A prediction rule for selective screening of Chlamydia trachomatis infection

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Abstract
Background: Screening for Chlamydia trachomatis infections is aimed at the reduction of these infections and subsequent complications. Selective screening may increase the cost effectiveness of a screening programme. Few population based systematic screening programmes have been carried out and attempts to validate selective screening criteria have shown poor performance. This study describes the development of a prediction rule for estimating the risk of chlamydial infection as a basis for selective screening. Methods: A population based chlamydia screening study was performed in the Netherlands by inviting 21 000 15–29 year old women and men in urban and rural areas for home based urine testing. Multivariable logistic regression was used to identify risk factors for chlamydial infection among 6303 sexually active participants, and the discriminative ability was measured by the area under the receiver operating characteristic curve (AUC). Internal validity was assessed with bootstrap resampling techniques. Results: The prevalence of C trachomatis (CT) infection was 2.6% (95% CI 2.2 to 3.2) in women and 2.0% (95% CI 1.4 to 2.7) in men. Chlamydial infection was associated with high level of urbanisation, young age, Surinam/Antillian ethnicity, low/intermediate education, multiple lifetime partners, a new contact in the previous two months, no condom use at last sexual contact, and complaints of (post)coital bleeding in women and frequent urination in men. A prediction model with these risk factors showed adequate discriminative ability at internal validation (AUC 0.78). Conclusion: The prediction rule has the potential to guide individuals in their choice of participation when offered chlamydia screening and is a promising tool for selective CT screening at population level.