Men who have sex with men (MSM) are disproportionately affected by HIV and other sexually transmitted infections (STIs). Being diagnosed as having an STI is among the most consistent and longstanding risk factors associated with HIV acquisition.1–3 The elevated risk of HIV acquisition among MSM with bacterial STIs reflects some combination of increased susceptibility,2–12 sustained risk behaviors, and sexual network factors. The advent of preexposure prophylaxis (PrEP) has created a new impetus for identifying the populations of MSM at greatest risk for HIV infection. Preexposure prophylaxis is efficacious13 but expensive, and cost-effectiveness analyses have consistently found that it is only cost-effective when targeted to the highest-risk men.14–18 Previous studies suggest that HIV-negative MSM diagnosed as having early syphilis, rectal gonorrhea, and rectal chlamydial infection may be at particularly high risk for subsequent HIV infection.19–22 However, these studies did not estimate HIV incidence for all bacterial STIs by anatomic site or stage of infection, were limited to sexually transmitted disease (STD) clinics or study populations, did not estimate the proportion of all HIV infections among MSM occurring in men with a recent STI diagnosis, and measured only the incidence of HIV diagnosis rather than HIV infection. To identify MSM for prioritization of intensive HIV prevention interventions, including PrEP, we used matched HIV/STI surveillance data from Washington State to examine the incidence of new HIV diagnoses after STI diagnoses among MSM statewide and estimate the incidence of new infection among MSM diagnosed at an STD clinic and large community-based HIV/STI testing site. We used these findings to estimate the number of men who would need to receive PrEP to avert one HIV infection directly. Finally, based on a prior analysis among MSM in our STD clinic suggesting that substance use was associated with HIV risk even when controlling for STI diagnosis,23 we assessed whether the risk of subsequent HIV diagnosis after STI diagnoses was modified by substance use.
MATERIALS AND METHODS
We used matched HIV/STI surveillance data from Washington State from January 1, 2007, to June 30, 2013. STI surveillance and partner services data are routinely matched with HIV surveillance data from the Enhanced HIV/AIDS Reporting System (eHARS) through a 2-step process. First, an automated probabilistic matching algorithm of all persons in the STI surveillance system and all individuals in eHARS based on legal and alias names, date of birth, and sex is run weekly. Second, Washington State Department of Health staff conduct a monthly manual review of STI cases not matched to eHARS but with an indication of HIV infection in STI surveillance or partner services data.
HIV-negative MSM or MSM with unknown status diagnosed as having syphilis of known stage or urethral, rectal, or pharyngeal gonorrhea or chlamydial infection were included in this analysis (98% of reported infections). Men who reported sex with men in the last year during partner services interviews, whose provider indicated male sex partners on the case report, or who were diagnosed as having rectal gonorrhea or chlamydial infection were defined as MSM. (Medical providers in Washington State are legally required to complete a case report form for each person they diagnose as having syphilis, gonorrhea, or chlamydial infection. This form includes gender of sex partners, which was available for 79% of all bacterial STI cases in men during the study period.) To include only HIV-negative MSM and MSM with unknown status, men whose HIV diagnosis date in eHARS preceded the date of their first STI diagnosis during the study period or who were diagnosed as having HIV infection or reported a prior HIV diagnosis at the time of their first STI diagnosis during this period were excluded.
Incidence of HIV Diagnosis by STI Type. We calculated incidences of HIV diagnosis after STI diagnosis defined by pathogen and anatomic site or stage of infection (STI type) by dividing the total number of new HIV diagnoses within a given STI stratum by the total time at risk within that stratum (see later for a description of how we defined these strata). We conducted a global comparison of incidences using Cox proportional hazards regression including all STI types as a time-varying covariate. The time scale for the Cox model was calendar time. Men entered observation on the date of their first STI diagnosis during the study period and exited either on the date of HIV diagnosis from eHARS or June 30, 2013 (administrative censoring). Before the analyses, we created a hierarchy of STI types by calculating the incidence of HIV diagnosis after STI diagnosis separately for each type and ranking them in descending order as follows: rectal gonorrhea, early syphilis (primary, secondary, and early latent), rectal chlamydial infection, urethral gonorrhea, late syphilis, pharyngeal gonorrhea, urethral chlamydial infection, and pharyngeal chlamydial infection. Because interventions would be targeted based on an individual's highest-risk STI, MSM diagnosed as having concurrent infections or infections at 1 or more sites were assigned the higher-risk STI for that time point, and men with multiple infections over time could move up, but not down, the STI hierarchy. In a parallel analysis, we examined the incidence of HIV diagnosis after coinfections with the 3 highest-risk STI types by incorporating them into the hierarchy as follows: rectal gonorrhea and early syphilis, rectal chlamydial infection and early syphilis, and rectal gonorrhea and rectal chlamydial infection.
