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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

Authors :
Jeffrey D. Klausner
Gino M Calvo
Xiaoyan Wang
Kelika A. Konda
Eddy R. Segura
Carlos F. Caceres
Silver K. Vargas
Lao-Tzu Allan-Blitz
Boris M Fazio
Source :
Sex Health
Publication Year :
2018

Abstract

Background Syphilis incidence worldwide has rebounded since 2000, particularly among men who have sex with men (MSM). A predictive model for syphilis infection may inform prevention counselling and use of chemoprophylaxis. Methods: Data from a longitudinal cohort study of MSM and transgender women meeting high-risk criteria for syphilis who were followed quarterly for 2 years were analysed. Incidence was defined as a four-fold increase in rapid plasma reagin (RPR) titres or new RPR reactivity if two prior titres were non-reactive. Generalised estimating equations were used to calculate rate ratios (RR) and develop a predictive model for 70% of the dataset, which was then validated in the remaining 30%. An online risk calculator for the prediction of future syphilis was also developed. Results: Among 361 participants, 22.0% were transgender women and 34.6% were HIV-infected at baseline. Syphilis incidence was 19.9 cases per 100-person years (95% confidence interval (CI) 16.3–24.3). HIV infection (RR 2.22; 95% CI 1.54–3.21) and history of syphilis infection (RR 2.23; 95% 1.62–3.64) were significantly associated with incident infection. The final predictive model for syphilis incidence in the next 3 months included HIV infection, history of syphilis, number of male sex partners and sex role for anal sex in the past 3 months, and had an area under the curve of 69%. The online syphilis risk calculator based on those results is available at: www.syphrisk.net. Conclusions: Using data from a longitudinal cohort study among a population at high risk for syphilis infection in Peru, we developed a predictive model and online risk calculator for future syphilis infection. The predictive model for future syphilis developed in this study has a moderate predictive accuracy and may serve as the foundation for future studies.

Details

Language :
English
Database :
OpenAIRE
Journal :
Sex Health
Accession number :
edsair.doi.dedup.....505e587c0d01109a6180b60d2d689d0e