Predictors of Interruptions in Antiretroviral Therapy among People Living with HIV in Nigeria: A Retrospective Cohort Study Using the Nigeria National Data Repository

Abstract

This study aimed to identify predictors of time to first interruption in treatment (IIT) and predictors of ever being interrupted in ART treatment among PLHIV in Nigeria using a national longitudinal dataset that covers all PEPFAR-funded implementing partners to inform national strategies to prevent IIT. This retrospective cohort study used data from Nigeria's National Data Repository (NDR). The NDR is a de-identified longitudinal database of over 1.9 million PLHIV who received ART in Nigeria beginning in 2004 and is owned by the Federal Ministry of Health (FMoH). The NDR contains patient-level demographics, clinic visits, laboratory, and ART prescription and refill data uploaded at least monthly. The data extracted for this study were obtained from electronic medical record systems of 2,226 public facilities offering HIV care in the country. In this study, we investigated the predictors of treatment interruption using data from the national HIV treatment program. We identified sets of predictors of first interruption in treatment using the logistic regression and these to be consistent in predicting time to first interruption including sex, non NRTI drug in ART regimen, recorded HIV viral load, recorded CD4 cell count, WHO clinical staging, functional status, last measured weight, highest education attained, occupation, marital status, year enrolled in care, pre and post surge, pre and post-COVID and residing in a state capital, Lagos, FCT (urban) versus other locations (rural). Age grouping was the only variable that was predictive only for time to first interruption but not for having a first interruption. To reduce the risk of IIT it is important to target interventions preemptively. We have highlighted the need for tailored interventions that address the unique needs of PLHIV in Nigeria. Targeted interventions focusing on those with a combination of risk factors could include education, counseling, supportive services, and monitoring and outreach.