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Effects of injectable progestogen contraception versus the copper intrauterine device on HIV acquisition: sub-study of a pragmatic randomised controlled trial
research-article
Author(s):
G Justus Hofmeyr
1 ,
Mandisa Singata-Madliki
1 ,
Theresa A Lawrie
1
,
2 ,
Eduardo Bergel
4 ,
Marleen Temmerman
3
Publication date (Electronic):
5 April 2017
Publisher:
BMJ Publishing Group
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Abstract
Background
Evidence from observational studies suggests an increased risk of HIV acquisition among women using depot medroxyprogesterone acetate (DMPA) contraception.
Methods
Within the context of a South African programme to increase women's access to the intrauterine contraceptive device (IUD), we conducted a pragmatic, open-label, parallel-arm, randomised controlled trial (RCT) of the IUD versus injectable progestogen contraception (IPC) at two South African hospitals. The primary outcome was pregnancy; secondary outcomes included HIV acquisition. Consenting women attending termination of pregnancy services were randomised after pregnancy termination between July 2009 and November 2012. Condoms were promoted for the prevention of sexually transmitted infections. Voluntary HIV testing was offered at baseline and at 12 or more months later. Findings on HIV acquisition are reported in this article.
Results
HIV acquisition data were available for 1290 initially HIV-negative women who underwent a final study interview at a median of 20 months after randomisation to IPC or an IUD. Baseline group characteristics were comparable. In the IPC group, 545/656 (83%) of participants received DMPA, 96 (15%) received injectable norethisterone enanthate, 14 (2%) received the IUD and one received oral contraception. In the IUD group 609 (96%) received the IUD, 20 (3%) received IPC and 5 (1%) had missing data. According to intention-to-treat analysis, HIV acquisition occurred in 20/656 (3.0%) women in the IPC arm and 22/634 (3.5%) women in the IUD arm (IPC vs IUD, risk ratio 0.88; 95% confidence interval 0.48–1.59; p=0.7).
Conclusions
This sub-study was underpowered to rule out moderate differences in HIV risk, but confirms the feasibility of randomised trial methodology to address this question. Larger RCTs are needed to determine the relative risks of various contraceptive methods on HIV acquisition with greater precision.
Related collections
Most cited references11
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An updated systematic review of epidemiological evidence on hormonal contraceptive methods and HIV acquisition in women
Chelsea Polis, Kathryn M Curtis, Philip C Hannaford … (2016)
Objective and design: Some studies suggest that specific hormonal contraceptive methods [particularly depot medroxyprogesterone acetate (DMPA)] may increase women's HIV acquisition risk. We updated a systematic review to incorporate recent epidemiological data. Methods: We searched for articles published between 15 January 2014 and 15 January 2016 and hand-searched reference lists. We identified longitudinal studies comparing users of a specific hormonal contraceptive method against either nonusers of hormonal contraception or users of another specific hormonal contraceptive method. We added newly identified studies to those in the previous review, assessed study quality, created forest plots to display results, and conducted a meta-analysis for data on DMPA versus non-use of hormonal contraception. Results: We identified 10 new reports of which five were considered ‘unlikely to inform the primary question’. We focus on the other five reports, along with nine from the previous review, which were considered ‘informative but with important limitations’. The preponderance of data for oral contraceptive pills, injectable norethisterone enanthate, and levonorgestrel implants do not suggest an association with HIV acquisition, though data for implants are limited. The new, higher quality studies on DMPA (or nondisaggregated injectables), which had mixed results in terms of statistical significance, had hazard ratios between 1.2 and 1.7, consistent with our meta-analytic estimate for all higher quality studies of hazard ratio 1.4. Conclusion: Although confounding in these observational data cannot be excluded, new information increases concerns about DMPA and HIV acquisition risk in women. If the association is causal, the magnitude of effect is likely hazard ratio 1.5 or less. Data for other hormonal contraceptive methods, including norethisterone enanthate, are largely reassuring.
