Introduction
Sexually transmitted infections (STI), especially those causing genital ulcer disease, are associated with increased sexual transmission of HIV [1–4]. Recent studies have highlighted the synergy between HIV and herpes simplex virus type 2 (HSV-2), a major cause of genital ulcers [1,5]. Several randomized controlled trials are currently underway to assess the impact of HSV-2 therapy on HIV acquisition and transmission.
The epidemiology of HSV-2 differs between women and men, with a greater probability of transmission from male-to-female than female-to-male [6] and gender-specific differences in the frequency of herpes recurrences [7]. It is, therefore, plausible that the effect of HSV-2 on HIV acquisition may also vary by gender, but there is little published evidence on this.
One previous meta-analysis[1] assessed the effect of HSV-2 infection on HIV acquisition in studies published up until April 1999. Nine longitudinal studies were identified, only one of which was among women. The summary estimate of studies among men showed a positive association between prevalent HSV-2 and HIV acquisition, while the single study among women showed a non-significant negative association [8] but was unadjusted for confounders. Two more recent reviews did not present an updated meta-analysis for either sex [5,9].
The primary objective of this study is systematically to review studies of the gender-specific effect of HSV-2 on HIV acquisition, and to carry out meta-analyses of studies in general populations and in groups at high risk of STI and HIV, adjusted for age and sexual behaviour. The review is limited to longitudinal studies in order to separate the effect of HSV-2 on HIV acquisition from any effect of HIV infection on subsequent acquisition of HSV-2. A secondary objective of the paper is to assess the effect of recently acquired (incident) HSV-2 on HIV acquisition in these populations; a limitation of this secondary objective is that the time sequence of infections is not always as clear.
Methods
Inclusion and exclusion criteria
Types of studies
Cohort and nested case–control studies that assessed the relationship between HSV-2 and HIV infection were eligible for inclusion. Studies in which the relative timing of HSV-2 and HIV infection could not be established were excluded.
Exposure and outcome measures
Studies were eligible if HIV and HSV-2 status was measured in all study participants (not just those who were symptomatic) using appropriate serological tests. Appropriate testing for HSV-2 was considered to be an enzyme-linked immunosorbent assay (ELISA) test or immunoblot test using HSV-2 type-specific glycoprotein G, or a Western blot [10,11]. Appropriate testing for HIV was an ELISA test, Western blot or particle agglutination test, confirmed with a second test.
Language
Abstracts and papers in languages other than English were included and were translated by a fluent speaker of the relevant language.
Statistical requirements
Studies providing an estimate of the relative risk (RR) for HIV infection in HSV-2 seropositive compared with seronegative persons were included. Studies were also included if such an estimate could be calculated from the data. Additionally, authors were contacted whenever it appeared that appropriate data were collected but not presented. Where two publications related to the same study, only the more informative was used.
Search strategy
The PubMED and Embase databases were searched to the first week of June 2004.
For the PubMED search, the following thesaurus terms were first combined with the Boolean operator ‘or’: ‘herpesvirus 2,’ ‘herpes genitalis epidemiology,’ and ‘herpes simplex’ (epidemiology, aetiology, prevention and control, and transmission). Four variations of text words for HSV-2 were then added to broaden the search. In order to identify studies that did not specifically mention HSV-2 in their abstracts, but rather referred to general STI, the thesaurus terms on ‘sexually transmitted diseases’ (epidemiology, aetiology, prevention and control, and transmission) were also included. Then, the search was limited to abstracts also containing information on HIV by adding thesaurus terms ‘HIV seropositivity’ or ‘HIV infections/transmission’ or the text phrase ‘HIV seroconverters’ to the previous search with the Boolean operator ‘anD'. The search also required that the abstracts either contained thesaurus terms for ‘cohort studies’, ‘case–control studies’, or ‘prospective studies’, or contained the appropriate text word for this study type. Only journal articles or letters were eligible. A similar Embase search strategy was also undertaken.
In addition, abstracts from the XIV and the XV International AIDS Conference and the 2003 International Society for Sexually Transmitted Diseases ResearchConference were searched on ‘herpes’ and ‘hsv’. Reference lists of included studies were examined for other pertinent studies. In addition, collaborating researchers were asked about any relevant unpublished data.
All identified abstracts were scanned and those clearly meeting exclusion criteria were eliminated at this point. Full-length papers were then retrieved if published or authors were contacted for more information if an abstract was not associated with a full length paper. Two reviewers (E. F. & H. W.) then applied the inclusion and exclusion criteria previously listed to the retrieved studies. Authors were contacted if further information was needed to include the study in this review.
