A Prospective Cohort Study on the effects of

A Prospective Cohort Study on the effects of Hormonal Contraception on the Natural History of HIV disease among women in Nairobi and Harare Collaborating institutions: KEMRI, UCSF, UZ, WHO

Background n As of 2005, approx 18 M women were HIVinfected worldwide and 80% in sub-Saharan Africa 100 M globally use hormonal contraception n Increasing HC use in HIV prevalent areas n n Effective contraception, a preventive tool for unintended pregnancies and in reducing proportion of HIV-infected children

Potential Interactions between steroid hormones and HIV Plausible mechanisms for HIV-HC interactions n Direct effects Binds directly to the HIV regulatory protein and enhances replication hence increasing viral load n Indirect effects Influencing both humoral and cell-mediated by either increasing or decreasing various cytokines

Previous studies n n n Hunt J et al, 1998 described a direct effect on virus expression via hormone response elements within the HIV-1 promoter. Marx et al, 1996 described an SIV macaque model and demonstrated increased infectivity with Progesterone treatment (thinning of the vaginal epithelium. Lavreys L, et al, 2003 found that DMPA use at the time of HIV-1 acquisition and the presence of a GUD during the early phase of infection were associated with higher levels of HIV-1 replication. Martin H et al, 1998 reported increased HIV-1 acquisition and other STI among women (CSW) using DMPA Sagar M et al, 2003 reported an association of COC use at the time of HIV-1 infection with increased risk of acquiring multiple HIV-1 genotypes leading to higher viral set points and rapid progression

Justification n Previous studies have demonstrated effects of hormones in animal models and among high risk populations Currently limited data exists on the effects of HC on HIV progression among women in the general population Increasing concern among health care providers on the possibility of rapid disease progression among HIV infected women using HC methods

Overall Objective To determine the effects of hormonal contraception on HIV-1 disease progression among women in Nairobi and Harare

Specific Objectives n n n To determine the effects of COC and DMPA on the rate of CD 4 decline To determine the effects of COC and DMPA on WHO clinical staging To determine the effects of COC and DMPA on plasma viral load

Methods Study Design: Prospective Cohort Study (2000 -2005) Study Sites: Nairobi, Kenya and Harare, Zimbabwe Study Population: HIV-1 infected women aged 18 -49 yrs presenting to FP facilities with CD 4 count >500 cells/µL and on self selected FP method (COC, DMPA, non-Hormonal contraceptive methods) for at least 3 months

Clinical and Laboratory procedures At enrolment and every 6 month follow up visit: n a medical history including social, sexual, contraceptive and examination performed using a structured questionnaire n n Hemogram, RPR, CD 4 count, plasma viral load measurement Annual pap smear test

Data Analysis n A Univariate comparison of baseline characteristics was done by COC, DMPA vs. non-HC methods. Potential confounding was controlled for all multivariate models. n Survival Analysis (univariate comparison of mean change in CD 4 counts by contraceptive method over time). n Linear Mixed Effects Models, multivariate analysis of the rate of CD 4 decline by contraceptive method. n n Cox Proportional Hazards Models (Multivariate analysis of factors associated with time to advanced HIV disease stages (III and IV). Considered two scenarios: 1) Analysis of outcomes while excluding non compliant contraceptive users and 2) the intention to treat analysis, included all non-compliant subjects

Results n A total of 498 women enrolled beginning the year 2000 and followed through to 2005 n Median follow up of 2 (0 -4) years n Mean age of 27. 45 (5. 3) years n 77% were married

Fig 1: Patient enrolment and follow up flow chart Total number of subjects enrolled: 498 Nairobi: 302 (60. 6%) Harare: 196(39. 4%) Total number excluded from analysis 9 (1. 8%) women on Norplant Overall with contraceptive change for both sites 127 (25. 6%) Nairobi: 7 (1. 4%) Harare: 2 (0. 4%) DMPA/COC to non-HC: 36 (28. 3%) Non-HC to COC/DMPA: 39 (30. 7%) Vice versa: 14 (11%) Pregnant: 38 (29. 9%) Overall number analyzed by contraceptive method and site: 336 (%) Nairobi: 217 (59. 3%) Harare: 149 (40. 7%) COC: 36 (16. 6%) COC=54(36. 2%) DMPA: 98 (45. 2%) DMPA: 46 (30. 9%) Non-HC: 83(38. 2%) Non-HC: 49(32. 9%) Overall Outcomes by Contraceptive Method 4 (1. 1%) of deaths COC: 0 (0%) DMPA: 3( 75%) Non–HC: 1 (25%) 27 (7. 4%) with CD 4 <200 cells/µL in 4 years COC: 2(7. 4%) DMPA: 15(55. 6%) Non-HC: 10(37%)