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Hormonal Contraception and the Risk of HIV Acquisition: An Individual Participant Data Meta-analysis
Charles Morrison, Pai-Lien Chen, Cynthia Kwok … (2015)
Introduction There is ongoing debate whether hormonal contraception (HC) increases the risk of HIV acquisition [1–4]. Strong evidence for an association would have important implications for sexual and reproductive health, particularly in areas of sub-Saharan Africa where the incidence of both HIV infection and unintended pregnancy remain high [5–7]. Contraception has profound benefits for women and societies, including reduced maternal and infant mortality and morbidity, empowerment of women to make choices about fertility, associated economic improvement, and a reduction in the number of babies born with HIV [8]. Although contraceptive prevalence remains low in much of sub-Saharan Africa, combined oral contraceptives (COCs, containing both estrogen and progestin) and the injectable progestins depot-medroxyprogesterone acetate (DMPA, given every 3 mo) and norethisterone enanthate (NET-EN, given every 2 mo) are the most popular contraceptive methods [9], with DMPA being the most commonly used method overall. HC, particularly DMPA, has been reported to be associated with increased risk of HIV acquisition in some, but not all, studies [1–4]. Such a relationship is biologically plausible based on laboratory, animal, and human data [1, 10]. However, many individual studies have important methodological flaws, including lack of accurate measurement of hormonal contraceptive exposures, failure to control for important confounding factors, poor follow-up, and small sample sizes [2, 3]. A systematic review of studies published up to December 2011 [3] and updated to January 15, 2014 [4], did not reach definitive conclusions about the potential risk of HIV acquisition associated with injectable progestins; the authors did not perform a meta-analysis because of concern about between-study heterogeneity, although this was not quantified statistically [3, 4]. A linked technical meeting of the World Health Organization in 2012 requested additional high-quality research to help better inform policy-makers, clinicians, and women about this important reproductive health issue [11]. Examining individual participant data (IPD) from several different studies can overcome some of the methodological limitations of reviews of aggregated data [12]. Our goal was to assess the risk of HIV acquisition associated with different hormonal contraceptives by combining data from large prospective longitudinal studies in an IPD meta-analysis. The specific objectives of this study were (1) to determine whether a woman’s hormonal contraceptive method increases the risk of HIV acquisition compared to women not using HC, (2) to evaluate whether age or herpes simplex virus type 2 (HSV-2) infection status modifies any effect of HC on the risk of HIV acquisition, and (3) to directly compare the risks of HIV acquisition between three groups of hormonal contraceptive (COC, DMPA, and NET-EN) users. Methods The Protection of Human Subjects Committee of FHI 360 approved the study and judged it as exempt research (PHSC #10263). All included studies had relevant country-specific institutional ethical review and regulatory board approvals, and all participants within each study provided written informed consent for study participation. The IPD meta-analysis followed a protocol (S1 Text) and a prespecified analysis plan (S2 Text). We report our findings in accordance with the Preferred Items of Reporting for Systematic Reviews and Meta-Analyses (PRISMA) (S1 Checklist) [13] and a checklist of items specific to IPD meta-analyses (S2 Checklist) [14]. Study Eligibility and Inclusion Criteria Cohort studies that prospectively collected data on both hormonal contraceptive use (COC, DMPA, or NET-EN) and incident HIV-1 infections in women aged 15 to 49 y from sub-Saharan Africa were eligible. We considered randomized controlled trials (RCTs) of HIV prevention interventions as cohort studies because HIV incidence is the outcome and many of these trials collected detailed longitudinal contraception data; several groups have published such secondary analyses of RCT data [15–20]. We excluded studies with 5% missing HIV infection or HC data, or scheduled follow-up visits >6 mo apart. Information Sources We used three sources of information. First, we used a database containing IPD from ten studies that contributed to an IPD meta-analysis of the effects of vaginal practices on the risk of HIV acquisition among women [21], amassed by the Vaginal Practices Research Partnership (VPRP). Second, we sought additional well-documented datasets from prospective cohort studies and RCTs completed by September 30, 2012, by asking collaborators and investigators of HIV prevention trials. Third, we checked the bibliographies of the two published systematic reviews for studies published up to December 2011 [1, 3]. We also checked the bibliography to January 15, 2014, of an updated version of one of the reviews [4]. Study Selection The ten studies contributing to the VPRP IPD meta-analysis [21] all had prospective hormonal contraceptive use data and met all other inclusion criteria. We reviewed the full text of all other identified publications and applied our inclusion and exclusion criteria. For eligible studies involving oral or vaginal microbicides that contained antiretroviral drugs, only data from the non-antiretroviral control arm were included (Table 1). 