1. The Immunologic Efficacy of Antiretroviral Therapy for HIV-infected Patients in North America and Africa IeDEA 2010 San Francisco, CA

2. Acknowledgements Southern Africa Robin Wood Jean Nachega Mattias Egger Andrew Boulle Denis Nash East Africa Jeffery Martin Steven Deeks Mwebesa Bosco Bwana Nicholas Musinguzi David Bangsberg Philippa Easterbrook Agnes Kiragga Moses Kamya UCSF Biostatistics Torsten Neilands Dave Glidden Eric Vittinghoff Charles E. McCulloch North America Richard Moore Keri Althoff Steven Gange Bryan Lau Jinbing Zhang West Africa Francois Dabis Rudolphe Theibault Indiana University Paula Braitstein Constantin Yiannoutsos Kara-Wools Kaloustian NIH Rosemary McKaig Carlie Williams Melanie Bacon

3. Background Changes in the CD4+ T cell count after ART initiation are a critical determinant of subsequent clinical outcomes. The “immunologic efficacy” – or best expected response of ART – can be estimated by examining CD4+ T cell recovery in persons achieving and maintaining virologic suppression. The immunologic efficacy of ART is heterogeneous and a substantial proportion of individuals fail to achieve a “normal” CD4+ T cell count even after years of suppression of HIV RNA.

4. Background While the immunologic efficacy of ART has been examined in North America, much less is known about resource-limited settings such as Africa. Africa and North America differ with respect to host genetics, environment (e.g., co-infections), and HIV clade. Previous analysis suggested that Africans may have attenuated CD4 recovery during virologic suppression compared to North Americans and Europeans (Lisgaris CROI 2005, De Wolf HIV Obs Datab 2009)

5. CD4 Recovery virologic suppression socio- behavioral factors access: stockouts, transportation immune activation host genetics coinfections age, CD4 nadir, sex, ART regimen Region adherence nutrition tropism, viral subtype

6. Patients and Measurements HIV-infected adult patients from North America and Africa in the International Epidemiologic Databases to Evaluate AIDS (IeDEA) consortium who have: – pretherapy CD4 < 350 cells/mm 3 – achieved HIV RNA < 1000 c/ml within 1 year of starting ART – in centers with serial HIV RNA monitoring Socio-demographic, clinical and laboratory data were collected in course of routine care in clinic-based cohorts and through research protocols in interval cohorts.

7. Analysis Mixed effects linear models to evaluate mean CD4+ T cell count values over time by region, adjusted for age, sex, pre-therapy CD4+ T cell count and pre-therapy plasma HIV RNA level. Random intercepts and slopes to accommodate subject-specific differences in pre-therapy CD4+ T cell count and subsequent CD4+ T cell count trajectories. CD4+ T cell values were square root transformed to accommodate model assumptions that residuals were homoscedastic and normally distributed. Linear splines were introduced with knots at 4 and 12 months to accommodate non-linearity of CD4+ T cell change over time.

8. 5,570 in Africa 2,887 in North America Patients, n=8,457 Boston Baltimore HIVRN MACS WIHS ANRS CepRef Fajara Gugulethu Masiphumelele Aid for Africa UARTO IDI HOMER UW San Francisco KPNC Vanderbilt UAB

9. Characteristics N. America, n=2887 Africa, n=5570 Age, in years*39 (33-45)34 (30-41) Male sex, n (%)2,324 (81)1,790 (32) Pre-therapy CD4+ T cell count, cells/mm 3 161 (63-246)122 (58-190) Pre-therapy plasma HIV RNA, log10 c/ml4.8 (4.4-5.3)5.0 (4.6-5.5) Days between CD4+ T cell determinations92 (62-153)112 (84-124) Number of CD4+ T cell determinations per subject 9 (5-14)4 (2-7) Time between HIV RNA determinations91 (63-126)112 (86-127) Total observation time, years4276 7581 Observation time by subject, years2.4 (1.3-2.8)2.0 (1.2-2.8) Patient Characteristics, n=8,457 * Median (IQR)

10. Time between CD4+ T cell and HIV RNA Determinations CD4+ T cell Determinations HIV RNA Determinations

11. Patient end of observation reasons n=8457 North AmericaAfrica administrative censor, n (%)1,172 (41)2,782 (50) nine month gap without HIV RNA determination, n (%) 448 (16)686 (12) loss to follow up, n (%)387 (13)1,306 (24) regimen switch or stop, n (%)133 (5)11 (0.2) HIV RNA rebound, n (%)692 (24)648 (12) death, n (%)55 (2)137 (2)

12. Pre-therapy CD4 value = 75 c/mm 3 Pre-therapy CD4 value = 25 c/mm 3 Pre-therapy CD4 value = 150 c/mm 3 Pre-therapy CD4 value = 250 c/mm 3 ┼ ┼ ┼ ┼ ┼ ┼ ┼ ┼

13. LTFU Unascertained transfer Continued on drugs with HIV RNA suppression but lower CD4 values led to inability to follow up Stopped drugs and had viral rebound Not in care / died Uninformative censoring Uninformative Potentially informative Not all loss to follow-up is informative on CD4+ T cell slope Because of socioeconomic or structural reasons

14. Time Since ART Initiation The lower values are more likely to be missing. But within “slope history” the probability of CD4+ T cell being missing is not related to the CD4+ T cell values. “MAR” of CD4+ T cell values on CD4+ T cell slope during HIV RNA suppression

15. Conclusions Immunologic efficacy in Africa is moderately attenuated in the first year of ART compared to North Americans. Over the longer term, however, however, immunologic efficacy in Africa exceeds or is equivalent to North Americans. Regional effects of immunologic activation do not appear to represent a strong limitation on the immunologic efficacy of ART in African patients. The attenuated CD4+ T cell recovery among Africans in the first year of ART may be due to co-prevalent or “unmasked” infections such as TB at and around the time of ART initiation.

16. Implications Given suppression of HIV RNA, the potential for long-term immunologic recovery in Africa is not limited as compared to North Americans through the combined effect of host genetics, environmental co-infections and viral factors. Opportunistic infections in African patients present at the time of ART initiation, such as tuberculosis, through attenuation CD4+ T cell recovery in the first year on ART, may contribute to early mortality on ART in Africa. The variability of CD4+ T cell recovery in Africa must be examined to more fully understand regional impact on immunologic efficacy. Further analysis using data with co-prevalent and incident tuberculosis diagnoses is needed to examine the effect of tuberculosis on the immunologic efficacy of ART.