Immediate HIV treatment prevents new infections: causal evidence on the real-world impact of immediate vs. deferred ART in rural South Africa Catherine Oldenburg, Jacob Bor, Frank Tanser, Guy Harling, Tinofa Mutevedzi, Maryam Shahmanesh, George Seage, Victor De Gruttola, Matthew Mimiaga, Kenneth Mayer, Deenan Pillay, Till Bärnighausen

Guy Harling has no conflicts of interest to declare

Benefits from immediate ART WHO now recommends immediate ART for all patients regardless of CD4 count Based on evidence from clinical trials Prevention Cohen et al. NEJM 2011, 2016 Health Severe et al. 2011; Grinsztejn et al. 2014; Lundgren et al. 2015; Danel et al. 2015

Little evidence on real world impact But potential gap between trial & real-world Quality of care Generalizability of population Behavioral responses to treatment eligibility

Behavioral response to eligibility Bor et al., CROI 2016

Little evidence on real world impact But potential gap between trial & real-world Differential quality of care Generalizability Behavioral responses to treatment eligibility In real-world settings, observational data

Incidence in partners And even when not in a carefully observed cohort or clinical study, ART substantially protects HIV-negative members of serodiscordant couples Oldenburg, Bärnighausen, Tanser, Iwuji, De Gruttola, Seage, Mimiaga, Mayer, Pillay, Harling, Clin Infect Dis, 2016.

Incidence in the household Beyond the couple, ART is associated with benefits for other-sex household members, associated with 45% reduction in hazard if all members on ART Vandormael, Newell, Bärnighausen, Tanser. Lancet GH, 2014

Incidence in the community And beyond the household, higher levels of ART coverage are associated with reduced population-level incidence. Tanser, Bärnighausen, Grapsa, Zaidi, Newell. Science, 2013

Little evidence on real world impact But potential gap between trial & real-world Differential quality of care Generalizability Behavioral responses to treatment eligibility In real-world settings, observational data May be affected by unobserved confounders

Study aim To estimate the causal, real-world effect of immediate eligibility for ART on: mortality, immune function, HIV incidence in the household We use Regression Discontinuity to identify causal effects RD will allow us to

Study opportunity SA National Treatment Guidelines (2004-2011) CD4 < 200 or Stage IV Initiate ART CD4 ≥ 200 & no Stage IV Return in 6 months

Regression discontinuity design True CD4 count: 200 True CD4 count: 200 True CD4 count: 200 Measured CD4: 188 Measured CD4: 195 Measured CD4: 207 - For example, CD4 counts and ART We have 3 people presenting to care for the first time, all of whom have identical true CD4 counts The first two, our measurement suggests CD4 < 200, so we initiate treatment The last one, CD4 > 200, so we wait Patients presenting just above vs. below 200 are similar on observed and unobserved characteristics…but assigned different exposures – as in an RCT. This amounts to random assignment of people with CD4 counts close to 200 – so we can measure the LOCAL treatment effect of ART Generate an unconfounded estimate, just like an RCT Bor, Mutevedzi, Tanser, Newell, Bärnighausen. Epidemiology, 2014. Moscoe, Bor, Bärnighausen. Journal of Clinical Epidemiology, 2015.

Study setting Africa Centre for Population Health We conducted our analysis in the Africa Centre for Population Health’s demographic surveillance area 2nd poorest district in SA Population participating in surveillance for the past 16 years Very high HIV prevalence and ongoing incidence; adult HIV prevalence of 30%

Study data All DSA residents attending public sector clinics in Hlabisa sub-district First CD4 count between Jan 2007 & July 2011 We see when ART initiated We see regular CD4 counts Mortality from demographic surveillance HIV incidence from population HIV surveillance

CD4 counts at first clinic visit Distribution of first CD4 counts between 50 and 350 Red line at 200 cells No bunching below 200; does not suggest manipulation of CD4 counts

Continuity in baseline observables Dots represent mean values within bins of width 10 cells/μl Green lines are coefficients under and over 200 cells Balance on covariates: as in RCTs

Immediate eligibility raises uptake

Immediate eligibility raises uptake Risk difference: 0.32 95% CI (0.27, 0.38) 2/3 on ART within 6m just below 200; 1/3 on ART just above So the cut-point does what we expected it to do We will now show impact of this roughly doubling of ART, increase of 32 percentage points

Eligibility reduces mortality Hazard Ratio = 0.65 95% CI (0.45, 0.94) Bor, Moscoe, Mutevedzi, Newell, Bärnighausen, Epidemiology, 2014.

Eligibility improves immune health Blue dotted line: 45 degrees. Same CD4 count at baseline and 12m Clear 120-200 cell rise for those eligible; fall off for those not eligible

Persistent impact on CD4 counts 75 cells/μl - 50 cell difference at 1 year, 75 at years 2-3

ART eligibility reduces household HIV incidence Hazard Ratio: 0.55 95%CI (0.35, 0.86)

Potential causal pathways Biological: Reduced viral load Behavioral: Changes in sexual behavior of household member on ART Relational: Social influence on other household members Proposed mechanisms for these reductions: VL, both within a given relationship and across the community Induced changes in ART client sexual behavior, arising directly from counselling or indirectly through experiences of ART or the healthcare system Indirect impact of clients influencing family and friends, thus changing their behaviors

Generalizability All effects are local to CD4 count of 200 May be different at other CD4 count cut-offs But similar effect seen for 350 cells/μl cut-off on ART uptake & retention Bor et al., CROI 2016a, b

Conclusions Immediate eligibility for ART is associated with lower mortality, improved immune function, reduced household HIV incidence Real-world confirmation of trial results & causal confirmation of observational data Both biological and behavioral pathways may contribute to the incidence effect

Acknowledgements Community and staff at the Africa Centre for Population Health KZN Provincial Department of Health Funders: Wellcome Trust (097410/Z/11/Z) NIH (K01-MH105320, R01-AI112339, R01-AI124389, R01-HD084233, R01-HD058482, R25-MH083620, T32-DA013911) You can reach the study team at: ceo242@mail.harvard.edu jbor@bu.edu gharling@hsph.harvard.edu tbarnighausen@africacentre.ac.za

Additional material

Robustness to bandwidth Preferred Spec +/- 150 ADD FIGURE SHOWING HRRD VS BW