10.1371/journal.pmed.1001778.t001 Table 1 Characteristics of studies included in the individual participant data meta-analysis. Study Number and Country/Region [Reference] Study Population Primary Study Objective Study Design Participants Eligible for IPD Meta-Analysis Planned Study Duration Frequency of Follow-Up Dates of Enrollment Number of Participants Mean (SD) Age at Enrollment(Years) Median (IQR) Follow-Up (Months) Percent Followed Up at 12 mo Number of Incident HIV Infections HIV Incidence, per 100 Woman-Years (95% CI) 1. Kenya [32, 39] Women engaging in transactional sex HC and HIV Cohort All Not fixed Monthly 02/93–12/02 1,219 27.1 (6.3) 11.6 (3.5–3.3) 65.3 162 11.8 (10.1–13.8) 2. South Africa [15, 41] Women not previously screened for cervical cancer Cervical cancer screening RCT Intervention (screening) and control 6–36 mo 6 mo 06/00–12/02 4,158 40.7 (4.2) 7.5 (5.8–12.2) 42.8 68 2.1 (1.6–2.7) 3. Uganda, Zimbabwe [30, 31] Women attending RH clinics HC and HIV Cohort All 15–24 mo 3 mo 11/99–09/02 4,425 25.4 (4.5) 23.2 (17.9–24.1) 97.2 211 2.8 (2.4–3.2) 4. Kenya [33] Women engaging in transactional sex HIV prevention; presumptive antibiotic treatment (azithromycin) RCT Intervention and control 24 mo 3 mo 05/98–01/02 399 28.8 (7.6) 22.7 (10.8–27.6) 76.8 30 4.6 (3.1–6.6) 5. Tanzania [34] Women working in bars, guest houses HIV prevention; microbicide feasibility study Cohort All 12 mo 3 mo 08/02–10/03 932 29.6 (7.8) 11.8 (8.5–12.0) 62.2 23 3.0 (1.9–4.5) 6. Tanzania [16, 40] Women working in bars, guest houses HIV prevention; HSV suppression (acyclovir) RCT Intervention and control 30 mo 3 mo 11/03–01/06 769 27.5 (5.0) 27.1 (15.5–28.3) 93.8 50 3.4 (2.5–4.5) 7. Zimbabwe, South Africa [20, 36] Sexually active women HIV prevention; diaphragm and condoms RCT Intervention and control 12–24 mo 3 mo 09/03–10/05 4,074 29.0 (7.8) 18.0 (14.8–23.9) 96.9 263 4.3 (3.8–4.9) 8. South Africa [57] Women attending RH clinics HC and HIV Cohort All 12 mo 3 mo 08/99–05/01 545 27.7 (6.6) 11.6 (10.8–12.0) 63.9 23 4.7 (3.0–7.1) 9. South Africa [37] Women attending FP and postnatal clinics HIV prevention; microbicide feasibility study Cohort All 12 mo 3 mo 01/02–01/04 690 24.7 (5.80) 11.1 (10.8–11.4) 38.8 20 3.4 (2.1–5.3) 10. South Africa [38] Women attending FP clinics HIV prevention; microbicide feasibility study Cohort All 12 mo 3 mo 07/03–07/04 257 29.0 (9.2) 9.5 (6.0–12.0) 56.8 29 15.2 (10.1–21.8) 11. Malawi, Zimbabwe [35, 42] Women attending FP and postnatal clinics HIV prevention; microbicide feasibility study Cohort All 9 mo 3 mo 06/01–08/02 1,423 28.0 (7.7) 9.0 (8.8–9.2) 82.1 52 5.2 (3.8–6.8) 12. South Africa [18, 43] Sexually active women HIV prevention; vaginal microbicide (Carraguard) RCT Intervention and control 9–24 mo 3 mo 03/04–06/06 5,615 29.8 (8.9) 17.7 (9.0–23.9) 92.6 272 3.7 (3.3–4.3) 13. Uganda [49] Women engaging in transactional sex HIV prevention; microbicide feasibility study Cohort All 12 mo 3 mo 04/08–05/09 418 26.5 (5.8) 12.0 (10.6–12.5) 65.5 17 4.4 (2.6–7.1) 14. Tanzania [48] Women working in bars, guest house HIV prevention; microbicide feasibility study Cohort All 12 mo 3 mo 07/08–09/09 873 27.9 (6.8) 11.4 (11.4–11.5) 94.1 30 3.9 (2.6–5.6) 15. East/southern Africa [17, 59] Sexually active women HIV prevention; HSV suppression (acyclovir) RCT Intervention and control 24 mo 3 mo 12/04–04/09 1,268 31.0 (7.7) 17.1 (11.9–23.7) 98.2 71 4.0 (3.1–5.0) 16. East/southern Africa [19, 44] Sexually active women HIV prevention; vaginal microbicide (PRO2000) RCT Intervention and control 12–24 mo Monthly 10/05–08/08 8,596 29.3 (8.4) 12.0 (11.7–12.2) 94.8 413 4.4 (3.1–6.1) 17. South Africa [5] Sexually active women HIV prevention; vaginal antiretroviral (tenofovir) RCT Control only Mean 18 mo Monthly 05/07–01/09 444 23.5 (4.9) 19.1 (13.1–22.8) 99.1 60 9.1 (6.9–11.7) 18. East/southern Africa [6] Sexually active women HIV prevention; oral antiretroviral (Truvada) RCT Control only Up to 60 wk Monthly 06/09–04/11 1,019 24.2 (4.8) 10.2 (7.0–13.8) 91.2 36 4.4 (3.1–6.1) FP, family planning; HSV, herpes simplex virus; IQR, interquartile range; RH, reproductive health; SD, standard deviation. Data Collection, Data Management, and Data Items Two investigators (C.S.M. and P.C.) contacted the investigators of eligible component studies by email or phone to ask their permission to use their study data in the meta-analysis. We collected information for the individual studies included in this analysis from protocols, questionnaires, and publications, and asked study investigators to determine whether desired variables had been collected or could be derived. We used the existing structure of the VPRP database to include the data from additional studies, which included three levels of variables: study, individual, and visit level. Study-level variables consisted of country, study site, study design and population group(s), study aims, recruitment period, study duration, frequency of follow-up visits, planned follow-up duration for each woman, definitions of primary and secondary study outcomes, and diagnostic procedures. Individual-level variables included age, education, employment status, religion, socio-economic indicators, parity, and marital status. Visit-level variables were hormonal contraceptive use, pregnancy status, vaginal practices, numbers and type of sexual partners, coital frequency, transactional sex, condom use, sexual partner risk, and HIV, HSV-2, and other diagnosed sexually transmitted or reproductive tract infections. We included individual- and visit-level items for all study