Development and validation of a Risk Score for Predicting Non-Adherence to Antiretroviral Therapy.

Several patient-related factors that influence adherence to antiretroviral therapy (ART) have been described. However, studies that propose a practical and simple tool to predict non-adherence after ART initiation are still scarce. In this study, we develop and validate a score to predict the risk of non-adherence in people starting ART. The model/score was developed and validated using a cohort of people living with HIV (PLHIV) starting ART at the Hospital del Mar, Barcelona, between 2012-2015 (derivation cohort) and between 2016-2018 (validation cohort), respectively. Adherence was evaluated bimonthly by both pharmacy refills and patient self-reports. Non-adherence was defined as taking <90% of the prescribed dose and/or ART interruption for more than one week. Predictive factors of non-adherence were identified by logistic regression. Beta-coefficients were used to develop a predictive score. Optimal cut-offs were identified via bootstrapping methodology and performance was evaluated through C statistic. Our study is based on 574 patients: 349 in the derivation cohort and 225 in the validation cohort. A total of 104 patients (29.8%) of the derivation cohort were non-adherent. Non-adherence predictors were patient prejudgment; previous medical appointment failures; cultural and/or idiomatic barriers; heavy alcohol use; substance abuse; unstable housing and severe mental illness. Cut-off point (ROC curve) for non-adherence: 26.3(sensitivity 0.87; specificity 0.86). C statistic (95% confidence interval): 0.91(0.87-0.94). These results were consistent with those predicted by the score in the validation cohort. This easy-to-use highly sensitive and specific tool could be easily used to identify patients at highest risk for non-adherence thus allowing resource-optimization and achieving optimal treatment goals.