A clinical algorithm to identify HIV patients at high risk for incident active tuberculosis: A prospective 5-year cohort study

Abstract

Background Predicting the risk of tuberculosis (TB) in people living with HIV (PLHIV) using a single test is currently not possible. We aimed to develop and validate a clinical algorithm, using baseline CD4 cell counts, HIV viral load (pVL), and interferon-gamma release assay (IGRA), to identify PLHIV who are at high risk for incident active TB in low-to-moderate TB burden settings where highly active antiretroviral therapy (HAART) is routinely provided. Materials and Methods A prospective, 5-year, cohort study of adult PLHIV was conducted from 2006 to 2012 in two hospitals in Taiwan. HAART was initiated based on contemporary guidelines (CD4 count < 350/μL or pVL ≥ 100,000/mL was a predictor of active TB (adjusted HR 4.87, 95% CI 1.49-15.90, P = 0.009). A positive baseline IGRA predicted TB in patients with baseline CD4 ≥ 350/μL and pVL < 100,000/mL (adjusted HR 6.09, 95% CI 1.52-24.40, P = 0.01). Compared with an IGRA-alone strategy, the algorithm improved the sensitivity from 37.5% to 76.5%, the negative predictive value from 98.5%to 99.2%. Compared with an untargeted strategy, the algorithm spared 468 (60.6%) from unnecessary TB preventive treatment. Area under the ROC curve was 0.692 (95% CI: 0.587-0.798) for the study cohort and 0.792 (95% CI: 0.776-0.808) and 0.766 in the 2 validation cohorts.