participants who had follow-up HIV and HC data. We excluded data from studies with scheduled follow-up visits >6 mo apart. Three statisticians and data managers (P.C., C.K., and A. Bernholc) at the study coordinating center (FHI 360) worked closely with data managers and investigators of the individual studies to clarify issues about variable definition and missing, incomplete, or implausible data. Of the 18 included studies, datasets for 13 were provided either by their own data manager or through the VPRP. Investigators of the other five studies sent raw data to the coordinating center staff, who provided data management support. Primary Outcome and Exposure Measures The primary outcome was incident HIV infection, defined as a new HIV infection following a preceding visit where the participant was confirmed HIV negative. The criteria for HIV diagnosis were defined by the investigators of the individual studies and were typically based on a positive ELISA/rapid test confirmed by a positive Western blot or HIV PCR test. The midpoint between the last negative and first positive HIV test was used as the estimated HIV infection date. The primary exposure was hormonal contraceptive use with COCs (any preparation including estrogen plus progestin), DMPA (150 mg intramuscularly every 3 mo), or NET-EN (200 mg intramuscularly every 2 mo). COC, DMPA, and NET-EN use were recorded at each study visit. Studies that did not specify the type of injectable hormone were categorized as DMPA in the primary analysis because only South Africa had a significant number of NET-EN users. We examined in a sensitivity analysis the effect of limiting the meta-analysis to only studies where the injectable was specified. The comparison group was women not using hormonal contraceptives. This group included sterilized women, women using condoms (consistently or inconsistently), women using non-hormonal intrauterine devices or diaphragms, and women not using any modern contraceptive method. Study participants were censored at the time they reported using a hormonal method not included in the study (such as the progestin-only pill or hormonal implants), at the end of the study, or at their last follow-up visit. Assessment of Study Methods and the Risk of Bias We developed a list of methodological features of the component studies that could bias the estimates of the association between HC and HIV acquisition or affect their precision. We used criteria for items specific to the research question [3, 4, 22]. Additional criteria for cohort studies were drawn from the Newcastle-Ottawa Scale [23], the Downs and Black instrument [24], the Strengthening the Reporting of Observational Studies in Epidemiology Statement [25], and the Meta-Analysis of Observational Studies in Epidemiology checklist [26]. For each study we assessed documentation about the following items to classify the study as being at either lower or higher risk of bias: participant retention rate [3, 4, 22–27] ( 10%). Two investigators (C.S.M. and N.L.) independently evaluated each study and reached agreement about any differences through discussion. Studies for which all items were at lower risk of bias were categorized as “lower risk of bias,” and all other studies were categorized as “higher risk of bias,” for evaluating the association between HC and HIV. Statistical Analysis We used Cox proportional hazards models with time-varying covariates to examine the association in each study between time-varying exposure to each hormonal contraceptive (COC, DMPA, and NET-EN) and HIV acquisition, and expressed the comparison with no hormonal contraceptive use as hazard ratios (HRs) with 95% confidence intervals. Follow-up time was censored at the first of the following: estimated date of HIV infection, the last follow-up visit, the end of the study, or after 30 mo of follow-up (owing to sparse data). The primary analysis used a two-stage approach to IPD meta-analysis; we used the effect estimate from each individual study and combined the effect estimates using random effects meta-analysis to estimate a summary HR (with 95% CI). We used the I 2 statistic to evaluate between-study heterogeneity (ranging from 0% to 100%) in this model and considered I 2 values below 50% as indicating mild to moderate heterogeneity [12, 28]. We examined the consistency of the results from the two-stage random effects model with those from a two-stage fixed effects model and with those from one-stage Cox regression analyses in which data were combined across all studies using study as the strata [28, 29]. No missing data were imputed in analyses; follow-up visits with a missing covariate did not contribute to the multivariable analyses. All statistical analyses were conducted using SAS (version 9.3, SAS Institute, Cary, North Carolina, US). We constructed two multivariable models for each study: the primary analysis included a common set of covariates for each study (prespecified covariates were age, marital status/living with partner, condom use, and number of sex partners; region of study was added later to this group); the second model included specific covariates for each individual study that showed statistical evidence of confounding. We examined statistical evidence of confounding of the association between each hormonal contraceptive exposure and HIV infection in the individual studies. Each potential confounding factor was added to a model that included hormonal contraceptive exposure and the prespecified covariates. If addition of the variable resulted in the HR changing by ≥10% for