Incidence of HIV Diagnosis by Substance Use. Partner services staff elicit substance use (methamphetamine, inhaled nitrites, and erectile dysfunction [ED] drugs) in the year before STI diagnosis during interviews. We calculated the incidence of HIV diagnosis after STI diagnosis by substance use by dividing the total number of new HIV diagnoses within a given substance use stratum, by the total time at risk within that stratum. We compared incidences using Cox proportional hazards regression with substance use and STI types as time-varying covariates. The time scale for the Cox model was calendar time. Men entered observation on the date of their first STI diagnosis during the study period at which substance use was ascertained and exited on their HIV diagnosis date or June 30, 2013. Men diagnosed as having multiple STIs over time could be recategorized from nonusers to users of substances, but not from users to nonusers.
Comparison With the General Population of MSM. For comparison, we estimated the incidence of HIV diagnosis among sexually active HIV-negative MSM in Washington State during the study period. We used the number of new HIV diagnoses among MSM in eHARS as the numerator and 3.9% of men age 15 years and older from Washington State census estimates (based on US Centers for Disease Control and Prevention estimate of proportion of men who have had sex with men in the past 5 years24) minus the number of MSM known to be living with HIV from eHARS as the denominator. Because HIV risk in Washington is concentrated among MSM younger than 65 years, we also compared the incidence of HIV diagnosis after STI diagnosis among MSM aged 15 to 64 years (99.5% of STI cases; 99% of HIV diagnoses among MSM with STIs) to the incidence among sexually active HIV-negative MSM in Washington State aged 15 to 64 years (99.6% of HIV cases among MSM).
Number Needed to Treat (NNT) and Population-Level Impact. We calculated the NNT with PrEP for 1 year to prevent one HIV infection among PrEP recipients as follows: 1 ÷ (HIV incidence × PrEP effectiveness)25. To address differences in PrEP effectiveness due to adherence, we used 3 efficacy estimates from iPrEx: the overall estimate of 44% reduction in HIV acquisition, the estimate among MSM reporting at least 90% adherence of 73%, and the estimate among MSM with detectable blood levels of emtricitabine, tenofovir, or their metabolites of 92%.13
To provide an upper bound for the potential direct population-level impact of a prevention intervention targeted toward MSM diagnosed as having bacterial STIs, we calculated the proportion of HIV cases reported among MSM in the last 2 years of the study period who had been diagnosed as having an STI in the 2 years before HIV diagnosis.
The primary analysis has the potential to underestimate the true HIV incidence and overestimate NNTs because men who were not tested for HIV infection at the time of STI diagnosis may have been misclassified as uninfected, passive follow-up may fail to identify new HIV infections, and incidence of HIV diagnosis is sensitive to the lag between HIV acquisition and diagnosis. To address these limitations, we conducted an analysis among STI cases diagnosed at 2 publicly funded HIV/STI testing programs (Public Health–Seattle & King County STD Clinic and Gay City), unless partner services data indicated that cases were not HIV tested at STI diagnosis. At these sites, near-universal HIV testing at STI diagnosis reduced misclassification of persons at study entry, and frequent HIV testing should diminish the influence of passive follow-up and the lag between HIV acquisition and diagnosis. In addition, we calculated an incidence of HIV infection (rather than diagnosis) by estimating the infection date as the midpoint between the last negative and first positive HIV test results from surveillance or partner services data. Men entered observation on the date of their first STI diagnosis at these sites during the study period and exited on the date of HIV infection or June 30, 2013.
