A new treatment-decision score for the diagnosis of tuberculosis (TB) in children with HIV performed well, and when used in an algorithm may facilitate prompt treatment decision making for children at a high risk for mortality, according to data published in Pediatrics.
Clinical assessments, chest radiography, Quantiferon Gold In-Tube (QFT), abdominal ultrasonography, and sample collections for microbiology, including Xpert MTB/RIF (Xpert) were performed on 438 children with HIV who were suspected to have TB in Burkina Faso, Cambodia, Cameroon, and Vietnam. Using logistic regression 4 TB diagnostic models were developed: (1) all predictors included, (2) QFT excluded, (3) ultrasonography excluded, and (4) QFT and ultrasonography excluded. These models were internally validated using resampling and scores built on the basis of the model with the best area under the receiver operating characteristic curve and parsimony.
Of the 438 children enrolled, 57.3% had TB, including 12.6% with culture- or Xpert-confirmed diagnosis. The 4 models included the following characteristics, which were noted to improve model prediction: Xpert positivity, fever lasting >2 weeks, unremitting cough, hemoptysis and weight loss in the prior 4 weeks, contact with a patient with smear-positive TB, tachycardia, miliary TB, alveolar opacities, and lymph nodes on chest radiograph, together with abdominal lymph nodes on the ultrasound and QFT results. For models 1, 2, 3, and 4 the areas under the receiver operating characteristic curves were 0.866, 0.861, 0.850, and 0.846, respectively.
The score developed using model 2, demonstrated a sensitivity >90% in the case-control population. Results also demonstrated that model 2 had a diagnostic sensitivity of 88.6% and a diagnostic specificity of 61.2%; it also had a positive predictive value of 77.4%, and negative predictive value of 78.1%. Further, when applied to the overall cohort, the score accurately identified 85.7% of children with TB if missing data was assumed negative; this increased to 90.8% when missing data was assumed positive.
Overestimation of the models’ diagnostic performance is a possibility due to incorporation bias resulting from the lack of a reference standard for childhood TB, independent of candidate predictors. A second limitation to the study is missing data for the predictors in almost one-quarter of the enrolled children, mostly younger children with severe clinical status. Finally, the study eligibility criteria differed from World Health Organization (WHO) criteria for investigation of TB; therefore this score is not directly applicable to children presenting with the WHO criteria.
The study is strengthened by using data from 4 different countries, which increases generalizability. Further, internal validation demonstrated that the models would provide good predictions. Investigators concluded that the high sensitivity and algorithmic approach of the score should, “enable rapid treatment decision in children with presumptive tuberculosis.” Researchers cautioned that further external validation is required to validate the scoring system and overall approach before its clinical usefulness can be fully confirmed.
Marcy O, Borand L, Ung V, et al. A treatment-decision score for HIV-infected children with suspected tuberculosis. Pediatrics. 2019;144:e20182065.