any of the hormonal contraceptive exposures, we included the covariate in the multivariable model. Variables evaluated for confounding included region of study, recent sexual behavior (concurrent sex partners, coital frequency, transactional sex, anal sex, oral sex), vaginal practices, reproductive health factors (parity, pregnancy history and status, lactation status), physical exam variables (cervical ectopy, genital epithelial findings), presence of cervical infections (Chlamydia trachomatis, Neisseria gonorrhoeae), and presence of vaginal infections (bacterial vaginosis, Trichomonas vaginalis, vulvovaginal candidiasis). We examined statistical evidence for effect modification using likelihood ratio tests. If the p-value was 5% missing exposure data [54], follow-up visits >6 mo apart [52, 53, 55], or no longitudinal data (from visits ≤6 mo apart) on injectable contraception [5, 50]. For two studies we did not reach an agreement with the study investigators to use their datasets by our cutoff date of September 2012 [47, 58]; we could not make contact with the responsible investigator of one study despite repeated attempts [45]. Additional searches after September 2012 identified one additional published study that did not meet the inclusion criteria [60] and two conference abstracts from studies that fulfilled the inclusion criteria [61, 62] (Table 2). 10.1371/journal.pmed.1001778.g001 Fig 1 Flow diagram of studies included in individual participant data meta-analysis of hormonal contraception and HIV acquisition. 10.1371/journal.pmed.1001778.t002 Table 2 Characteristics of studies not included in the individual participant data meta-analysis. Study Number and Country/Region Short Study Name Primary Publications [Reference] Reason Not Included in IPD Meta-Analysis Study Design Number of Women with HIV/Total Number of Women Number of Women with HIV in Contraceptive Groups Comparison Group a Study Results: Adjusted Effect Measure (95% CI) unless Otherwise Specified b Studies that did not meet inclusion criteria (n = 8) 19. Rwanda Not known Bulterys et al., AIDS 1994 [55] Did not meet inclusion criteria: follow-up visits >6 mo apart Cohort 31/1,524 12 No contraception HC use: OR 1.9 (0.8–4.6) 20. Thailand Not known Ungchusak et al., JAIDS 1996 [51] Not sub-Saharan Africa Cohort 15/365 NR No contraception COC: IRR 0.22 (0.03–1.9); injectable HC: IRR 3.8 (1.0–14.4) 21. Tanzania Not known Kapiga et al., AIDS1998 [53] Did not meet inclusion criteria: follow-up visits >6 mo apart Cohort 75/2,471 7 (COC); 2 (injectable HC) No COC use; no injectable use COC: HR 1.0 (0.5–2.3); injectable HC: HR 0.3 (0.07–1.3) 22. Thailand Not known Kilmarx et al., AIDS 1998 [56] Not sub-Saharan Africa Cohort 30/340 20 (COC); 5 (DMPA) No COC use; no DMPA use COC: RR 1.8 (0.8–4.0); DMPA: unadjusted RR 1.5 (0.6–4.0) 23. Uganda Rakai Study Kiddugavu et al., AIDS 2003 [52] Did not meet inclusion criteria: follow-up visits >6 mo apart Cohort 202/5,117 12 (COC); 16 (injectable HC) No contraception, no condoms COC: IRR 1.1 (0.5–2.6); injectable HC: IRR 0.8 (0.4–1.7) 24. Benin, Ghana, Nigeria, South Africa, Uganda, India SAVVY/CS Trials Feldblum et al., Sex Transm Dis 2010 [50] Did not meet inclusion criteria: no longitudinal data on injectable contraception RCT 114/7,364 13 (COC); 15 (injectable HC) No contraception or emergency contraception only COC: unadjusted RR 1.8 (0.8–4.1); injectable HC: unadjusted RR 2.5 (1.1–5.6) 25. South Africa CAPRISA 050/051 Abdool Karim et al., Int J Epidemiol 2011 [46] Did not meet inclusion criteria: longitudinal data on injectable contraception >6 mo apart RCT 39/594 NA NA No published HC—HIV results 26. South Africa, Zambia, Zimbabwe HPTN 039 Reid et al., JAIDS 2010 [54] Did not meet inclusion criteria: >5% missing data for exposure RCT 72/1,358 NR No contraception, no condoms COC: HR 0.9 (0.5–1.8); injectable HC: HR 0.9 (0.5–1.9) Studies not included because agreement was not obtained from investigators (n = 3) 27. South Africa, west Africa, Southeast Asia COL 1492 Van Damme et al., Lancet 2002 [45] No agreement/dataset RCT 99/552 NA NA No published HC—HIV results 28. Malawi, South Africa, Zambia, Zimbabwe, US HPTN 035 Abdool Karim et al., AIDS 2011 [58];; Chirenje et al., Int’l Microbicides Conf. 2012 [61] No agreement/dataset RCT 192/2,887 NR No HC COC: HR 0.6 (0.3–1.2); injectable HC: HR 1.4 (0.9–2.0) 29. Kenya, Uganda Partners Prep Baeten et al., N Engl J Med 2012 [47] No agreement/dataset RCT 28/1,584 NA NA No published HC—HIV results Studies with results published after September 2012 (n = 2) 30. Uganda Rakai Study Lutalo et al., AIDS 2013 [60] Does not meet inclusion criteria: follow-up visits >6 mo apart; published after meta-analysis dataset closed Cohort 30/190 3 (COC); 7 (DMPA) No contraception, no condoms COC: IRR 2.7 (0.82–8.6); DMPA: IRR 1.4 (0.6–3.4) 31. South Africa, Uganda, Zimbabwe VOICE Study Noguchi et al., CROI 2014 [62] Published after meta-analysis dataset closed; no non-hormonal-contraceptive comparison RCT 207/3,141 204 NET-EN use DMPA: HR 1.4 (1.0–2.0) aComparison group, based on information reported by the authors; for study 31 there was no comparison with non-hormonal-contraceptive users, so the comparison group is women using NET-EN. b“Injectable” reported if this was the term used by the authors and the specific progestin was not mentioned; all effect sizes rounded to one decimal place. IRR, incidence rate ratio; NA, not applicable; NR, not reported; OR, odds ratio; RR, risk ratio. Description of Studies and Study Populations Overall, there were