Incidence and predictors of death, retention, and switch to second-line regimens in antiretroviral- treated patients in sub-Saharan African Sites with comprehensive monitoring availability.
ABSTRACT Antiretroviral treatment programs in sub-Saharan Africa have high rates of early mortality and loss to follow-up. Switching to second-line regimens is often delayed because of limited access to laboratory monitoring.
Retrospective analysis was performed of a cohort of adults who initiated a standard first-line antiretroviral treatment at 5 public sector sites in 3 African countries. Monitoring included routine CD4 cell counts, human immunodeficiency virus RNA measures, and records of whether appointments were kept. Incidence and predictors of death, loss to follow-up, and switch to second-line regimens were analyzed by time-to-event approaches.
A total of 3749 patients were analyzed; at baseline, 37.1% were classified as having World Health Organization disease stage 3 or 4, and the median CD4 cell count was 192 cells/mL. First-line regimens were nevirapine based in 96.5% of patients; 17.7% of patients attended <95% of their drug pickup appointments. During 4545 person-years of follow-up, mortality was 8.6 deaths per 100 person-years and was predicted by lower baseline CD4 cell count, lower hemoglobin level, and lower body mass index (calculated as weight in kilograms divided by the square of height in meters); more-advanced clinical stage of infection; male sex; and more missed drug pickup appointments. Dropouts (which accrued at a rate of 2.1 dropouts per 100 person-years) were predicted by a lower body mass index, more missed visits and missed drug pickup appointments, and later calendar year. Incidence of switches to second-line regimens was 4.9 per 100 person-years; increased hazards were observed with lower CD4 cell count and earlier calendar year at baseline. In patients who switched, virological failure was predicted by combined clinical and CD4 criteria with 74% sensitivity and 30% specificity.
In an antiretroviral treatment program employing comprehensive monitoring, the probability of switching to second-line therapy was limited. Regular pickup of medication was a predictor of survival and was also strongly predictive of patient retention.
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ABSTRACT: The Zambian Ministry of Health has scaled-up human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) care and treatment services at primary care clinics in Lusaka, using predominately nonphysician clinicians. To report on the feasibility and early outcomes of the program. Open cohort evaluation of antiretroviral-naive adults treated at 18 primary care facilities between April 26, 2004, and November 5, 2005. Data were entered in real time into an electronic patient tracking system. Those meeting criteria for antiretroviral therapy (ART) received drugs according to Zambian national guidelines. Survival, regimen failure rates, and CD4 cell response. We enrolled 21,755 adults into HIV care, and 16,198 (75%) started ART. Among those starting ART, 9864 (61%) were women. Of 15,866 patients with documented World Health Organization (WHO) staging, 11,573 (73%) were stage III or IV, and the mean (SD) entry CD4 cell count among the 15,336 patients with a baseline result was 143/microL (123/microL). Of 1142 patients receiving ART who died, 1120 had a reliable date of death. Of these patients, 792 (71%) died within 90 days of starting therapy (early mortality rate: 26 per 100 patient-years), and 328 (29%) died after 90 days (post-90-day mortality rate: 5.0 per 100 patient-years). In multivariable analysis, mortality was strongly associated with CD4 cell count between 50/microL and 199/microL (adjusted hazard ratio [AHR], 1.4; 95% confidence interval [CI], 1.0-2.0), CD4 cell count less than 50/microL (AHR, 2.2; 95% CI, 1.5-3.1), WHO stage III disease (AHR, 1.8; 95% CI, 1.3-2.4), WHO stage IV disease (AHR, 2.9; 95% CI, 2.0-4.3), low body mass index (<16; AHR,2.4; 95% CI, 1.8-3.2), severe anemia (<8.0 g/dL; AHR, 3.1; 95% CI, 2.3-4.0), and poor adherence to therapy (AHR, 2.9; 95% CI, 2.2-3.9). Of 11,714 patients at risk, 861 failed therapy by clinical criteria (rate, 13 per 100 patient-years). The mean (SD) CD4 cell count increase was 175/microL (174/microL) in 1361 of 1519 patients (90%) receiving treatment long enough to have a 12-month repeat. Massive scale-up of HIV and AIDS treatment services with good clinical outcomes is feasible in primary care settings in sub-Saharan Africa. Most mortality occurs early, suggesting that earlier diagnosis and treatment may improve outcomes.JAMA The Journal of the American Medical Association 08/2006; 296(7):782-93. · 29.98 Impact Factor
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ABSTRACT: Maintaining treatment adherence among the growing number of patients receiving antiretroviral treatment in Africa is a dramatic challenge. The objective of our study was to explore the results of a computerized pill count method and to test the validity, sensitivity, and specificity of this method with respect to viral load measurement in an African setting. We performed a prospective, observational study involving patients who received first-line highly active antiretroviral therapy in Mozambique from 1 April 2005 through 31 March 2006. Enrolled patients had received treatment for at least 3 months before the study. For defining treatment adherence levels, pill counts were used, and the results were analyzed with viral load measurements at the end of the observation period. The study involved 531 participants. During the 12 months of observation, 137 patients left the program or discontinued first-line therapy. Of the remaining 394 patients, 284 (72.1%) had >95% treatment adherence; of those 284 patients, 274 (96.5%) had a final viral load <1000 copies/mL. A Cox proportional hazards analysis revealed that the relationship between >95% treatment adherence and the final viral load was closer than that between >90% treatment adherence and viral load. Treatment adherence >95% maximizes the results of the nonnucleoside reverse-transcriptase inhibitor-based regimen. The pill count method appears to be a reliable and economic tool for monitoring treatment adherence in resource-limited settings.Clinical Infectious Diseases 05/2008; 46(10):1609-16. · 9.37 Impact Factor
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ABSTRACT: In lower-income countries, WHO recommends a population-based approach to antiretroviral treatment with standardised regimens and clinical decision making based on clinical status and, where available CD4 cell count, rather than viral load. Our aim was to study the potential consequences of such monitoring strategies, especially in terms of survival and resistance development. A validated computer simulation model of HIV infection and the effect of antiretroviral therapy was used to compare survival, use of second-line regimens, and development of resistance that result from different strategies-based on viral load, CD4 cell count, or clinical observation alone-for determining when to switch people starting antiretroviral treatment with the WHO-recommended first-line regimen of stavudine, lamivudine, and nevirapine to second-line antiretroviral treatment. Over 5 years, the predicted proportion of potential life-years survived was 83% with viral load monitoring (switch when viral load >500 copies per mL), 82% with CD4 cell count monitoring (switch at 50% drop from peak), and 82% with clinical monitoring (switch when two new WHO stage 3 events or a WHO stage 4 event occur). Corresponding values over 20 years were 67%, 64%, and 64%. Findings were robust to variations in model specification in extensive univariable and multivariable sensitivity analyses. Although survival was slightly longer with viral load monitoring, this strategy was not the most cost effective. For patients on the first-line regimen of stavudine, lamivudine, and nevirapine the benefits of viral load or CD4 cell count monitoring over clinical monitoring alone are modest. Development of cheap and robust versions of these assays is important, but widening access to antiretrovirals-with or without laboratory monitoring-is currently the highest priority.The Lancet 04/2008; 371(9622):1443-51. · 39.06 Impact Factor