Simple-to-use nomogram for predicting the risk of syphilis among MSM in Guangdong Province: results from a serial cross-sectional study

Abstract

Background: The purpose of this study was to develop and validate a simple-to-use nomogram for the prediction of syphilis infection among men who have sex with men (MSM) in Guangdong Province. Methods: A serial cross-sectional data of 2184 MSM from 2017 to 2019 was used to develop and validate the nomogram risk assessment model. The eligible MSM were randomly assigned to the training and validation dataset. Factors included in the nomogram were determined by multivariate logistic regression analysis based on the training dataset. The receiver operating characteristic (ROC) curves was used to assess its predictive accuracy and discriminative ability. Results: A total of 2184 MSM were recruited in this study. The prevalence of syphilis was 18.1% (396/2184). Multivariate logistic analysis found that age, the main venue used to find sexual partners, condom use in the past 6 months, commercial sex in the past 6 months, infection with sexually transmitted diseases (STD) in the past year were associated with syphilis infection using the training dataset. All these factors were included in the nomogram model that was well calibrated. The C-index was 0.80 (95% CI 0.76–0.84) in the training dataset, and 0.79 (95% CI 0.75–0.84) in the validation dataset. Conclusions: A simple-to-use nomogram for predicting the risk of syphilis has been developed and validated among MSM in Guangdong Province. The proposed nomogram shows good assessment performance.