Date Published: May 20, 2008
Publisher: Public Library of Science
Author(s): Gregory P Bisson, Robert Gross, Scarlett Bellamy, Jesse Chittams, Michael Hislop, Leon Regensberg, Ian Frank, Gary Maartens, Jean B Nachega, David Bangsberg
Abstract: BackgroundWorld Health Organization (WHO) guidelines for monitoring HIV-infected individuals taking combination antiretroviral therapy (cART) in resource-limited settings recommend using CD4+ T cell (CD4) count changes to monitor treatment effectiveness. In practice, however, falling CD4 counts are a consequence, rather than a cause, of virologic failure. Adherence lapses precede virologic failure and, unlike CD4 counts, data on adherence are immediately available to all clinics dispensing cART. However, the accuracy of adherence assessments for predicting future or detecting current virologic failure has not been determined. The goal of this study therefore was to determine the accuracy of adherence assessments for predicting and detecting virologic failure and to compare the accuracy of adherence-based monitoring approaches with approaches monitoring CD4 count changes.Methodology and FindingsWe conducted an observational cohort study among 1,982 of 4,984 (40%) HIV-infected adults initiating non-nucleoside reverse transcriptase inhibitor-based cART in the Aid for AIDS Disease Management Program, which serves nine countries in southern Africa. Pharmacy refill adherence was calculated as the number of months of cART claims submitted divided by the number of complete months between cART initiation and the last refill prior to the endpoint of interest, expressed as a percentage. The main outcome measure was virologic failure defined as a viral load > 1,000 copies/ml (1) at an initial assessment either 6 or 12 mo after cART initiation and (2) after a previous undetectable (i.e., < 400 copies/ml) viral load (breakthrough viremia). Adherence levels outperformed CD4 count changes when used to detect current virologic failure in the first year after cART initiation (area under the receiver operating characteristic [ROC] curves [AUC] were 0.79 and 0.68 [difference = 0.11; 95% CI 0.06 to 0.16; χ2 = 20.1] respectively at 6 mo, and 0.85 and 0.75 [difference = 0.10; 95% CI 0.05 to 0.14; χ2 = 20.2] respectively at 12 mo; p < 0.001 for both comparisons). When used to detect current breakthrough viremia, adherence and CD4 counts were equally accurate (AUCs of 0.68 versus 0.67, respectively [difference = 0.01; 95% CI −0.06 to 0.07]; χ2 = 0.1, p > 0.5). In addition, adherence levels assessed 3 mo prior to viral load assessments were as accurate for virologic failure occurring approximately 3 mo later as were CD4 count changes calculated from cART initiation to the actual time of the viral load assessments, indicating the potential utility of adherence assessments for predicting future, rather than simply detecting current, virologic failure. Moreover, combinations of CD4 count and adherence data appeared useful in identifying patients at very low risk of virologic failure.ConclusionsPharmacy refill adherence assessments were as accurate as CD4 counts for detecting current virologic failure in this cohort of patients on cART and have the potential to predict virologic failure before it occurs. Approaches to cART scale-up in resource-limited settings should include an adherence-based monitoring approach.
Partial Text: As the number of patients on combination antiretroviral therapy (cART) grows worldwide, developing simple, affordable ways of monitoring patients after treatment initiation has become a major public health priority. Since the central paradigm of antiretroviral therapy is suppression of viral replication, and since costs of second-line cART are higher than first-line regimens , monitoring efforts should, as much as possible, focus on preserving the virologic effectiveness of first-line combinations. Failure to identify patients who are at high risk of future virologic failure or who are currently on partially suppressive regimens may result in selection of viral resistance mutations, which have been associated with more rapid disease progression and death [2–4].
There were 5,723 adults who initiated cART and had registration information included in the Aid for AIDS database used in this study. Of these, 739 patients (13%) initiated non-NNRTI-based regimens and were therefore excluded. Of the remaining 4,984, 1,982 (40%) initiating NNRTI-based cART between 20 December 2000 and 28 February 2003 had sufficient paired CD4 count and viral load data both at baseline and at follow-up to be included in at least one of the analyses below. The pretreatment median (interquartile range [IQR]) CD4 counts were slightly lower among those who did not have sufficient follow-up data (144 [61 to 223] versus 165 [75 to 241] cells/μl), and the median (IQR) viral loads were similar (5.12 [4.6 to 5.6] among those included versus 5.16 [4.7 to 5.6] log10 copies/ml among those not included). All patients meeting inclusion criteria described above were analyzed. Of 1,982 patients, 890 (45%) initiated zidovudine, lamivudine, and efavirenz; 538 (27%) initiated zidovudine, lamivudine, and nevirapine; 206 (10%) initiated didanosine, stavudine, and an NNRTI; the remaining 348 (18%) initiated other three-drug, NNRTI-based regimens.
These results demonstrate that adherence levels, as estimated by pharmacy claims data, can be at least as accurate as CD4 count changes for detection of virologic failure among patients receiving cART. This finding was consistent when evaluating patients at two time points during the first year and after initial virologic suppression, and was not dependent on the level of viremia used to define virologic failure. Because cART scale-up guidelines for resource-limited settings suggest use of CD4 count monitoring after cART initiation , these findings are relevant to ongoing antiretroviral treatment efforts in resource-limited settings.