Data extraction
Data were extracted onto standardized forms by the two reviewers. A quality assessment was also performed on each study to assess selection bias, response rates, loss to follow-up, misclassification and adjustment for confounding.
Statistical analysis
Meta-analyses were undertaken using odds ratios for nested case–control studies and rate ratios for cohort studies. Since HIV incidence rates were low in most studies, the odds ratios would approximate the risk ratio. Summary relative risks (RR) values were calculated where appropriate, using random-effects models rather than fixed-effects models [1,12,13]. Evidence for statistical heterogeneity was taken as P ≤ 0.1 [13,14] since the test for statistical heterogeneity lacked power [15].
Age and sexual behaviour were taken to be a-priori confounders of the relationship between HSV-2 seropositivity and subsequent infection with HIV. Measures of sexual behaviour were allowed to vary by study, since different measures were appropriate for different groups such as commercial sex workers or men who have sex with men (MSM). Only RR adjusted for age and at least one measure of sexual behaviour were included in the final meta-analysis.
It had been hypothesized that the effect of HSV-2 on acquisition of HIV might vary between women and men, and that within each sex there might be variation by type of study population. To explore this potential diversity, studies in males were divided into MSM and men in the general population (assumed to be largely heterosexual) since the effect of HSV-2 could vary by mode of HIV transmission. Studies in females were also divided into two groups: women at high risk, consisting of sex workers and bar workers; and women in the general population. High-risk women are more likely to have other STI besides HSV-2 that might enhance HIV acquisition.
Sex-specific Begg funnel plots were used to examine inclusion bias in the systematic review. The most comprehensively adjusted relative risk for each study was used for this investigation. Data management and statistical analyses were undertaken in STATA 8.0 (Stata Corp., College Station, Texas, USA).
A secondary objective of the systematic review was to collate available information on the incident HSV-2 (acquired during the study period) as a risk factor for HIV acquisition in studies retrieved in the review. An a-priori decision was made that results from these studies would not be included in the meta-analysis because of the unclear relative timing of the two infections, but results are presented in a separate table.
Results
Details of selected studies
After removing duplicates, 4426 abstracts were identified through the PubMED and Embase searches. Additionally, 13 abstracts were retrieved from recent international conferences. One further unpublished study and one in press study were identified by collaborating researchers.
Out of a total of 4441 studies, 4361 were excluded as not relevant. Of the 80 full-length papers retrieved or the authors contacted, as appropriate, 37 studies were identified for possible inclusion (Fig. 1). There were 19 studies that met all of the inclusion criteria (Table 1) [8,16–33]; of these 14 were already published in a peer-reviewed journal, two were in press, and three were unpublished (two of which already had abstracts published in conference proceedings). Additional information and data were received from authors of 14 of these included studies. The 18 studies that were excluded failed to meet specific inclusion criteria, had insufficient information provided by the authors or had repetition of data (see Supplementary Table S1, http://www.lshtm.ac.uk/ideu/research/freeman_hsv2.html) [16,34–50].
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Fig. 1: Flowchart of study selection for inclusion in systematic review.
Table 1: Studies included in the systematic review.
Table 1: (Continued)
Of the 19 studies included in the review (Table 1), RR values adjusted for both a-priori confounders, age and a marker of sexual behaviour (and in some cases for other factors as well) were obtained for 18. One study of MSM did not take confounding into account in the presentation of RR values and was considered unadjusted; this study was included in the review but not the meta-analysis. In total, there were 10 studies in women – 4 in the general population and 6 among high-risk women – and 14 studies in men – 9 in the general population and 5 among MSM. Fourteen studies were conducted in developing countries.
The methodological quality of included studies was assessed and can be seen in Supplementary Table S2 (http://www.lshtm.ac.uk/ideu/research/freeman_hsv2.html). Selection bias was considered, including selection of cases and controls where appropriate. Reporting of loss to follow-up was inconsistent; some retrospective studies only considered loss of data or serum rather than loss of individuals in the initial cohort. In studies that did report on this criterion, there was a broad range of loss to follow-up, ranging from a loss at first return visit of 5 to 38% in studies with active follow-up. Few studies supplied information on proportion of selected individuals agreeing to participate. A range of HIV and HSV-2 tests was used by the different studies, but in no case were potential problems thought to have influenced the association of HSV-2 and HIV; no studies were excluded on this basis.