Analyses were conducted using SAS 9.3 (SAS Institutes, Cary, NC) and Stata 11.0 (Stata Corp, College Station, TX). These analyses were conducted as part of public health program activities and not considered human subjects research.
From January 2006 to June 2013, 10,080 bacterial STIs were reported among 6577 HIV-negative MSM or MSM with unknown status in Washington State at 8371 unique time points. These men were followed up for a total of 17,419 person-years (median, 2.4 years; interquartile range, 1.1–4.0 years), and 280 (4.3%) were diagnosed as having HIV infection during follow-up for an overall incidence of 1.61 diagnoses per 100 person-years (95% confidence interval [CI], 1.43–1.81), 4 times greater than the estimated incidence of diagnoses among all HIV-negative MSM statewide (0.41 per 100 person-years). Restricted to MSM aged 15 to 64 years, incidence of HIV diagnosis was 1.60 per 100 person-years among men after STI diagnoses, more than 3-fold higher than the 0.48 per 100 person-years among all HIV-negative MSM. Sociodemographic characteristics at each individual's initial reported STI during the study period and HIV testing history are presented in Table 1.
The incidence and cumulative hazard of HIV diagnosis after STI diagnosis by STI type are presented in Table 2A and Figure 1, respectively. Men who have sex with men were at the greatest risk for acquiring HIV after diagnosis with rectal gonorrhea (incidence, 4.1 per 100 person-years), followed by early syphilis (2.8), urethral gonorrhea (1.6), rectal chlamydial infection (1.6), pharyngeal gonorrhea (1.1), late syphilis (1.0), and urethral chlamydial infection (0.6; P < 0.0001 overall). Consequently, the NNT with PrEP was lowest for rectal gonorrhea and early syphilis (Table 2A; Fig. 2A). If PrEP reduces the risk of acquiring HIV by 44%, 55 and 80 MSM diagnosed as having rectal gonorrhea and early syphilis, respectively, would need to be treated with PrEP for 1 year to prevent 1 new infection among PrEP recipients. Using the highest estimate of PrEP efficacy (92% risk reduction), 26 and 38 MSM with rectal gonorrhea and early syphilis would need to be treated.
Men were concurrently diagnosed as having more than 1 bacterial pathogen at 810 time points (9.7% of 8371), including 24 early syphilis–rectal gonorrhea, 29 early syphilis–rectal chlamydia, and 251 rectal gonorrhea–rectal chlamydia coinfections. The incidences of HIV diagnosis after these coinfections were the greatest we observed: 11.8, 10.8, and 5.9 per 100 person-years, respectively.
Table 2B and Figure 2B describe the HIV incidence and NNTs from the sensitivity analysis conducted among STI cases from publicly funded testing programs and estimating the incidence of HIV infection. Overall, HIV incidence after STI diagnosis was 2.48 per 100 person-years, a 54% increase from 1.61 in the primary analysis. The absolute difference between estimated incidence of diagnosis and infection was small for gonococcal infections regardless of anatomic site and urethral chlamydial infection, but higher for early and latent syphilis and rectal chlamydial infection. Despite these differences, MSM continued to be at greatest risk for acquiring HIV after diagnosis with rectal gonorrhea (incidence, 4.4 per 100 person-years) and early syphilis (3.7).
From July 2011 to June 2013, 736 MSM were diagnosed as having HIV infection in Washington State, of whom 104 (14%) had a history of bacterial STI in the 2 years before HIV diagnosis, including 47 (6.4%) with a history of early syphilis or rectal gonorrhea (Fig. 3).
Among 3715 men (56% of total) for whom information regarding substance use was available from at least 1 STI diagnosis, 306 (8.2%) reported using methamphetamine, 632 (17%) inhaled nitrites, and 401 (11%) ED medications in the year before STI diagnosis. In bivariable analyses, men who reported using each of these substances experienced greater incidences of HIV diagnosis after STI diagnosis than did men who denied using these substances (methamphetamine, 5.09 vs. 1.65 per 100 person-years; inhaled nitrites, 4.40 vs. 1.53; ED drugs, 3.91 vs. 1.71; P < 0.001 for all). In multivariable analyses including all 3 substances and STI type, methamphetamine and inhaled nitrite use remained significantly associated with incidence of HIV diagnosis (adjusted hazard ratios, 1.92 [95% CI, 1.29–2.84] and 2.2 [1.6–3.1], respectively; P < 0.001 for both).
