 participants in follow-up after 1 year 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.
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 2-5 years on ART using Cox proportional hazards models. RESULTS: Of 2960 participants in follow-up after 1 year 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.
Authors: Cissy Kityo; Diana M Gibb; Charles F Gilks; Ruth L Goodall; Ivan Mambule; Pontiano Kaleebu; Deenan Pillay; Ronnie Kasirye; Peter Mugyenyi; A Sarah Walker; David T Dunn Journal: PLoS One Date: 2014-03-13 Impact factor: 3.240
Authors: Sylvia Kiwuwa-Muyingo; Hannu Oja; Ann Walker; Pauliina Ilmonen; Jonathan Levin; Andrew Reid; Peter Mugyenyi; Jim Todd Journal: BMC Infect Dis Date: 2013-08-27 Impact factor: 3.090
Authors: Raphael Z Sangeda; Fausta Mosha; Mattia Prosperi; Said Aboud; Jurgen Vercauteren; Ricardo J Camacho; Eligius F Lyamuya; Eric Van Wijngaerden; Anne-Mieke Vandamme Journal: BMC Public Health Date: 2014-10-04 Impact factor: 3.295
Authors: David I Dolling; Ruth L Goodall; Michael Chirara; James Hakim; Peter Nkurunziza; Paula Munderi; David Eram; Dinah Tumukunde; Moira J Spyer; Charles F Gilks; Pontiano Kaleebu; David T Dunn; Deenan Pillay Journal: BMC Infect Dis Date: 2017-02-21 Impact factor: 3.090