Prediction Models for Prevalent Pulmonary Tuberculosis in Adults

Van Wyk, S.S., Lin, H.H. and Claassens, M.M., 2017. A systematic review of prediction models for prevalent pulmonary tuberculosis in adults. The International Journal of Tuberculosis and Lung Disease, 21(4), pp.405-411.

  • Many presumptive TB cases are not identified promptly, leading to diagnostic and treatment delays.
  • Studies focused on developing models using clinical predictors such as history, physical examination, and chest radiography (CXR) to estimate PTB probability; more advanced imaging technologies were excluded due to lack of availability in high TB burden settings.
  • Exclusion criteria for studies involved settings like inpatients, specific populations (e.g., TB contacts, pregnant women, drug users), to reduce heterogeneity.
  • Only six studies met these criteria, developing and validating models to improve PTB detection using additional factors like CD4 count, BMI, and duration on antiretroviral therapy (ART).
  • Addition of the tuberculin skin test (TST) to the WHO symptom screen significantly improved sensitivity for detecting PTB.
  • Development of clinical scores using various predictors to facilitate screening in routine and low-resource settings.
  • Models showed potential for improving diagnostic accuracy by incorporating additional information to WHO recommendations.
  • Highlighted the need for a low-cost, easily applicable TB risk score to enhance screening accuracy and feasibility in high TB burden, low-resource settings.
  • Current reliance on the WHO symptom screen due to the absence of better alternatives.

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