In Washington State, MSM diagnosed as having any bacterial STI experienced 3- to 4-fold greater incidence of HIV diagnosis after their STI than did MSM overall, with the greatest risks observed among MSM diagnosed as having rectal gonorrhea and early syphilis or reporting methamphetamine or inhaled nitrite use. However, only 1 in every 7 MSM newly diagnosed as having HIV infection had been diagnosed as having a bacterial STI in the 2 years before HIV diagnosis, and only 6.4% had a recent history of rectal gonorrhea or syphilis. These results suggest that targeting HIV prevention interventions to MSM diagnosed as having STIs, specifically rectal gonorrhea and early syphilis and methamphetamine or inhaled nitrite users, has the potential to reach very high risk men but will only directly affect a relatively small subset of MSM who will ultimately acquire HIV infection. These findings highlight the potential value of using specific STIs to target resource-intensive interventions such as PrEP, but suggest how such a highly targeted approach might have limited direct population-level impact.
This population-based study supports conclusions from previous studies in clinical and research settings that MSM with rectal infections and early syphilis are at extremely high risk for subsequently acquiring HIV, although our absolute risk estimates are lower than those previously reported.19–22 Similar to a study in New York City STD clinics,19 we observed higher HIV incidence after rectal gonorrhea than rectal chlamydia diagnosis, but HIV incidence in both groups was greater in New York City than in Washington State (7.1 vs. 4.1 per 100 person-years for rectal gonorrhea; 5.9 vs. 1.6 for rectal chlamydial infection). In iPrEx,21 which was conducted primarily in South America, MSM experienced an HIV incidence of 8.0 per 100 person-years after syphilis diagnosis, more than twice the 2.8 per 100 person-years observed among MSM in Washington State. Variations in absolute risk across studies may reflect differences in HIV incidence among MSM in these geographic areas, differences in risk in the study populations (i.e., population-based vs. STD clinic clients or study participants), or, in the case of iPrEx, greater ascertainment of infection through active follow-up.
The relationship between HIV and STI acquisition is complex and multidirectional. Some evidence suggests that genital tract inflammation caused by bacterial STIs increases the risk of HIV transmission by increasing HIV shedding by HIV-infected partners and causing breaches in the genital tract epithelium and recruitment of targets cells to this area in HIV-susceptible partners.2–12 However, these biological mechanisms require the pathogen to be present at the time of HIV exposure. Rather, our findings are likely a result of the association between different STI and subsequent behaviors and sexual network factors that result in exposure to HIV. Rectal infections are direct markers of condomless receptive anal sex, which is associated with a greater risk of HIV acquisition than oral or insertive anal sex,26–28 and because the syphilis epidemic in the United States and other developed countries is concentrated among MSM living with HIV,29 early syphilis may be a marker of condomless sex within sexual networks including high-risk MSM living with HIV. It is also possible that men at higher risk for acquiring HIV are more likely to seek STI screening in general, in clinical settings where extragenital testing is available, or are more likely to recognize or seek care in response to symptoms. Exploring the reasons that STI diagnoses predict future HIV acquisition may help identify additional targets for prevention interventions.
