Tuberculosis continues to be a global health problem. In 2013, nine million people contracted active TB and 1.5 million died from it, including 360,000 people living with HIV infection. The World Health Organization has set a goal to end the global TB epidemic by 2035, and treatment of latent TB infection is one of the major end TB strategies. A clinical algorithm using CD4 cell counts, HIV viral loads, and interferon-gamma release assay (IGRA) has been developed by Dr. Chi-Tai Fang of National Taiwan University to accurately stratify the risk of developing incident active TB in HIV infected persons, and clearly identify who would most benefit from isoniazid preventive treatment (IPT). This study has been published in August in PLoS ONE.
The research was conducted by a PhD student, Dr. Susan Shin-Jung Lee and her advisor, Dr. Chi-Tai Fang, associate professor at the Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
The WHO recommends universal IPT for all HIV-infected patients, however, whether such recommendations is suitable for countries with low-to-moderate TB burden settings where highly active antiretroviral therapy (HAART) is routinely provided, remains uncertain.
The present study was a five-year cohort study of HIV-infected patients that identified predictors of active TB to help construct the algorithm. The investigators found that using IGRA positivity alone for the decision to start IPT would miss the majority (65 percent) of those who develop active TB. However, starting IPT in patients with low CD4 cell counts of less than 350 cells/µL or a high HIV viral load of greater than 100,000 copies/mL, irrespective of IGRA status, will capture 52 percent of those who develop active TB. Additionally treating those without the above two factors, but presenting with a positive IGRA result, will capture a total of 76 percent of those who later develop active TB. Following this algorithm for IPT, ensures targeted treatment of HIV-infected persons at high risk of developing active TB, and will spare 61 percent of the patients from receiving unnecessary IPT. The number needed to treat (NNT) is reduced from 45 in the universal IPT strategy of W.H.O. to 23 using the current algorithm for targeted treatment. Compared with an IGRA alone strategy, the algorithm improved the sensitivity from 37.5 percent to 76.5 percent, and the negative predictive value from 98.5 to 99.2 percent. The investigators further validated their algorithm using two large, separate, HIV cohorts with 1455 patients in Taiwan from previous published studies.
The present study developed a clinical algorithm incorporating CD4 cell count, HIV viral load, and IGRA that can identify those HIV patients at high risk of incident active TB who are most likely to benefit from IPT. This algorithm can be used to guide targeted TB preventive treatment in HIV patients living at low-to-moderate TB burden settings, while avoiding unnecessary exposure of low-risk patients to drug toxicity and simultaneously reduce the burden on the health care system.