Number needed to screen for TB in clinical, structural or occupational risk groups

• Published in: The international journal of tuberculosis and lung disease Vol. 26; no. 6; pp. 500 - 508
• Main Authors: Naufal, F., Chaisson, L. H., Robsky, K. O., Delgado-Barroso, P., Alvarez-Manzo, H. S., Miller, C. R., Shapiro, A. E., Golub, J. E.
• Format: Journal Article
• Language: English
• Published: France International Union Against Tuberculosis and Lung Disease 01-06-2022; International Union against Tuberculosis and Lung Disease (IUATLD)
• Subjects: Active Case Finding; Adult; Diabetes mellitus; Epidemiology; Homelessness; Humans; Incidence; Mass Screening - methods; Mathematical analysis; Medical personnel; Number Needed To Screen; Population studies; Prevalence; Prisoners; Prisons; Risk; Risk Groups; Screening; Tuberculosis; Tuberculosis, Pulmonary - diagnosis; Tuberculosis, Pulmonary - epidemiology
• ISSN: 1027-3719; 1815-7920
• DOI: 10.5588/ijtld.21.0749

BACKGROUND: Screening for active TB using active case-finding (ACF) may reduce TB incidence, prevalence, and mortality; however, yield of ACF interventions varies substantially across populations. We systematically reviewed studies reporting on ACF to calculate the number needed
to screen (NNS) for groups at high risk for TB.METHODS: We conducted a literature search for studies reporting ACF for adults published between November 2010 and February 2020. We determined active TB prevalence detected through various screening strategies and calculated crude
NNS for - TB confirmed using culture or Xpert® MTB/RIF, and weighted mean NNS stratified by screening strategy, risk group, and country-level TB incidence.RESULTS: We screened 27,223 abstracts; 90 studies were included (41 in low/moderate and 49 in medium/high TB
incidence settings). High-risk groups included inpatients, outpatients, people living with diabetes (PLWD), migrants, prison inmates, persons experiencing homelessness (PEH), healthcare workers, and miners. Screening strategies included symptom-based screening, chest X-ray and Xpert testing.
NNS varied widely across and within incidence settings based on risk groups and screening methods. Screening tools with higher sensitivity (e.g., Xpert, CXR) were associated with lower NNS estimates.CONCLUSIONS: NNS for ACF strategies varies substantially between adult risk groups.
Specific interventions should be tailored based on local epidemiology and costs.