Preexposure prophylaxis implementation is resource-intensive, and several cost-effectiveness analyses have found that despite its potential impact on HIV incidence, providing PrEP to general populations of MSM in the United States and Australia is probably not cost-effective at current medication costs.14–17,30 Prioritizing subpopulations of MSM with higher HIV incidence, however, may be cost-effective in some situations.14–18 With that in mind, we designed our analysis to identify populations at high risk for HIV infection for PrEP prioritization and assess the potential population-level effects of such an approach. Numbers Needed to Treat can be used to compare the effectiveness of targeting interventions to subpopulations with different levels of risk, intervention adherence, and other factors. Similar to an analysis from iPrEx,31 relatively few MSM diagnosed as having syphilis would need to be treated with PrEP to prevent one new HIV infection among PrEP recipients, but the proportion of HIV infections occurring in men with a prior syphilis diagnosis was small. In iPrEx, condomless receptive anal sex with a partner of any HIV status was associated with a similar NNT but a much larger population attributable fraction, suggesting that offering PrEP to all men reporting condomless receptive anal sex would have a larger population-level impact than offering it to MSM with rectal gonorrhea or early syphilis alone at a similar cost per case directly averted. Our study does not directly address the relative benefits of targeting MSM with syphilis or rectal gonorrhea versus all MSM who engage in condomless receptive anal sex. However, in a prior analysis among MSM attending an STD clinic, we found that condomless receptive anal sex was not associated with HIV incidence when adjusting for diagnosis with a bacterial STI and methamphetamine or inhaled nitrite use in the prior year,23 suggesting that NNTs may be substantially higher in a group defined solely by condomless receptive anal sex and not stronger risk factors. Neither the iPrEx study population (primarily South American MSM) nor MSM in Washington State are likely to provide accurate estimates of HIV risk for prioritizing PrEP among MSM in other settings. Preexposure prophylaxis targeting criteria should be context-specific and may not be appropriate in settings where HIV risk in the general population of MSM is extremely high. Regardless, offering PrEP to MSM diagnosed as having higher-risk STIs may help increase the cost-effectiveness of PrEP programs.
This study has several limitations. First, without being able to measure the true date of HIV infection, the primary analysis relied on the date of the first positive test result. This approach likely led us to underestimate the true incidence of HIV infection after STI diagnosis for several reasons: the lag between HIV acquisition and diagnosis, failure to identify infections in men who did not test during follow-up, and underascertainment of infections in men who migrated out of the area. Our approach may also have misclassified HIV-infected MSM who tested HIV negative during acute infection or did not test at the time of their initial STI diagnosis, potentially leading to an overestimate of the true HIV incidence in the population. To partially address these limitations, we undertook an analysis restricted to MSM diagnosed as having STIs in large publicly funded testing programs and estimated time of HIV infection based on patients' HIV testing history. Numbers Needed to Treat were somewhat lower in this analysis, suggesting that relying on HIV diagnosis as a surrogate for HIV infection led us to overestimate NNTs in our main analysis. Some of this variation, however, may reflect differences between persons seen in an STD clinic or community-based program and the general population. In addition, many bacterial STIs in MSM are asymptomatic, and it is possible that the elevated rate of HIV diagnoses we observed overall and following specific STI types reflects a pattern of more frequent testing in men with these STIs rather than a true elevation of HIV risk. Although we cannot completely exclude this possibility, that some asymptomatic STIs (e.g., urethral chlamydial infection and pharyngeal gonorrhea) were associated with a relatively low risk of subsequent HIV acquisition argues against the idea that our findings are simply a result of ascertainment bias. Moreover, from a public health perspective, our findings clearly identify groups at high risk for HIV acquisition that could benefit from PrEP. Missing data regarding substance use may affect estimates of the association with subsequent HIV diagnosis and limited our ability to calculate the potential population-level effects of such prioritization. Furthermore, our NNTs were limited to the direct effects of PrEP on individuals taking the medications and did not take into account potential infections averted among partners and sexual networks. Last, the utility of PrEP efficacy estimates from iPrEx for calculating NNTs may be affected by differences in behavior and adherence between MSM in Washington State and the study population due to differential knowledge regarding PrEP effectiveness, access to intensive risk reduction or adherence counseling, or frequency and intensity of HIV exposures.
In conclusion, we found that MSM with rectal gonorrhea and syphilis and MSM with STIs who use methamphetamine or inhaled nitrites were at very high risk for future HIV infection. Gonorrhea and syphilis are reportable throughout the United States, and insofar as gonococcal infections are reportable with data on anatomic site of infection, the population with these infections is readily defined and could be targeted by public health agencies for specific prevention outreach, particularly promoting frequent HIV/STI testing and PrEP. At a minimum, clinicians should discuss PrEP as an HIV prevention option with MSM with rectal gonorrhea or early syphilis, or who report methamphetamine or inhaled nitrite use concurrent with any STI diagnosis.
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