Table 1: Sociodemograhic characteristics by contraceptive method among HIV-1 infected women in Nairobi and Harare Characteristic COC N= 90 (24. 7%) DMPA N= 144 (39. 2%) Non-HC N= 132 (36. 2%) Study site: Kenya Zimbabwe 36(40. 0%) 54(60. 0%) 98(68. 1%) 46(31. 9%) 83(62. 9%) 49(37. 1%) 0. 000 Mean age (sd) yrs 27. 5 (5. 31) 26. 2(4. 5) 29. 9 (6. 56) 0. 000 Education None Primary Secondary College 0 (0%) 38(42. 2%) 51(56. 7%) 1(1. 1%) 1 (0. 7%) 66 (46. 2%) 75 (52. 4%) 1 (0. 7%) 4 (3. 0%) 44 (33. 3%) 66 (50. 0%) 18 (13. 6%) 0. 000 Marital Status Single (never married) Married (cohabiting) Regular partn(not cohabiting) Divorced/separated/widowed 0(0%) 84(93. 3%) 4 (4. 4%) 2 (2. 2%) 2 (1. 4%) 126 (87. 5%) 9 (6. 3%) 7 (4. 9%) 12 66 21 32 0. 000 Current smoker 2 (2. 2%) 3 (2. 1%) 11(8. 3%) 0. 028 Currrent alcoholic drinks 23(25. 6%) 25(17. 4%) 47(35. 6%) 0. 003 (9. 2%) (50. 4%) (16. 0%) (24. 4%) P-value

Table 1 continued: Sexual history by contraceptive method Characteristic COC DMPA Non-HC P-value Mean (sd) age of sexual debut (yrs) 17. 8 (2. 54) 16. 87(2. 44) 17. 7(2. 94) 0. 02 37 (41. 1%) 39 (43. 3%) 13 (14. 4%) 1 (1. 1%) 38(26. 4%) 69(47. 9%) 35(24. 3%) 2(1. 4%) 31(23. 5%) 53(40. 2%) 34(25. 8%) 14(10. 6%) 0. 000 Never Less than half More than half always 60 (68. 2%) 7 (8. 0%) 9 (10. 2%) 12(13. 6%) 95 (78. 5%) 10 (8. 3%) 5 (4. 1%) 11 (9. 1%) 13 (17. 6%) 3 (4. 1%) 4 (5. 4%) 54(73. 0%) 0. 000 Currently having other sexual partners 2(2. 2%) 3(2. 1%) 20(15. 2%) 0. 000 No of lifetime sexual partners One 2 -3 4 -10 11 and more Condom use with regular partner

Table 1 continued: Sexual, reproductive history and Clinical parameters by contraceptive method Characteristic COC DMPA Non-HC P-value Ever exchanged sex for money or gifts 2(2. 2%) 4(2. 8%) 20(15. 2%) 0. 000 37 (41. 1%) 39 (43. 3%) 13 (14. 4%) 1 (1. 1%) 38 (26. 4%) 69 (47. 9%) 35 (24. 3%) 2 (1. 4%) 31(23. 5%) 53 (40. 2%) 34 (25. 8%) 14 (10. 6%) 0. 000 Reproductive history Currently breastfeeding Median (range) number of births 24 (26. 7%) 2 (1 -5) 57 (39. 6%) 2 (1 -6) 16 (12. 2%) 2 (0 -8) 0. 000 CD 4 count, median (range) 639 (502 -1457) 684 (505 -1383) 630 (500 -1689) 0. 343 Baseline WHO clinical stages WHO stage II 80 (88. 9%) 10 (11. 1%) 126 (87. 5%) 18 (12. 5%) 117(90. 0%) 13 (10. 0%) 0. 807 Lifetime number of sexual partners: One 2 -3 4 -10 11 or more

Table 2: Multivariate analysis of the association of contraceptive use on CD 4 count decline among HIV-1 infected women in Nairobi and Harare Characteristic Estimate (95% CI) P-value Study site Kenya Zimbabwe 0. 015 (-0. 066, 0. 096) ref 0. 719 - Age (mean, SD) years -0. 001 (-0. 008, 0. 006) 0. 749 Contraceptive method COC DMPA Non-HC -0. 266 (-0. 612, 0. 081) -0. 145 (-0. 426, 0. 137) ref 0. 133 0. 313 - Baseline CD 4 count 0. 001 (0. 000, 0. 002) 0. 024 WHO Disease Staging Stage II Advanced stage 0. 464 (-0. 223, 1. 152) 0. 198 (-0. 511, 0. 908) ref 0. 185 0. 584 - Age of sexual debut -0. 017 (-0. 032, -0. 003) 0. 019

Table 3: Multivariate analysis of the association of contraceptive use with time to advanced WHO clinical stages among HIV-1 infected women in Nairobi and Harare Covariate Adjusted HR (95%CI) P-value Study site Kenya Zimbabwe 0. 30 (0. 11, 0. 82) ref . 018 - Age (years) 1. 12 (1. 03, 1. 21) . 006 Contraceptive method COC DMPA Non-HC 0. 91 (0. 25, 3. 27) 0. 56 (0. 19, 1. 64) ref 0. 883 0. 290 - Initial CD 4 count 0. 994 (0. 990, 0. 999) 0. 021 1. 84(0. 12, 27. 63) 0. 12 (0. 02, 0. 88) 0. 32 (0. 05, 1. 87) ref 0. 658 0. 038 0. 205 - Education level None Primary Secondary Post Secondary

