Background Prediction of Chlamydia trachomatis (Ct) infection is important to identify subjects at high risk. We aimed to develop Ct prediction rules with different levels of detail in information, i.e. with readily available registries only and with additional detailed questionnaires.

Methods In the Chlamydia Screening Implementation (CSI) study all inhabitants of Rotterdam and Amsterdam aged 16–29 were invited yearly from 2008 until 2011 for home based urine testing. This resulted in 80,385 unique participants of whom 3,440 were infected. In addition to registry data (gender, age, ethnicity, neighbourhood level socioeconomic status [SES]) participants were asked to fill in a questionnaire on education, STI history, symptoms, partner information and sexual behaviour. We developed prediction rules based on registry risk factors only and with additional questionnaire risk factors by multilevel logistic regression to account for clustering within neighbourhoods. We assessed the discriminative ability by the area under the receiver operating characteristic curve (AUC). The models were internally validated with a bootstrap procedure.

Results Strong registry based predictors for Ct infection were young age (especially for women) and either Surinamese, Antillean or Sub-Sahara-African ethnicity. SES was of minor importance especially when questionnaire predictors were added. From the questionnaire, low to intermediate education level, ethnicity of the partner (non-Dutch) and having sex with casual partners showed strong associations with Ct infection. The AUC at internal validation was 0.67 based on registry risk factors only and 0.75 when questionnaire risk factors were added. To find 80% of the Chlamydia infections approximately 50% of the population needed to be screened when using the prediction rule including questionnaire risk factors.

Conclusion The registry based prediction rule can potentially facilitate selective Ct screening at population level, with further refinement at the individual level by including questionnaire risk factors.