nine cohort studies [30, 32, 34, 35, 37, 38, 48, 49, 57] and nine RCTs [5, 6, 15, 16, 17, 33, 36, 43, 44] (Table 1; S1 Table). The 18 studies were conducted in nine countries. Of the 37,124 participants, 27% were from east Africa (Kenya, Uganda, Tanzania, Rwanda), 55% were from South Africa, and 18% were from other southern African countries (Zambia, Zimbabwe, Malawi, Botswana). Participants were sexually active women recruited from community settings, reproductive health or family planning clinics, or bars and other recreational facilities where high levels of HIV infection have been documented (Table 1). Most studies followed women for 12 to 24 mo with clinic visits monthly, quarterly, or every 6 mo. Retention at 12 mo ranged from 39% to 99%. Studies documented from 17 [49] to 413 [44] incident HIV infections, with infection rates ranging from 2.1 [15] to 15.2 [38] per 100 woman-years; most studies recorded incidence rates between 2.5 and 5.0 per 100 woman-years. Five of the 18 included studies were judged to be at lower risk of bias for the analysis of HC and HIV acquisition [17, 18, 20, 30, 48] (Table 3). Amongst the other 13 studies, eight had 1 sex partner, time-varying condom use. cData censored at last visit prior to first contraceptive method switch. dData censored at last visit prior to first reported condom use. eIncidence measured low versus high (based on median: 3 mo. There was no statistical evidence of an interaction between HC and a study having less than 10% of its sample in the no-HC group. Sensitivity analyses where we censored visits at the time a woman became pregnant, and an analysis where women who ever became pregnant during the study were excluded, resulted in estimates of effects for each of the contraceptive methods that were very similar to the primary study results (S2 Table). We found stronger associations between hormonal contraceptive use and HIV acquisition in east Africa than in southern Africa or South Africa for COC use (p interaction = 0.004) and DMPA use (p interaction < 0.001). Interactions between region of study and NET-EN were not meaningful because NET-EN was used primarily in South Africa (Table 4). There was increased risk associated with DMPA use for east Africa and South Africa but not for southern Africa, and an increased risk for COC use in east Africa but not in South Africa or Southern Africa. We found no statistical evidence for modification of the association between HC and HIV acquisition according to the background HIV incidence of the component studies. Prespecified sensitivity analyses using different methods for censoring person-time prior to contraceptive method switch, limiting studies to only those where the type of injectable was specified, or limiting person-time to periods with no condom use yielded results very similar to the primary study results (Table 4). In post hoc analyses, we found some evidence for stronger associations between COC (p interaction = 0.025) and DMPA (p interaction = 0.088) use and HIV acquisition in women reporting transactional sex than among women not reporting transactional sex (Table 4). We found no important differences between analyses of HC and HIV acquisition based on type of study design (RCT or cohort study) or after including the published results from the one study for which we could not obtain individual-level data [61] (S2 Table). Discussion In this large IPD meta-analysis, we found that women who use DMPA had an increased risk of HIV acquisition compared to women not using HC, after controlling for potential confounding variables. The incidence of HIV was also increased for women using NET-EN, but confidence intervals were wide, and the increase was not statistically significant after controlling for potential confounding factors. There was no increased HIV risk associated with COC use. However, the assessed risk of methodological bias of component studies modified the effect of the hormonal contraceptive methods on HIV acquisition, with lower HRs for all contraceptive methods in studies at lower risk of bias. Direct comparisons between the three contraceptives suggest that use of DMPA is associated with an increased risk of HIV acquisition compared to either COC or NET-EN use and that NET-EN use is associated with a borderline increase in HIV acquisition risk compared to women using COCs (p = 0.055). Neither age nor baseline HSV-2 infection status modified the effect of the hormonal contraceptive methods on HIV acquisition. The findings from other sensitivity analyses support the overall study findings. Our finding that oral contraceptive use is not associated with increased risk of HIV, compared with no hormonal contraceptive use, is consistent with descriptive reviews of the findings from most previous prospective studies [3, 4]. Overall, we found a 50% higher risk of HIV acquisition in women using DMPA, but the increase was reduced to 22% in studies at lower methodological risk of bias, with confidence intervals including the possibility of no increased risk. Our meta-analysis results concerning DMPA agree with the findings of an increased HIV risk in some studies [17, 31, 35, 50, 51, 63], but do not agree with the findings of other studies [15, 16, 18, 52–56]. Our meta-analysis is, to our knowledge, the largest analysis to date of the association between NET-EN and HIV acquisition. Our findings indicate no overall increased HIV risk associated with NET-EN use; in studies at lower risk of bias, the risk of HIV was even lower. This is in agreement with five prospective studies in