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Tenofovir is less toxic than other nucleoside reverse-transcriptase inhibitors used in antiretroviral therapy (ART) and may improve retention of human immunodeficiency virus (HIV)–infected patients on ART. We assessed the impact of national guideline changes in South Africa (2010) and Zambia (2007) recommending tenofovir for first-line ART. We applied regression discontinuity in a prospective cohort study of 52,294 HIV-infected adults initiating first-line ART within 12 months (±12 months) of each guideline change. We compared outcomes in patients presenting just before and after the guideline changes using local linear regression and estimated intention-to-treat effects on initiation of tenofovir, retention in care, and other treatment outcomes at 24 months. We assessed complier causal effects among patients starting tenofovir. The new guidelines increased the percentages of patients initiating tenofovir in South Africa (risk difference (RD) = 81 percentage points, 95% confidence interval (CI): 73, 89) and Zambia (RD = 42 percentage points, 95% CI: 38, 45). With the guideline change, the percentage of single-drug substitutions decreased substantially in South Africa (RD = −15 percentage points, 95% CI: −18, −12). Starting tenofovir also reduced attrition in Zambia (intent-to-treat RD = −1.8% (95% CI: −3.5, −0.1); complier relative risk = 0.74) but not in South Africa (RD = −0.9% (95% CI: −5.9, 4.1); complier relative risk = 0.94). These results highlight the importance of reducing side effects for increasing retention in care, as well as the differences in population impact of policies with heterogeneous treatment effects implemented in different contexts. [ABSTRACT FROM AUTHOR]

Background: HIV prevalence estimates from population-based surveys are vulnerable to selection bias if HIV status is missing for a proportion of the eligible population. Standard approaches, such as imputation, to correct prevalence estimates for selective nonparticipation assume that data are "missing at random." These approaches lead to biased estimates, if unobserved factors are associated with both survey participation and HIV status.Methods: We use Heckman-type selection models to test and correct for selection on unobserved factors (separately for men and women) in the 2007 Zambia Demographic and Health Survey, in which 28% of the 7146 eligible men and 23% of the 7408 eligible women did not participate in HIV testing. Performance of these models depends crucially on selection variables that determine survey participation but do not independently affect HIV status.Results: We identify 2 highly-plausible selection variables that are statistically significant determinants of survey participation: interviewer identity, and visit on the first day of fieldwork in a survey cluster. HIV-positive status was negatively correlated with consent to test in men (ρ = -0.75 [95% confidence interval = -0.94 to -0.18]), but not in women. Adjusting for selection on unobserved variables substantially increased the HIV prevalence estimate for men from 12% (based on measured HIV status alone) and 12% (based on imputation) to 21%. In addition, the adjustment for selection substantially changed the estimated effects of HIV risk factors.Conclusions: Studies of HIV prevalence and risk factors based on surveys with substantial nonparticipation should routinely use Heckman-type selection models to correct for selection on unobserved variables. [ABSTRACT FROM AUTHOR]