Informing selective screening through more robust estimation of STI risk

Background. Due to rising health care costs and increases in client volumes, it is imperative to develop systems that make efficient use of increasingly scarce publicly funded sexual health resources. With this in mind, an internet-based testing program that provides online access to STI testing is in development in British Columbia (BC) to improve the accessibility and limit the burden on health resources. However, much is still unknown about how to implement risk assessment and recommend tests in online settings. Prediction rules have been shown to successfully increase efficiency and cost-effectiveness of STI case finding. The aim of this dissertation was to develop and validate a risk-scoring algorithm for the selective screening of asymptomatic patients at increased risk for chlamydia and gonorrhoea infections. Methods. The risk-scoring algorithm was derived from a multivariate logistic regression of patient visits at two sexual health clinics in Vancouver between 2000 and 2006 (i.e., derivation population) and validated in a subsequent time period between 2007 and 2012 (i.e., temporal validation population). The model’s performance was evaluated using the area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow (H-L) statistic. Geographical validation was performed using seven sexual health clinics outside of Vancouver between 2000 and 2012. Results. The prevalence of infection was 1.8% (n=10,437), 2.2% (n=14,956), and 5.3% (n=10,425) in the derivation, temporal validation, and geographical validation populations, respectively. The predictors that comprised the algorithm were young age, non-white race/ethnicity, multiple sexual partners, previous chlamydia or gonorrhoea infection. The model discriminative accuracy was good in the derivation population (AUC=0.74, 95% CI: 0.70-0.77) and acceptable in the temporal (AUC=0.64, 95% CI: 0.61-0.67) and geographical (AUC=0.69, 95% CI: 0.67-0.71) validation populations. The model also demonstrated adequate calibration and screening performance in all three populations. Conclusions. The results from this research will have important implications for scaling up of Internet-based testing in BC. The algorithm could be adapted in an online setting to offer individualized testing recommendations and create educational materials to inform other Web-based content by creating awareness about STI risk factors, which may stimulate health care seeking behaviour among individuals accessing the website.

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