A Treatment-Decision Score for HIV-Infected Children With Suspected Tuberculosis

Olivier Marcy1,2, Laurence Borand3, Vibol Ung4,5

  • 1Epidemiology and Public Health Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia; olivier.marcy@u-bordeaux.fr.

Pediatrics
|August 29, 2019
PubMed

Insights

Improved tuberculosis diagnosis in HIV-infected children is crucial for reducing mortality. A new prediction score aids in timely antituberculosis treatment decisions for these vulnerable children.

Area of Science:

  • Pediatrics
  • Infectious Diseases
  • Public Health

Background:

  • Improved diagnosis of tuberculosis (TB) in children with HIV is essential to lower mortality rates.
  • Prediction scores were developed to assist in antituberculosis treatment decisions for HIV-infected children with suspected TB.

Purpose of the Study:

  • To develop and validate prediction scores for diagnosing tuberculosis in HIV-infected children.
  • To guide timely antituberculosis treatment decisions in this high-risk population.

Main Methods:

  • Four logistic regression models were developed using data from HIV-infected children with suspected TB across four countries.
  • Models varied by inclusion of Xpert MTB/RIF (Xpert), Quantiferon Gold In-Tube (QFT), and ultrasonography.
  • Internal validation was performed using resampling, and a score was derived from the best-performing, most parsimonious model.

Main Results:

  • A total of 438 children were enrolled; 57.3% had TB, with 12.6% confirmed by culture or Xpert.
  • The best model (excluding QFT and ultrasonography) achieved an area under the receiver operating characteristic curve of 0.861.
  • The derived score demonstrated a sensitivity of 88.6% and a specificity of 61.2% for TB diagnosis.

Conclusions:

  • The developed prediction score exhibits good diagnostic performance for tuberculosis in HIV-infected children.
  • Implementation within an algorithm can facilitate prompt treatment decisions, potentially reducing mortality and yielding significant public health benefits.
Abstract

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