NET-EN users [15, 18–20, 57]. Our finding of an increased risk of HIV acquisition associated with DMPA use when directly compared with NET-EN use agrees closely with a secondary analysis of data from the VOICE (Vaginal and Oral Interventions to Control the Epidemic) microbicide trial (DMPA versus NET-EN aHR 1.44, 95% CI 1.05–1.98; Table 2) [62], which ended after data collection in our study was completed. The quantitative results from this IPD meta-analysis provide several advances over previous reviews of HC and HIV [1, 3, 4]. First, we provide pooled summaries of associations between injectable progestin-only contraceptives and HIV acquisition. Second, the individual-level data allowed a consistent approach to coding and multivariable analysis [14, 64], which overcame some of the heterogeneity that precluded meta-analysis of the aggregated data [3, 4]. Third, with data from about 37,000 women and more than 1,800 incident HIV outcomes, we had sufficient statistical power to examine associations between specific contraceptives and HIV risk and to investigate effect modification in prespecified subgroup analyses. In particular, we found that methodological features of study design or conduct affected the association between hormonal contraceptive use and HIV acquisition. Assessing the risk of bias in observational studies is inherently subjective, so we tried to minimize the subjectivity of these ratings by having independent evaluations by two evaluators. We developed our own assessment tool a priori and included items from published checklists together with items related to other methodological features we believed to be important for studies of HC and HIV risk. Other evaluators have chosen different criteria [3, 4]. It is biologically plausible that DMPA might be more strongly associated with an increased risk of HIV acquisition than either NET-EN or COCs. Two particular characteristics of DMPA are worth noting. First, DMPA results in a more hypoestrogenic environment than NET-EN and estrogen-containing COCs [65, 66], and lack of estrogen has been linked to increased HIV risk through decreased integrity of the vaginal epithelium and changes to the genital immune environment [10, 67]. Second, medroxyprogesterone acetate has a higher affinity for binding with the glucocorticoid receptor than either norethindrone or levonorgestrel (progestins used in NET-EN and most COCs in this study), and activation of the glucocorticoid receptor has been linked to suppressed local immunity in several studies [68–70]. Other factors associated with hormonal contraceptive use might also increase the risk of HIV acquisition, such as changes in the genital epithelium (e.g., cervical ectopy), changes in the vaginal microbiome [71–73], changes in the genital immune environment [74–76], and direct effects on HIV (i.e., up-regulation of viral replication) [1, 10, 70, 75]. Our meta-analysis has some limitations. First, our collection of datasets might not be representative of all datasets that could be used to address the associations between HC and HIV. This problem affects reviews of observational epidemiology in general because many studies are secondary analyses of existing datasets; in other studies, the associations of interest may not have been analyzed or published. Systematic searches of electronic databases will only identify the published studies. Our search strategy identified both published studies and datasets with the relevant variables that had not yet been analyzed. The 18 datasets in our meta-analysis included the three studies specifically designed to investigate the research question [30, 32, 57], most of the studies included in a systematic review [3, 4], and ten new datasets [5, 6, 16, 19, 33–35, 37, 38, 49]. Reasons for excluding studies were independent of the study findings. Our findings did not change with the addition of the one eligible study with HC—HIV results from among the datasets we were not able to obtain [61] (S2 Table). Second, while IPD meta-analysis overcomes some of the problems associated with aggregated data, it cannot eliminate bias stemming from study design or conduct. In particular, not all component studies had comparable data on all subgroups and potential confounding variables. We worked directly with the primary investigators from all included studies to try to define variables consistently, but residual confounding could still be present in our effect estimates. Third, the studies in the meta-analysis used self-reported measures of sexual behavior, including condom use, which might not be accurate. If over-reporting of condom use is primarily in the HC groups (compared to the no-HC group), then the effect of this misreporting would likely be to overinflate the effect estimates for HC. Conversely, if over-reporting of condom use is greater in the no-HC group than in the HC groups (as we believe is more likely, given the higher self-reported condom use in the no-HC group than in the HC groups), then such over-reporting will result in an underestimate of the true effect of hormonal contraceptives on HIV acquisition. In any case, we included a sensitivity analysis where person-time was limited to those periods when women reported no condom use, and there was little change in the effect measures for any of the hormonal contraceptives. The reports of no condom use are thought to be of higher validity, as there is little social pressure to underreport condom use in these studies. Fourth, there was evidence of between-study heterogeneity in the main analyses for NET-EN