A model was sensitive but not specific for screening for tuberculosis in contact patients

Question In persons who have come into contact with others with tuberculosis (TB), can an effective screening model be validated for detecting TB? Methods Design 2 cohort studies, 1 for derivation and 1 for validation. Setting Val de Marne suburb, Paris, France. Patients 1575 contact patients (325 index cases) for derivation and 618 contact patients (88 index cases) for validation who were 3 days to 85 years of age (52% women, based on 1955 contact patients; 98% had previous bacillus Calmette-Gurin [BCG] vaccination) and lived in the same environment as a patient with pulmonary TB within 3 months before diagnosis of the index case. Exclusion criteria were history of tuberculin skin testing induration 15 mm. Description of prediction guide Logistic regression analysis of risk factors in the derivation cohort found 8 independent variables associated with TB infection: age, cavitation on chest radiograph of the index case, free health care, acid-fast bacilli (AFB) 100/field on the sputum smear of the index case, active smoking by the contact patient, household contact at night, first-degree family relationship with the index case, and birth in a country with TB incidence >25/100000 persons. Outcomes Diagnosis of TB (latent infection or overt disease). Main results 425 (27%) patients in the derivation cohort and {231 (37%)}* patients in the validation cohort were diagnosed with TB. The screening model had high sensitivity but low specificity for detecting TB infections (Table). {The areas under the receiver-operating characteristic curve were 0.759 for the derivation cohort and 0.726 for the validation cohort. }* Conclusion A model was sensitive but not specific for screening for tuberculosis infections in contacts of persons with tuberculosis. Test features of a screening model for predicting tuberculosis (TB) infection in persons who have come into contact with others with TB Cohort Sensitivity (95% CI) Specificity (CI) +LR LR Derivation (n =1575) 93% (89 to 96) 34% (30 to 38) 1.4 0.2 Validation (n =618) 94% (89 to 96) 32% (27 to 36) 1.4 0.2 LR = likelihood ratio; diagnostic terms defined in Glossary. CIs provided by author. LRs calculated from data in article. Commentary Contact tracing is an important priority for TB control programs, second only to detection and treatment of active cases. Contacts have an increased prevalence of active disease, as well as TB infection. The first step in any investigation is to identify the contacts at greatest risk for disease and infection who should be evaluated first. Such contacts are generally persons who have been exposed to the most infectious patients. Operationally, most programs define those at greatest risk for exposure as household contacts and the more infectious patients as those with pulmonary TB who are AFB-positive on direct microscopy of a sputum smear (1). Aissa and colleagues performed a methodologically rigorous study in which they derived and validated a predictive model. An important limitation of the study was the definition that tuberculin skin testing was positive only when 15 mm. This will decrease sensitivity for detection of TB infection by as much as 40% but will enhance specificity in a BCG-vaccinated population, although only if BCG vaccination was given after infancy (2). Aissa and colleagues identified known indicators of index-case contagiousness (AFB smear results, extent of radiographic disease) in addition to well-known indicators of TB infection among contacts (older age, longer duration, and closeness of contact). They also identified some more novel indicators, such as smoking status of index cases and contacts. The utility of the predictive model is unclear, but the authors have identified additional risk factors to consider when high-risk contacts are being identified. In addition, the high prevalence of active disease and latent TB infection among the contacts in the study serves as a useful reminder that contact investigation remains a high priority for TB control.