The development of an online risk calculator for the prediction of future syphilis among a high-risk cohort of men who have sex with men and transgender women in Lima, Peru

Computational methods applied to syphilis: where are we, and where are we going?

Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions.

Incidence and Risk Factors for Early Syphilis Among Men Who Have Sex With Men in Australia, 2013-2019: A Retrospective Cohort Study

Background

We aimed to examine the incidence of syphilis in men who have sex with men (MSM) and identify subgroups of MSM at a higher risk of syphilis infection.

Methods

We conducted a retrospective cohort study of MSM attending a sexual health clinic in Australia, during 2013-2019, who had at least 2 syphilis serological tests during the study period. The incidence of syphilis was expressed as per 100 person-years. A cox regression analysis was conducted to identify risk factors for syphilis.

Results

A total of 24 391 individual MSM (75 086 consultations) were included. A total of 1404 new syphilis cases were diagnosed with an incidence of 3.7/100 person-years (95% confidence interval, 3.5-3.9). Syphilis incidence was higher in MSM with human immunodeficiency virus ([HIV] 9.3/100 person-years) than in MSM taking HIV pre-exposure prophylaxis (PrEP) (6.9/100 person-years) or HIV-negative MSM not taking PrEP (2.2/100 person-years). Risk factors associated with high incidence of syphilis included the following: MSM with HIV (adjusted hazard ratio [aHR] 2.7), MSM taking HIV PrEP (aHR 2.1), past history of syphilis infection (aHR 2.4), injecting drug use (aHR 2.7), condomless anal sex (aHR 1.7), >4 sexual partners in the last 12 months (aHR 1.2), and concurrent sexually transmitted infection (chlamydia and gonorrhoea) (aHR 1.6).

Conclusions

The incidence of syphilis remains high among MSM, particularly in subgroups with associated risk factors for syphilis infections. These data highlight the need for biomedical and behavioral interventions to be targeted to subgroups of MSM at the highest risk of syphilis infection.

Risk Prediction Score for Screening Asymptomatic Sexually Transmitted Infections in HIV-positive French Men Who Have Sex with Men (ANRS 9520 DRIVER)

OBJECTIVES

Asymptomatic sexually transmitted infections (STI) are frequent among men who have sex with men (MSM). Identifying asymptomatic STIs is a crucial issue, not only for secondary but also for primary prevention, as early treatment can reduce transmission risk. We aimed to develop a self-reported predictive score for early identification of asymptomatic STIs.

METHODS

Participants provided clinical data and completed a self-administered questionnaire including sociodemographic variables and behaviors during the 6 previous months. We used multivariable logistic regression to identify factors associated with asymptomatic STIs. We calculated the accuracy of the model by the non-parametric area (AUC) under the receiver-operating-characteristic (ROC) curve to find the optimal discriminant threshold for screening.

RESULTS

A total of 781 HIV-positive MSM were included with a mean age of 46.8 years. Asymptomatic STI prevalence was 13.2%. Detectable plasma HIV RNA (adjusted odds ratio (aOR [95% CI): 2.54 [1.23;5.25]), inconsistent condom use during anal sex (2.20 [1.36;3.56]), group sex (2.00 [1.15;3.45]), during or-genital practices (1.83 [1.12;3.01]), not being in stable relationship (1.70 [1.01;2.66] and an item from a sensation-seeking behavioral scale "I don't like watching porn videos" (1.61 [1.01;2.59] were associated with asymptomatic STI. AUC was 0.7 and with optimal threshold of 0.1082 for this model; sensitivity was 80.4%. Self-reported asymptomatic STI predictive score was built with this threshold according to the 6 factors in the final model.

CONCLUSIONS

As this predictive score is not designed to be diagnostic, but to provide indications for diagnostic tests, its ease of administration and sensitivity remain the most important features. Its use in clinical practice for early detection of asymptomatic STIs potentially can reinforce STI primary and secondary prevention.

Screening for Syphilis Infection in Nonpregnant Adolescents and Adults: US Preventive Services Task Force Reaffirmation Recommendation Statement

IMPORTANCE

Syphilis is a sexually transmitted infection that can progress through different stages (primary, secondary, latent, and tertiary) and cause serious health problems if left untreated. Reported cases of primary and secondary syphilis in the US increased from a record low of 2.1 cases per 100 000 population in 2000 and 2001 to 11.9 cases per 100 000 population in 2019. Men account for the majority of cases (83% of primary and secondary syphilis cases in 2019), and rates among women nearly tripled from 2015 to 2019.

