How Long Is the Window of Opportunity Between Adherence Failure and Virologic Failure on Efavirenz-Based HAART?
ABSTRACT The time between onset of nonadherence and onset of virological failure is unknown. However, this information is critical to the design, implementation, and testing of interventions aiming to forestall treatment failure.
We conducted an observational cohort study of 116 HIV-infected adults with virological suppression on efavirenz-based regimens. Patients were seen monthly and censored at virological failure (>1000 copies/mL) or 12 months, whichever came first. Adherence was measured using the Medication Event Monitoring System (MEMS). Percent of doses taken was summarized for 90-day periods. We assessed 4 adherence periods: immediately prior to censor, and then 30 days, 60 days, and 90 days prior to censor.
Adherence was significantly lower for patients with virological failure (n=7) than those without virological failure (n=99) at all time points assessed. These differences were statistically significant even up to 90 days prior to the virologic failure date (failure group 57% vs. nonfailure group 95%; p= .03).
The window between the onset of nonadherence and virological failure can be as long as 90 days. This will allow substantial time for interventions to be implemented and to take effect.
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ABSTRACT: Antiretroviral medication refill adherence has not been compared directly to electronic drug monitoring (EDM) in any identifiable published study. We retrospectively studied adults with undetectable HIV titers on highly active antiretroviral therapy. We used Pearson correlation coefficients and receiver operating characteristic curves to relate the two adherence measures, and we used the Wilcoxon rank-sum test to assess the relation between adherence and viral load. In sixty-five subjects, the majority of whom were African American and male with median age of 44 years, pharmacy refill adherence was difficult to collect retrospectively, was not significantly correlated with EDM adherence, and was not significantly related to viral load. Ninety-day supply pharmacy refill adherence correctly classified 95% EDM adherence maximally at 94 days between refills, and the measure was most sensitive for non-adherence at <90 days. Reassessment of the relation between pharmacy refill data and EDM would be warranted when pharmacy refill data is collected as soon as feasible from sources with complete data capture.AIDS and Behavior 12/2008; 14(4):748-54. DOI:10.1007/s10461-008-9502-1 · 3.49 Impact Factor
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ABSTRACT: While the relationship between average adherence to HIV potent antiretroviral therapy is well defined, the relationship between patterns of adherence within adherence strata has not been investigated. We examined medication event monitoring system (MEMS) defined adherence patterns and their relation to subsequent virologic rebound. We selected subjects with at least 3-months of previous virologic suppression on a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen from two prospective cohorts in France and North America. We assessed the risk of virologic rebound, defined as HIV RNA of >400 copies/mL according to several MEMS adherence measurements. Seventy two subjects were studied, five of them experienced virologic rebound. Subjects with and without virologic rebound had similar baseline characteristics including treatment durations, regimen (efavirenz vs nevirapine), and dosing schedule. Each 10% increase in average adherence decreased the risk of virologic rebound (OR = 0.56; 95% confidence interval (CI) [0.37, 0.81], P<0.002). Each additional consecutive day off therapy for the longest treatment interruption (OR = 1.34; 95%CI [1.15, 1.68], P<0.0001) and each additional treatment interruption for more than 2 days (OR = 1.38; 95%CI [1.13, 1.77], P<0.002) increased the risk of virologic rebound. In those with low-to-moderate adherence (i.e. <80%), treatment interruption duration (16.2 days versus 6.1 days in the control group, P<0.02), but not average adherence (53.1% vs 55.9%, respectively, P = 0.65) was significantly associated with virologic rebound. Sustained treatment interruption may pose a greater risk of virologic rebound on NNRTI therapy than the same number of interspersed missed doses at low-to-moderate adherence.PLoS ONE 07/2008; 3(7):e2783. DOI:10.1371/journal.pone.0002783 · 3.53 Impact Factor
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ABSTRACT: There is a paucity of data on the health care costs of antiretroviral therapy (ART) programmes in Africa. Our objectives were to describe the direct heath care costs and establish the cost drivers over time in an HIV managed care programme in Southern Africa. We analysed the direct costs of treating HIV-infected adults enrolled in the managed care programme from 3 years before starting non-nucleoside reverse transcriptase inhibitor-based ART up to 5 years afterwards. The CD4 cell count criterion for starting ART was <350 cells/microl. We explored associations between variables and mean total costs over time using a generalised linear model with a log-link function and a gamma distribution. Our cohort consisted of 10,735 patients (59.4% women) with 594,497 mo of follow up data (50.9% of months on ART). Median baseline CD4+ cell count and viral load were 125 cells/microl and 5.16 log(10) copies/ml respectively. There was a peak in costs in the period around ART initiation (from 4 mo before until 4 mo after starting ART) driven largely by hospitalisation, following which costs plateaued for 5 years. The variables associated with changes in mean total costs varied with time. Key early associations with higher costs were low baseline CD4+ cell count, high baseline HIV viral load, and shorter duration in HIV care prior to starting ART; whilst later associations with higher costs were lower ART adherence, switching to protease inhibitor-based ART, and starting ART at an older age. Drivers of mean total costs changed considerably over time. Starting ART at higher CD4 counts or longer pre-ART care should reduce early costs. Monitoring ART adherence and interventions to improve it should reduce later costs. Cost models of ART should take into account these time-dependent cost drivers, and include costs before starting ART. Please see later in the article for the Editors' Summary.PLoS Medicine 12/2009; 6(12):e1000189. DOI:10.1371/journal.pmed.1000189 · 14.00 Impact Factor