A Clinical Algorithm to Identify HIV Patients at High Risk for Incident Active Tuberculosis: A Prospective 5-Year Cohort Study
Abstract
<div><p>Background</p><p>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.</p><p>Materials and Methods</p><p>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). 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.</p><p>Results</p><p>Seventeen 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, <i>P</i> = 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, <i>P</i> = 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.</p><p>Conclusions</p><p>A 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.</p></div- Dataset
- Dataset
- Biological Sciences
- cohort study
- study cohort
- baseline CD 4 cell count
- haart
- hr
- adult PLHIV
- baseline CD 4 cell counts
- Antiretroviral therapy
- High risk
- drug toxicity
- baseline CD 4
- 772 participants
- Identify HIV Patients
- IGRA status
- 2 validation cohorts.ConclusionsA
- Cox regression
- ci
- Clinical Algorithm
- validation cohorts
- Healthcare system
- baseline IGRA
- ROC curve
- untargeted strategy
- tb
- CD 4 count
- 5.21 years
- algorithm