Effect of HSV-2 seropositivity on HIV acquisition
The RR of HIV acquisition in HSV-2-seropositive compared with HSV-2-negative individuals, adjusted for age and sexual behaviour, is shown in Fig. 2. Among general population studies, the summary estimate of adjusted RR was similar for women [RR, 3.1; 95% confidence interval (CI), 1.7–5.6] and men (RR, 2.7; 95% CI, 1.9–3.9) (Table 2). There was little evidence of heterogeneity among studies of women in the general population. The studies in men all showed a positive association (RR values ranging from 1.3 to 7.5), but there was significant heterogeneity (P = 0.03). Among high-risk women, RR values ranged widely, from 0.50 to 6.3, with significant heterogeneity (P = 0.02). Hence, the summary estimates for these studies should be interpreted with caution. The effect of HSV-2 on HIV acquisition in MSM (RR, 1.7; 95% CI, 1.2–2.4) was lower than in general population males, and this difference was of borderline statistical significance (P = 0.07).
Fig. 2: Relative risk of HIV acquisition in subjects positive for herpes simplex virus type 2 (HIV-2) compared with those negative for HIV-2 in specific populations. The odds ratios are all adjusted for age and sexual behaviour. The squares and horizontal lines correspond to the relative risk and 95% confidence intervals, respectively, for each study. The area of the square reflects the weight of each study. The summary relative risks are shown by the diamonds. (a) General population females; (b) high-risk females (commercial sex workers and bar workers); (c) general population males; (d) men who have sex with men.
Table 2: Summary of random effects estimates of the relative risk of HIV acquisition in subjects positive for herpes simplex virus type 2 from meta-analyses.
Sex-specific Begg funnel plots of included studies (supplementary Fig. S1, http://www.lshtm.ac.uk/ideu/research/freeman_hsv2.html) plot the natural logarithm of the RR from each study against the logarithm of the study's standard error (a marker of study size). There is little evidence of inclusion bias (i.e., there is no evidence that smaller studies were more likely to be included if they detected large effects).
Effect of incident HSV-2 infection on HIV acquisition
Of the studies in the review, eight either presented a relative risk for incident HSV-2 as a risk factor for HIV seroconversion, or presented data allowing for its calculation. These RR values are presented in Table 3. However, with few exceptions, the majority of HSV-2 and HIV seroconversions were recorded during the same follow-up intervals, so it was impossible to determine which infection occurred first, or whether both infections occurred simultaneously. Also, in contrast to our meta-analyses, very few studies adjusted for confounders such as markers of sexual behaviour. In most [19,24,25,27,32], but not all [30,33] studies, recent HSV-2 seroconverters had a higher risk of HIV acquisition than those who had seroconverted to HSV-2 before the study began (comparing Table 3 with Table 1), but these estimates should be interpreted with caution.
Table 3: Incident herpes simplex virus type 2 seroconversion (during study period) and risk of HIV acquisition.
Discussion
This systematic literature review and meta-analysis shows for the first time that prevalent HSV-2 infection is a statistically significant risk factor for HIV acquisition in both men and women in the general population, after adjusting for confounding by age and sexual behaviour. In general populations, men and women infected with HSV-2 had approximately three times the risk of acquiring HIV. Although there was evidence of heterogeneity in the effect among men in the general population, all nine studies contributing to this male summary estimate found a positive association (RR values ranging from 1.3 to 7.5). In MSM, the effect appeared slightly lower than in general population males. This may be due to chance or it could reflect true differences owing to the different transmission route.
The relationship between prevalent HSV-2 and HIV acquisition was not consistent in studies among high-risk women, with RR values ranging from 0.5 to 6.3. This variation between studies could be due to different prevalences of other STI, which act as cofactors for HIV transmission, since these would increase the rate of HIV acquisition in HSV-2-negative individuals. Alternatively, the difference may be a result of residual confounding, if adjustment for sexual exposure to HIV was more complete in some studies than others.
In comparison with the previous meta-analysis [1], we located 16 additional longitudinal estimates of RR from 11 additional studies. In heterosexual men, the new estimate of the adjusted relative risk was slightly higher than that found from unadjusted or partially adjusted studies in the previous meta-analysis (RR, 2.2; 95% CI, 1.3–3.8 [1]). In MSM, our summary adjusted RR was slightly lower than that reported for unadjusted and partially adjusted studies previously (RR, 2.1; 95% CI, 1.3–3.4 [1]), and, unlike the previous study, did not demonstrate any evidence of statistical heterogeneity.
By limiting our meta-analysis to studies with known time sequence of HSV-2 infection and HIV infection, we tried to minimize any bias owing to HIV effects on subsequent acquisition of HSV-2. However, a time lag exists between acquisition of infection and a positive test for both infections. For HSV-2, median time to a positive test from culture-documented primary HSV-2 episodes is 21–120 days, dependent upon the type of test used [51]. The time sequence could, therefore, be misclassified in either direction. This is a particular problem for the examination of incident HSV-2 as a risk factor for HIV, where exact timings are even more difficult to establish.
