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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.
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.
Background:
Diagnosis of tuberculosis should be improved in children infected with HIV to reduce mortality. We developed prediction scores to guide antituberculosis treatment decision in HIV-infected children with suspected tuberculosis.
Methods:
HIV-infected children with suspected tuberculosis enrolled in Burkina Faso, Cambodia, Cameroon, and Vietnam (ANRS 12229 PAANTHER 01 Study), underwent clinical assessment, chest radiography, Quantiferon Gold In-Tube (QFT), abdominal ultrasonography, and sample collection for microbiology, including Xpert MTB/RIF (Xpert). We developed 4 tuberculosis diagnostic models using logistic regression: (1) all predictors included, (2) QFT excluded, (3) ultrasonography excluded, and (4) QFT and ultrasonography excluded. We internally validated the models using resampling. We built a score on the basis of the model with the best area under the receiver operating characteristic curve and parsimony.
Results:
A total of 438 children were enrolled in the study; 251 (57.3%) had tuberculosis, including 55 (12.6%) with culture- or Xpert-confirmed tuberculosis. The final 4 models included Xpert, fever lasting >2 weeks, unremitting cough, hemoptysis and weight loss in the past 4 weeks, contact with a patient with smear-positive tuberculosis, tachycardia, miliary tuberculosis, alveolar opacities, and lymph nodes on the chest radiograph, together with abdominal lymph nodes on the ultrasound and QFT results. The areas under the receiver operating characteristic curves were 0.866, 0.861, 0.850, and 0.846, for models 1, 2, 3, and 4, respectively. The score developed on model 2 had a sensitivity of 88.6% and a specificity of 61.2% for a tuberculosis diagnosis.
Conclusions:
Our score had a good diagnostic performance. Used in an algorithm, it should enable prompt treatment decision in children with suspected tuberculosis and a high mortality risk, thus contributing to significant public health benefits.
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