Retention in Care among HIV-infected Patients Receiving Antiretroviral Therapy in Africa: Estimation via a Sampling-based Approach Elvin Geng 1, David.

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Retention in Care among HIV-infected Patients Receiving Antiretroviral Therapy in Africa: Estimation via a Sampling-based Approach Elvin Geng 1, David Glidden 1, David Bangsberg 2,3, Mwebesa Bwana 3, Nicolas Musinguzi 3, Nneka Emenyonu 2,3, Winnie Muyindike 3, Isaac Kigozi 3, Katerina Christopoulos 1, Torsten Neilands 1, Constantin Yiannoutsos 4, Steven Deeks 1 and Jeffrey Martin 1 1 University of California, San Francisco; 2 Massachusetts General Hospital, SF, CA; Massachusetts General Hospital, Harvard Medical School, Boston, MA; 3 Mbarara University of Science and Technology, Mbarara, Uganda ; 4 Department of Medicine, Indiana University, Indianapolis, IN; and the East Africa International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortium (all). Retention in care is a fundamental measure of the effectiveness of the global effort to deliver ART in resource limited settings. Existing estimates of retention have assumed that patients who are lost to follow-up (i.e., who have unknown outcomes) are no longer engaged in care and these estimates of retention are alarmingly low. In the setting of rapid decentralization of ART services, this assumption may not be true. Estimating retention in care therefore requires incorporating updated outcomes among those lost to follow-up (i.e., are they still in care). Given the scale of the ART roll-out, ascertaining updated outcomes in all patients lost to follow-up is rarely feasible. Conclusions HIV-infected adults starting ART between Jan. 1, 2004 and Sept. 30, 2007 at the Immune Suppression Syndrome (ISS) Clinic in Mbarara, Uganda. Objectives Estimate retention in care through a sampling-based approach in a clinic-based cohort of HIV-infected patients on ART in rural Uganda. Implications 829 became lost to follow-up – defined by 6 months of absence from the ISS Clinic for a cumulative incidence of 16, 30 and 39% at 1, 2 and 3 years respectively. Updated information in 128 (15%) of 829 lost patients was sought though tracking in the community and was obtained in 111 (87%). 79 of 111 patients were found to be alive. In 48 (61%) cases, the patients was directly contacted and in 31(39%) cases an informant was interviewed. Among the 48 patients whom had been lost, tracked and directly interviewed, 35 (73%) indicated they had seen a provider for HIV care in the past 3 months and were taking ART in the 30 days and were considered retained in care. A “naïve” analysis made use only of outcomes known to the clinic passively. “Corrected” analyses incorporated the outcomes of tracking through a probability weight. If an informant was interviewed, we did not ask whether the patient was still engaged in care because this could inadvertently violate the privacy of the patient. We conducted a sensitivity analysis using a “pessimistic” assumption that patients who were alive but not directly interviewed were not retained in care and a “optimistic” assumption that all patients alive remained in care. Socio-demographic and clinical data were obtained during routine clinical care. Patients considered no longer retained in care at the ISS Clinic if they had no visits for at least 3 months after scheduled return. An unselected and consecutive sample of patients lost to follow- up were sought in the community by a tracker on motorcycle to obtain updated information about their engagement in care. Patients with unknown outcomes at the ISS clinic who were found by the tracker were considered to be retained in care if they had seen an HIV provider at a new site in the last 3 months and taken ART in the last 30 days. Estimates of retention in care, n=3628 Estimates of survival and retention in care NaiveCorrected (pessimistic)Corrected (optimistic) Background Patient Characteristics, n=3628 Analyses Tracking Outcomes The cumulative incidence of becoming not retained in care was estimated in the presence of a competing risk event - death. Lost patients who had vital status ascertained through tracking were assigned a probability weight to allow them to represent outcomes in all patients lost to follow-up in the corrected analysis. To our knowledge, this is the first explicit estimate of retention in care rather than retention in clinic. Retention in care is substantially higher than previous estimates. In a typical scale up setting where decentralization is occurring rapidly, most patients lost to follow-up were in care elsewhere. We also found evidence of the process of decentralization: in patients lost from ISS Clinic, those who lived farther away and whose last visit was at a later calendar time were more likely to be retained in care elsewhere. Retention in care is feasible to estimate through a sampling-based approach and should be featured as an indictor of effectiveness in the global ART delivery effort. Loss to follow-up is not an informative indicator of program effectiveness because it combines poor outcomes (i.e.., deaths and being out of care) and favorable outcomes (i.e., unascertained transfers) and may therefore be artifactually influenced by decentralization. Given the high numbers of unascertained transfers, estimates of the total number of patients starting ART may be inflated. Efforts to find and re-engage patients who have become lost from a particular clinic should target only patients who are most likely unengaged in care (rather than all lost to follow-up). This will save resources that can be used to maximize the number of patients starting ART. NaïveCorrected (pessimistic)Corrected (optimistic) Time (years) Retention in care Retention and survivalRetention in care Retention and survivalRetention in care Retention and survival 184.2%82.7%91.2%86.4%95.3%90.9% 270.5%68.8%81.6%75.2%91.3%85.5% 361.6%59.7%79.2%72.0%90.0%83.6% Patients Measurements Time (years)NaïveCorrected (pessimistic)Corrected (optimistic) 184.2%91.2%95.3% 270.5%81.6%91.3% 361.6%79.2%90.0% Determinants of retention in care in a sample of patients lost to follow up and sought in the community (n=48) FactorISS Clinic, Mbarara, Uganda Age, years, (median, IQR)* 35 (30-41) Male Sex, n(%)1408 (39) Pre-therapy CD4 c/cc3, (median, IQR) † 117 (48-197) Weight, kg (median,IQR) ‡ 54 (47-60) WHO stage 4, n (%) € 745 (22) ART start year (14) 20051,380 (38) (25) (21) Distance from clinic to residence ¥ 35.4 ( ) * Missing in 31, † missing in 1036; ‡ missing in 227, € missing in 1403, ¥ missing in 740 Patient Follow-up