Rosen S, Fox MP, Gill CJ. Patient retention in antiretroviral therapy programs in sub-Saharan Africa: a systematic review. PLoS Med. 2007;4(10):e298.
Long-term retention of patients in Africa's rapidly expanding antiretroviral therapy programmes for HIV is essential for these programmes' success but has received relatively little attention. In this paper Rosen and colleagues present a systematic review of patient retention in antiretroviral therapy programmes in sub-Saharan Africa. They searched Medline, other literature databases, conference abstracts, publications archives, and the "grey literature" (project reports available online) between 2000 and 2007 for reports on the proportion of adult patients retained (i.e., remaining in care and on antiretroviral therapy) after 6 months or longer in sub-Saharan African, non-research antiretroviral therapy programs, with and without donor support. Estimated retention rates at 6, 12, and 24 months were calculated and plotted for each program. Retention was also estimated using Kaplan-Meier curves. In sensitivity analyses the authors considered best-case, worst-case, and midpoint scenarios for retention at 2 years; the best-case scenario assumed no further attrition beyond that reported, while the worst-case scenario assumed that attrition would continue in a linear fashion. The authors reviewed 32 publications reporting on 33 patient cohorts (74,192 patients, 13 countries). For all studies, the weighted average follow-up period reported was 9.9 months, after which 77.5% of patients were retained. Loss to follow-up and death accounted for 56% and 40% of attrition, respectively. Weighted mean retention rates as reported were 79.1%, 75.0% and 61.6% at 6, 12, and 24 months, respectively. Of those reporting 24 months of follow-up, the best program retained 85% of patients and the worst retained 46%. Attrition was higher in studies with shorter reporting periods, leading to monthly weighted mean attrition rates of 3.3%/month, 1.9%/month, and 1.6%/month for studies reporting to 6, 12, and 24 months, respectively, and suggesting that overall patient retention may be overestimated in the published reports. In sensitivity analyses, estimated retention rates ranged from 24% in the worse case to 77% in the best case at the end of 2 years, with a plausible midpoint scenario of 50%. Since the inception of large-scale antiretroviral therapy access early in this decade, antiretroviral therapy programs in Africa have retained about 60% of their patients at the end of 2 years. Loss to follow-up was the major cause of attrition, followed by death. Better patient tracing procedures, better understanding of loss to follow-up, and earlier initiation of antiretroviral therapy to reduce mortality are needed if retention is to be improved. Retention varies widely across programmes, and programmes that have achieved higher retention rates can serve as models for future improvements.
Editors’ note: An estimated half of people starting antiretroviral treatment in Africa in programmes that publish their results are no longer receiving treatment after two years. Starting treatment earlier to prevent mortality and concerted efforts to discover and remedy the conditions that lead people to drop out of programmes are obvious first steps. Sharing what works in patient monitoring and tracing, as well as in overcoming transport, nutritional, financial, and other barriers, is urgently needed.
Toure S, Kouadio B, Seyler C, Traore M, Dakoury-Dogbo N, Duvignac J, Diakite N, Karcher S, Grundmann C, Marlink R, Dabis F, Anglaret X; Aconda Study Group. Rapid scaling-up of antiretroviral therapy in 10,000 adults in Côte d’Ivoire: 2-year outcomes and determinants. AIDS. 2008;22(7):873-82.
Toure and colleagues aimed to assess the rates and determinants of mortality, loss to follow-up, and immunological failure in a nongovernmental organization-implemented program of access to antiretroviral treatment in Côte d’Ivoire. In each new treatment center, professionals were trained in HIV care, and a computerized data system was implemented. Individual patient and programme level determinants of survival, loss to follow-u,p and immunological failure were assessed by multivariate analysis. Between May 2004 and February 2007, 10,211 patients started antiretroviral treatment in 19 clinics (median pre-antiretroviral treatment CD4 cell count, 123 cells/microl; initial regimen zidovudine-lamivudine-efavirenz, 20%; stavudine-lamivudine-efavirenz, 22%; stavudine-lamivudine-nevirapine, 52%). At 18 months on antiretroviral treatment, the median gain in CD4 cell count was +202 cells/microlitre, the probability of death was 0.15, and the probability of being loss to follow-up was 0.21. In addition to the commonly reported determinants of impaired outcomes (low CD4 cell count, low BMI, low haemoglobin, advanced clinical stage, old age and poor adherence), two factors were also shown to independently jeopardize prognosis: male sex (men vs. women: hazard ratio = 1.52 for death, 1.27 for loss to follow-up, 1.31 for immunological failure); and attending a recently opened clinic (inexperienced vs. experienced centers: hazard ratio = 1.40 for death, 1.58 for loss to follow-up). None of the three outcomes was associated with the drug regimen. In this rapidly scaling-up program, survival and immune reconstitution were good; women and patients followed up in centers with longer experience had better outcomes; and outcomes were similar in zidovudine/stavudine-based regimens and in efavirenz/nevirapine-based regimens. Decreasing the rate of loss to follow-up should now be the top priority in antiretroviral treatment rollout.
Editors’ note: An easy-to-manage computerized data monitoring system in 10 mostly primary health care units provided real-time indicators of numbers of patients in care and their treatment progress. Male sex was associated with immunological failure, mortality, and higher rates of programme withdrawal, suggesting that these are interlinked. Experienced centres should be twinned with new treatment centres for assistance in monitoring and improving the economical, managerial, logistical, and organizational characteristics that influence patient outcomes.