ObjectivesEpidemiological treatment of persons who are sexual contacts to partners withNeisseria gonorrhoeae(NG) andChlamydia trachomatis(CT) often results in treatment of uninfected persons, which may increase the risk of antibiotic-resistant infections. We sought to identify the predictors of NG and/or CT infections to develop a risk score that could be used to limit epidemiological treatment to persons most likely to have these infections.MethodsWe included visits to the Public Health - Seattle & King County Sexual Health Clinic by asymptomatic cisgender men who have sex with men (MSM) aged ≥18 who presented as a sexual contact to partner(s) with CT or NG infection between 2011 and 2019. We used logistic regression to estimate the odds of CT and/or NG infections associated with demographic and clinical predictors, selecting the final set of predictors using the Akaike information criteria and obtaining score weights from model coefficients. We used a cross-validation approach to obtain average model discrimination from each of 10 models, leaving out 10% of the data, and evaluated sensitivity and specificity at various score cut-offs.ResultsThe final model for predicting NG or CT infection included seven predictors (age <35 years, HIV status, receptive oral sex in the prior 2 months, CT diagnosis, condomless receptive anal intercourse, condomless insertive anal intercourse and methamphetamine use in the prior 12 months). Model discrimination, as measured by the receiver operating curve, was 0.60 (95% CI 0.54 to 0.66). Sensitivity for detection of infection was ≥90% for scores ≥3, ≥5 and ≥7; specificity for these cut-offs was <16%. At scores ≥9, ≥12 and ≥14, specificity increased but sensitivity decreased to ≤76%.ConclusionsOur risk score did not sufficiently discriminate between asymptomatic MSM with and without NG/CT infection. Additional studies evaluating epidemiological treatment as a standard of care in diverse populations are needed to guide best practices in the management of contacts to NG/CT infection.