and DMPA, albeit mild. The I 2 values for DMPA (I 2 = 47%) and NET-EN (I 2 = 41%) were similar, but the patterns of results differed. In the forest plot of NET-EN and HIV, there was one statistically influential study with an effect estimate in the opposite direction from the other studies (Fig. 2C, study #12). We evaluated this pattern and found that this study was not statistically an outlier [77]. Finally, marginal structural Cox survival models using stabilized inverse probability treatment weighting might have been a more appropriate approach to control time-dependent confounding than Cox proportional hazards models [3, 78, 79]. However, we could not apply this method consistently across the different studies. This IPD meta-analysis found no evidence that COC or NET-EN use increases women’s risk of HIV compared to women not using HC, and adds to the evidence that DMPA might increase the risk of HIV acquisition, although some of the excess risk attributed to injectable contraception results from methodological limitations of the studies, including poor follow-up and residual confounding. Because of the importance of effective family planning to women’s reproductive health and to the morbidity and mortality of women and children, it is critical to obtain the highest quality evidence possible to inform the decisions of women, clinicians, and policy-makers in regions or risk groups with high HIV incidence. The results of this study also provide important information to inform the design of an RCT [80, 81], which would provide more direct evidence of the effects of different hormonal contraceptive methods, in particular DMPA, on the risk of HIV acquisition. In the absence of definitive data, however, women with high HIV risk need access to additional safe and effective contraceptive options, and they need to be counseled about the relative risks and benefits of the available family planning methods. Supporting Information S1 Checklist PRISMA checklist. (DOCX) Click here for additional data file. S2 Checklist Additional checklist of items specific to individual participant data meta-analyses. (DOCX) Click here for additional data file. S1 Table Additional information about studies included in the hormonal contraception—HIV individual participant data meta-analysis. (DOCX) Click here for additional data file. S2 Table Sensitivity analyses from the hormonal contraception—HIV individual participant data meta-analysis, including analyses with studies not included in the primary meta-analysis. (DOCX) Click here for additional data file. S3 Table Data availability of component datasets for the hormonal contraception—HIV individual participant data meta-analysis. (DOCX) Click here for additional data file. S1 Text Study protocol. (DOCX) Click here for additional data file. S2 Text Statistical analysis plan. (DOCX) Click here for additional data file.
- Record: found
- Abstract: found
- Article: not found
Progesterone implants enhance SIV vaginal transmission and early virus load.
William P. Dailey, A Spira, A Gettie … (1996)
Simian immunodeficiency virus (SIV) can cross the intact vaginal epithelium to establish a systemic infection in macaques (mac). Using this SIVmac model, we found that subcutaneous progesterone implants, which could mimic hormonally based contraceptives, thinned the vaginal epithelium and enhanced SIV vaginal transmission 7.7-fold over that observed in macaques treated with placebo implants and exposed to SIV in the follicular phase of the menstrual cycle. Progesterone treatment also increased the number of SIV DNA-positive cells in the vaginal lamina propria as detected by in situ polymerase chain reaction analysis. Moreover, plasma viral RNA was elevated for the first three months in macaques with progesterone implants, and three of the progesterone-treated macaques developed relatively rapid disease courses. This study shows that SIV genital infection and disease course are enhanced by subcutaneous implants containing progesterone when compared with the rate of vaginal transmission in the follicular phase.
Author and article information
Journal
Journal ID (nlm-ta): J Fam Plann Reprod Health Care
Journal ID (iso-abbrev): J Fam Plann Reprod Health Care
Journal ID (hwp): familyplanning
Journal ID (publisher-id): jfp
Title:
The Journal of Family Planning and Reproductive Health Care
Publisher:
BMJ Publishing Group
(BMA House, Tavistock Square, London, WC1H 9JR
)
ISSN
(Print):
1471-1893
ISSN
(Electronic):
2045-2098
Publication date
(Print):
July
2017
Publication date
(Electronic):
5
April
2017
Volume: 43
Issue: 3
Pages: 175-180
Affiliations
Author notes
[Correspondence to
] Dr Theresa Lawrie, Cochrane Office, Education Centre, Royal United Hospital, Bath
BA1 3NG, UK;
tess@
123456lawrie.com
Author information
Theresa A Lawrie
http://orcid.org/0000-0002-5500-8590
Article
Publisher ID: jfprhc-2016-101607DOI: 10.1136/jfprhc-2016-101607
PMC ID: 5537534
PubMed ID: 28381443
SO-VID: 8140f756-851f-4866-92c1-7ed2451d4fb9
Copyright © Published by the BMJ Publishing Group Limited. For permission to use (where not already
granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
License:
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
History
Date
received
: 11
August
2016
Date
revision received
: 21
November
2016
Date
accepted
: 16
January
2017
Categories
Subject:
1506
Subject:
1507
Subject:
Research
Custom metadata
special-feature unlocked
special-feature editors-choice
ScienceOpen disciplines: Health & Social care
Data availability:
ScienceOpen disciplines: Health & Social care