1. Factors Associated with Survival in HIV-Infected African Patients on Antiretroviral Therapy: The Impact of a Sampling-Based Approach to Address Losses to Follow-up Elvin H. Geng 1, David R. Bangsberg 2, Nicholas Musinguzi 3, Nneka Emenyonu 2, Mwebesa Bwana 3, David V. Glidden 1, Constantin T. Yiannoutsos 4, Tor Neilands 1, Steven G. Deeks 1, and Jeffrey N. Martin 1 1 University of California, San Francisco; 2 Harvard Initiative on Global Health, Massachusetts General Hospital; 3 Mbarara University of Science and Technology, Mbarara, Uganda; 4 Indiana University, Indianapolis, Indiana Introduction In cohort analyses, losses to follow-up which are differential on both exposures of interest (e.g., pre-therapy CD4 count) and the outcome (e.g., mortality) are a major threat to the validity of both descriptive and analytic findings. This type of loss to follow-up, a form of selection bias, occurs in a high proportion of HIV infected patients on antiretroviral therapy (ART) in Africa. Losses to follow-up therefore likely represent an important barrier to understanding the impact of ART delivery, identifying determinants of survival and developing evidence-based strategies to optimize care. Although the high numbers of loss in Africa preclude finding true outcomes on all lost patients, the bias incurred by losses to follow-up in cohort analyses can be corrected by empiric ascertainment of vital status through tracking a representative sample of lost patients in the community. Conclusions Ascertainment of vital status in a high proportion of a sample of patients lost to follow-up from ART treatment programs in Africa is feasible and therefore a means of correcting analyses to identify determinants of mortality. Findings of the naïve analysis that did not account for losses to follow-up were dramatically biased. After adjustment for other factors, this bias lead to both (1) identification of spurious associations with mortality (male sex) as well as (2) failure to identify significant associations with mortality (age, weight, calendar year of ART initiation). Patients We evaluated HIV-infected adults starting ART between Jan. 1, 2004 and Sept. 30, 2007 at the Immune Suppression Clinic in Mbarara, Uganda. Loss to follow-up was defined as not returning to care for > 6 months. Objectives To demonstrate the effect of a sampling-based approach on analyses to identify factors associated with mortality in a clinic-based cohort of HIV- infected patients on ART in rural Uganda. Implications Observational epidemiology, a chief means of providing scientific evidence for the public-health approach, must address losses to follow-up in the setting of African ART delivery to identify valid determinants of mortality. Tracking a sample of lost patients to determine vital status in clinic-based cohorts in Africa is a potentially generalizable solution to the scientific obstacles created by losses to follow-up. Tracking a sample of patients lost to follow-up in the community to determine true vital status can strengthen the quality of evidence used by policy makers and help to optimize global ART delivery. Results In the naïve analysis, male sex and pretherapy CD4 count were found to be significantly associated with mortality after adjustment for other factors. Results 3628 patients started ART between January 1, 2004 and Sept. 30 2007 and 829 became lost to follow-up (cumulative incidence of 16, 30 and 39% at 1, 2 and 3 years respectively). Vital status in 128 (15%) of 829 lost patients was sought though tracking in the community. Of the 128 tracked patients, 111 (87%) had vital status ascertainment (32 deceased and 79 alive). All patients lost to follow-up Those tracked with vital status ascertained P-value Number 718111 % female 58590.66 Age, median (IQR) 36 (31-42)35 (29-42)0.84 Baseline CD4 count, median (IQR) 72 (19-144)75 (20-191)0.44 In the sample-corrected analysis, pretherapy CD4 count remained a significant predictor of mortality. However, age, weight and calendar year of ART initiation were found to be significantly associated with mortality whereas in the naïve analysis they were not. Furthermore, male sex, which was found to be strongly (HR=1.86) and significantly (p=0.03) associated with mortality in the naïve analysis, was not associated with mortality in the sample-corrected analysis. Factors associated with mortality in the naïve analysis Factors associated with mortality in the sample-corrected analysis Patients with vital status outcomes ascertained through tracking in the community were similar to all patients lost to follow-up. Lost patients who had vital status ascertained through tracking were assigned a probability weight in order to allow them to represent outcomes in all patients lost to follow-up in the corrected analysis. The weight is the ratio of all those lost to follow-up / those lost with vital status ascertained. Measurements An unselected and consecutive sample of those lost to follow-up were sought in the community by a health educator on motorcycle who attempted to ascertain their true vital status (alive or dead). Demographic (age, sex, distance from home to clinic, ART start year) and clinical (pretherapy CD4, weight, and WHO stage) predictor variables were collected through routine clinical care and obtained from the clinic electronic medical record system. Analyses Naïve analysis (using only passively ascertained deaths) and sample- corrected analysis (incorporating updated vital status in the tracked patients) were conducted with Cox proportional hazards models. Missing pretherapy CD4 values were addressed with multiple imputation.