OBJECTIVE

To reaffirm its 2016 recommendation, the US Preventive Services Task Force (USPSTF) commissioned a reaffirmation evidence update focusing on targeted key questions evaluating the performance of risk assessment tools and the benefits and harms of screening for syphilis in nonpregnant adolescents and adults.

POPULATION

Asymptomatic, nonpregnant adolescents and adults who have ever been sexually active and are at increased risk for syphilis infection.

EVIDENCE ASSESSMENT

Using a reaffirmation process, the USPSTF concludes with high certainty that there is a substantial net benefit of screening for syphilis infection in nonpregnant persons who are at increased risk for infection.

RECOMMENDATION

The USPSTF recommends screening for syphilis infection in persons who are at increased risk for infection. (A recommendation).

Screening for Syphilis Infection in Nonpregnant Adults and Adolescents: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

This systematic review to support the 2022 US Preventive Services Task Force Recommendation Statement on screening for syphilis infection summarizes published evidence on the benefits and harms of screening for syphilis infection in asymptomatic, nonpregnant adults and adolescents at increased risk for syphilis infection.

Validation of a Clinical Prediction Rule to Predict Asymptomatic Chlamydia and Gonorrhea Infections Among Internet-Based Testers

BACKGROUND

Clinical prediction rules (CPRs) can be used in sexually transmitted infection (STI) testing environments to prioritize individuals at the highest risk of infection and optimize resource allocation. We previously derived a CPR to predict asymptomatic chlamydia and/or gonorrhea (CT/NG) infection among women and heterosexual men at in-person STI clinics based on 5 predictors. Population differences between clinic-based and Internet-based testers may limit the tool's application across settings. The primary objective of this study was to assess the validity, sensitivity, and overall performance of this CPR within an Internet-based testing environment (GetCheckedOnline.com).

METHODS

We analyzed GetCheckedOnline online risk assessment and laboratory data from October 2015 to June 2019. We compared the STI clinic population used for CPR derivation (data previously published) and the GetCheckedOnline validation population using χ2 tests. Calibration and discrimination were assessed using the Hosmer-Lemeshow goodness-of-fit test and the area under the receiver operating curve, respectively. Sensitivity and the fraction of total screening tests offered were quantified for CPR-predicted risk scores.

RESULTS

Asymptomatic CT/NG infection prevalence in the GetCheckedOnline population (n = 5478) was higher than in the STI clinic population (n = 10,437; 2.4% vs. 1.8%, P = 0.007). When applied to GetCheckedOnline, the CPR had reasonable calibration (Hosmer-Lemeshow, P = 0.90) and discrimination (area under the receiver operating characteristic, 0.64). By screening only individuals with total risk scores ≥4, we would detect 97% of infections and reduce screening by 14%.

CONCLUSIONS

The application of an existing CPR to detect asymptomatic CT/NG infection is valid within an Internet-based STI testing environment. Clinical prediction rules applied online can reduce unnecessary STI testing and optimize resource allocation within publicly funded health systems.

"Mini Dial-A-Nurses" and "Good Brands": What Are the Desirable Features of Online HIV/STI Risk Calculators?

A wide variety of risk calculators estimate individuals' risk for HIV/sexually transmitted infections (STI) online. These tools can help target HIV/STI screening and optimize clinical decision-making. Yet, little evidence exists on suitable features for these tools to be acceptable to end-users. We investigated the desirable characteristics of risk calculators among STI clinic clients and testing service providers. Participants interacted with online HIV/STI risk calculators featuring varied target audiences, completion lengths, and message outputs. Thematic analysis of focus groups identified six qualities that would make risk calculators more appealing for online client use: providing personalized risk assessments based on users' specific sexual behaviors and HIV/STI-related concerns; incorporating nuanced risk assessment and tailored educational information; supplying quantifiable risk estimates; using non-stigmatizing and inclusive framing; including explanations and next steps; and developing effective and appropriate branding. Incorporating these features in the design of online HIV/STI risk calculators may improve their acceptability among end-users.