Although our analysis concentrated on the effect of prevalent HSV-2, there would have been variation between studies in the proportion of individuals with recent and with more remote HSV-2 infections. Since recent HSV-2 may have a stronger effect on HIV acquisition than does more long-standing HSV-2 infection, owing to greater frequency and severity [7,52] of clinical HSV-2 episodes, studies including more recent HSV-2 infections might be expected to have higher RR values.
It was not possible to assess the effect of very recent (incident) HSV-2 infections directly. Few studies examined incident HSV-2, and most of these recorded HSV-2 and HIV seroconversions during the same follow-up interval; consequently, the sequence of infections could not be established. While these studies are consistent with the hypothesis that recent HSV-2 infection is a stronger risk factor for HIV acquisition than is prevalent HSV-2 infection, problems with the time lag, small study size, long intervals between testing dates and lack of adjustment for confounding make the evidence inconclusive.
We attempted to minimize confounding by requesting that authors adjust their estimates of relative risk by a-priori confounders of age and sexual behaviour. Only studies adjusting for at least these confounders were included in the meta-analysis of the effect of prevalent HSV-2. However, residual confounding, especially by sexual behaviour, which was controlled for in a wide variety of ways by included studies, is a major concern in a meta-analysis of observational studies. Obtaining accurate information on sexual behaviour is extremely difficult. However, in most studies the RR changed little upon adjustment for a wide range of confounders.
Studies also used a wide range of HIV and HSV-2 tests. The sensitivity and specificity vary between different tests, and between the same test used on different populations [53]. Misclassification of HSV-2 status is likely to be non-differential with respect to HIV status, leading to underestimation of the association between HSV-2 and HIV.
Publication bias is unlikely to have played an important role in our study since only 5 of the 23 RR values used were published in the form in which they appear in this analysis. Many RR values were extracted from papers or requested from authors whose papers had been published with a different purpose. In these cases, publication was probably not determined by the strength of the RR of interest to this meta-analysis. The funnel plots of ‘inclusion’ bias showed little evidence of any bias.
Controlling HSV-2 could potentially have a large impact on HIV incidence in areas of high HSV-2 prevalence. In a recent review, HSV-2 prevalence in Africa in random and population-based samples of individuals of reproductive age was found to be 29–71% in women and 5–53% in men [54]. Despite the limitations of calculating population-attributable fractions for infectious diseases based on observational studies, from this range of prevalence values and the summary RR values calculated in this meta-analysis, our results suggest that, in these general populations, potentially 38–60% of new HIV infections may be attributable to prevalent HSV-2 infection in women and 8–49% in men.
HSV-2 antiviral treatment is available and has been shown to significantly reduce HSV-2 transmission between discordant heterosexual couples [55]. The impact of this treatment on HIV incidence is not yet known [56]. Ultimately, the best way to establish causality and to understand the impact of HSV-2 interventions on HIV is to undertake HSV-2 intervention studies; several are currently underway.
Acknowledgements
We would like to thank the authors of studies included in the review, and especially researchers contributing information and further data analyses to this review (listed alphabetically by study group/institution): Scott Holmberg (Centers for Disease Control); Nicolas Nagot (Centre Muraz, Burkina Faso); Eduard Sanders, Nicole Dukers (Ethio-Netherlands AIDS Research Project); Ron Gray (Johns Hopkins University Bloomberg School of Public Health); Steven Reynolds, Mary Shepherd, Sanjay Mehendale (Johns Hopkins University–National AIDS Research Institute India Collaboration); Jim Todd (London School of Hygiene and Tropical Medicine); Gabriele Riedner, Michael Hoelscher (Mbeya Medical Research Programme); Gita Ramjee, Eleanor Gouws, Brian Williams (Medical Research Council, South Africa/UNAIDS/WHO); Willi McFarland, Tim Kellogg (San Francisco Department of Public Health); Peter Kilmarx, Sara Whitehead, Philip Mock, Khanchit Limpakarniarnarat (Thailand MOPH–US CDC Collaboration); Lawrence Kingsley (University of Pittsburgh); Rupert Kaul (University of Toronto); Ludo Lavreys, Jared Baeten, Joel Rakwar (University of Washington/University of Nairobi).
Sponsorship: E. E. Freeman was supported by a Marshall Scholarship; H. A. Weiss is funded by the UK Medical Research Council; J. R. Glynn is supported by the UK Department of Health (Public Health Career Scientist Award).
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