Predicting tuberculosis treatment outcome in a low-incidence area
OBJECTIVE: To identify predictors of unsuccessful treatment of PTB and to generate a nomogram to assist treating physicians and public health authorities with the identification of cases needing close follow-up.
RESULTS: Overall, 1564 cases were identified. Among new cases, predictors of successful treatment outcome were sex (women vs. men, aOR 0.48, 95%CI 0.37–0.63), geographic origin (EU vs. non-EU countries, aOR 0.43, 95%CI 0.31–0.60) and treatment setting (out-patient vs. in-patient services and unknown setting, aOR 0.2, 95%CI 0.16–0.26). Predictors of unsuccessful outcome were long-term residency status (homeless vs. residential, aOR 9.91, 95%CI 4.38–22.38) and age (for each year, aOR 1.02, 95%CI 1.01–1.03).
CONCLUSION: Using a limited number of predictors, the authors designed a nomogram predicting the individual probability of unfavourable SSCC. In principle, this approach is generalisable to other settings and the nomogram can be calibrated on local data to ensure appropriate case management and support targeted treatment follow-up.
Document Type: Regular Paper
Affiliations: 1: Division of Epidemiology, Public Health and Primary Care, Imperial College, London, UK; Cancer Epidemiology Unit, CPO Piemonte and Amedeo Avogadro University, Novara, Italy 2: Cancer Epidemiology Unit, CPO Piemonte and University of Turin, Turin, Italy 3: CPA ASL 4, Regional Reference Centre for Tuberculosis Prevention, Turin, Italy
Publication date: 2008-12-01
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