Predicting the diagnosis of HIV and sexually transmitted infections among men who have sex with men using machine learning approaches

OBJECTIVES

We aimed to develop machine learning models and evaluate their performance in predicting HIV and sexually transmitted infections (STIs) diagnosis based on a cohort of Australian men who have sex with men (MSM).

METHODS

We collected clinical records of 21,273 Australian MSM during 2011-2017. We compared accuracies for predicting HIV and STIs (syphilis, gonorrhoea, chlamydia) diagnosis using four machine learning approaches against a multivariable logistic regression (MLR) model.

RESULTS

Machine learning approaches consistently outperformed MLR. Gradient boosting machine (GBM) achieved the highest area under the receiver operator characteristic curve for HIV (76.3%) and STIs (syphilis, 85.8%; gonorrhoea, 75.5%; chlamydia, 68.0%), followed by extreme gradient boosting (71.1%, 82.2%, 70.3%, 66.4%), random forest (72.0%, 81.9%, 67.2%, 64.3%), deep learning (75.8%, 81.0%, 67.5%, 65.4%) and MLR (69.8%, 80.1%, 67.2%, 63.2%). GBM models demonstrated the ten greatest predictors collectively explained 62.7-73.6% of variations in predicting HIV/STIs. STIs symptoms, past syphilis infection, age, time living in Australia, frequency of condom use with casual male sexual partners during receptive anal sex and the number of casual male sexual partners in the past 12 months were most commonly identified predictors.

CONCLUSIONS

Machine learning approaches are advantageous over multivariable logistic regression models in predicting HIV/STIs diagnosis.

Latent classes of sexual risk and corresponding STI and HIV positivity among MSM attending centres for sexual health in the Netherlands

OBJECTIVES

Continuing high STI positivity among men who have sex with men (MSM) attending centres for sexual health (CSH) indicates that high-risk behaviour is ongoing. The objective of this study was to gain a better insight into risk behaviours among MSM attending CSH and to explore STI and HIV positivity by subgroups.

METHODS

We used national data routinely collected during CSH consultations for this study. From September to December 2017, questions on group sex, substance use and sex with HIV-positive partners were asked at each CSH consultation. We analysed latent classes of client-related factors and sexual risk behaviour among MSM attending CSH in this period. We examined STI positivity and prevalence ratios by latent classes.

RESULTS

A total of six classes were identified in order of increasing risk: 'overall low-risk behaviour' (n=2974; 22.0%), 'Western origin and multiple sex partners' (MSP) (n=4182; 30.9%), 'Non-Western origin and MSP' (n=2496; 18.5%), 'living with HIV' (n=827; 6.1%), 'group sex and HIV-positive partners' (n=1798; 13.3%) and 'group sex and chemsex' (n=1239; 9.2%). The any STI positivity ranged from 14.0% in the overall low-risk behaviour class to 35.5% in the group sex and chemsex class. HIV positivity did not differ significantly between classes. The Western origin and MSP class was largest and accounted for the majority of STI and HIV infections.

CONCLUSIONS

Although STI positivity increased with increased risky behaviours, considerable STI positivity was found in all six latent classes. Comparable HIV positivity between classes indicates risk reduction strategies among subgroups engaged in risky behaviours. The differences in risk behaviour and STI positivity require preventive strategies tailored to each subgroup.

Venue-Based HIV-Testing: An Effective Screening Strategy for High-Risk Populations in Lima, Peru

Venue-based testing may improve screening efforts for HIV and syphilis, thereby reducing transmission. We offered onsite rapid dual HIV and syphilis testing at venues popular among MSM and/or transgender women in Lima, Peru. We used Poisson regression to calculate adjusted prevalence ratios (aPRs) for factors associated with each infection. Most (90.4%) of the 303 participants would test more frequently if testing was available at alternative venues. New cases of HIV (69) and syphilis infection (84) were identified. HIV was associated with recent sex work (aPR 1.11; 95% CI 1.02-1.22), sex with a partner of unknown serostatus (aPR 1.18; 95% CI 1.09-1.27), exclusively receptive anal sex role (aPR 1.16; 95% CI 1.03-1.30) or versatile sex role (aPR 1.17; 95% CI 1.06-1.30) compared to insertive. Syphilis was associated with reporting role versatility (aPR = 2.69; 95% CI 1.52-5.74). Sex work venues had higher syphilis prevalence 47% versus 28% in other venues, p value = 0.012. Venue-based testing may improve case finding.