A Clinical Algorithm to Identify HIV Patients at High Risk for Incident Active Tuberculosis: A Prospective 5-Year Cohort Study.

Susan Shin-Jung Lee,Ih-Jen Su,Kuan-Sheng Wu,Cheng-Len Sy,Chien-Chin Hung,Jui-Kuang Chen,Chin-Hui Yang,Hung-Chin Tsai,Hsin-Yun Sun,Hsi-Hsun Lin,Yao-Shen Chen,Chi-Tai Fang,Antonio Guilherme Pacheco

doi:10.1371/journal.pone.0135801

Abstract

BackgroundPredicting 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 MethodsA 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). Cox regression was used to identify the predictors of active TB and to construct the algorithm. The validation cohorts included 1455 HIV-infected individuals from previous published studies. Area under the receiver operating characteristic (ROC) curve was calculated.ResultsSeventeen of 772 participants developed active TB during a median follow-up period of 5.21 years. Baseline CD4 < 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.ConclusionsA validated algorithm incorporating the baseline CD4 cell count, HIV viral load, and IGRA status can be used to guide targeted TB preventive treatment in PLHIV in low-to-moderate TB burden settings where HAART is routinely provided to all PLHIV. The implementation of this algorithm will avoid unnecessary exposure of low-risk patients to drug toxicity and simultaneously, reduce the burden of universal treatment on the healthcare system.

Highlights

We aimed to develop and validate a clinical algorithm, using baseline CD4 cell counts, HIV viral load, and interferon-gamma release assay (IGRA), to identify people living with HIV (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
A validated algorithm incorporating the baseline CD4 cell count, HIV viral load, and interferon gamma releasing assay (IGRA) status can be used to guide targeted TB preventive treatment in PLHIV in low-to-moderate TB burden settings where HAART is routinely provided to all PLHIV
Tuberculosis (TB) remains the major cause of death in people living with HIV (PLHIV) worldwide [1]

Summary

Introduction

Tuberculosis (TB) remains the major cause of death in people living with HIV (PLHIV) worldwide [1]. While the use of highly active antiretroviral therapy (ART) reduces the risk of TB by 70%–90%, the incidence of TB remains two to four-fold higher than HIV-negative populations [5,6,7,8,9]. 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

Objectives

Methods

Results