Table 3 continued…. : Multivariate analysis of the association of contraceptive use with time to advanced disease Covariate HR (95% CI) P-value Had support from friends 1. 56 (0. 58, 4. 22) 0. 378 Had support from other groups 1. 57 (0. 55, 4. 49) 0. 400 Let others know of their HIV status 0. 28 (0. 10, 0. 78) 0. 015 Body weight 0. 95 (0. 91, 0. 99) 0. 010 0. 98 (0. 81, 1. 18) 1. 86 (0. 62, 0. 77) 0. 21 (0. 06, 0. 77) 0. 804 0. 271 0. 019 Psychosocial characteristics Sexual and social behavior Age of sexual debut Taking alcoholic beverages Exchanged sex for gifts

Fig 2: Kaplan Meier Curves for survival to advanced WHO clinical stages by contraceptive method 1. 1 1. 0 Method Non-hormonal . 9 DMPA. 8 COC. 7 0 1 2 Time in years 3 4 5

Slopes of mean CD 4 count by hormonal contraceptive method 100 0 -100 Method Combined pills -200 DMPA Non-hormonal -300. 00 . 50 1. 00 1. 50 2. 00 2. 50 3. 00 3. 50 4. 00

Mean change in CD 4 count by contraceptive method 100 0 -100 Method Combined pills -200 Mean change in CD 4 100 0 -100 Me -200 DMPA Non-hormonal -300. 00 . 50 1. 00 1. 50 2. 00 2. 50 Follow-up visit (in yrs)) 3. 00 3. 50 4. 00 -300. 00 . 50 1. 00 1. 50 2. 00 2. 50 3. 00 Follow-up visit (in yrs)) 3. 50 4. 00

Kaplan Meier curves on time to WHO advanced disease stages (intent-to-treat analysis) 1. 02 1. 1 1. 00 1. 0 Method Non-hormonal . 9 Metho . 98 non-horm . 96. 94 DMPA dmpa. 92 . 8 COC . 90 combined . 88 . 7 0 1 2 3 Time in years 4 5 0 1 2 3 4 Time to advanced disease (yrs) 5

Comparison of analyses of the effect of contraceptive on CD 4 count decline: intent-to treat analysis vs. per exposure analysis Per exposure Analysis Intent-to-treat Analysis Characteristic Estimate cells/µL/yr (95%CI) Pvalue 0. 268(0. 0173, 0. 362) 0. 215(0. 111, 0. 320) -ref <0. 001 Advanced stage Estimate cells/µL(95%CI) P-value 0. 464(-0. 223, 1. 152) 0. 185 WHO clinical stages I II Characteristic <0. 001 I II Advanced stage 0. 584 0. 198(-0. 511, 0. 908) -ref

Comparison of Multivariate analysis on the effect of HC on time to advanced WHO clinical stages: intent-to-treat vs. per exposure analysis Intent-to-treat analysis Characteristic HR (95%CI) Per exposure analysis Pvalue Country Characteristic HR (95%CI) P-value Kenya 0. 30 (0. 11, 0. 82) 0. 018 Zimbabwe Ref Ever exchanged sex for gifts 0. 21 (0. 06, 0. 77) Country Kenya 0. 69 (0. 29, 1. 69) Zimbabwe Ref Ever exchanged sex for gifts 0. 310 (0. 095, 1. 011) 0. 427 0. 052 0. 019

Pending Analysis n n Effects of HC on Plasma viral load Effects of COC vs. DMPA on CD 4 decline

Study Limitations n n n Switching from one contraceptive method to another Stringent inclusion criteria thereby missing women who were likely faster progressors Follow up period shorter to attain study endpoints

Discussion n n Differences in baseline CD 4 counts and time to advanced WHO stages by country CD 4 decline compared to other natural history studies Non-HC group risky sexual and social behavior Why findings differ from those among high risk populations: issues of residual confounding in terms of sexual practice or STI

Discussion n n Factors significantly associated with CD 4 decline, faster progression to advanced WHO clinical stages: Baseline CD 4 count, age of sexual debut, age and body weight

Summary n n n Findings suggest that COC and DMPA have no effects on HIV-1 progression among women attending FP facilities in Nairobi and Harare Baseline CD 4 and age of sexual debut were associated with the rate of CD 4 decline. Older age and body weight were associated with faster progression to advanced WHO clinical stages

Summary n These findings will contribute to findings that HIV-1 infected women using either COC or DMPA are not at increased risk of rapid disease progression compared to their counterparts using non hormonal contraceptive methods

Acknowledgements n n n n Dr. Craig Cohen (UCSF) Dr. Tsungai Chipato (UZ) Tim Farley (WHO) Estie Hudes (CAPS, UCSF) Research teams (Kenya and Zimbabwe) Study participants Collaborating institutions (UCSF, KEMRI, UZ) and funding orgs (WHO, CFAR)