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Predicting tuberculosis treatment outcome in a low-incidence area
I Baussano1, E Pivetta, L Vizzini
1Division of Epidemiology, Public Health and Primary Care, Imperial College, London, UK. i.baussano06@imperial.ac.uk
Setting:
Based on the cohort of pulmonary tuberculosis (PTB) cases resident between 2001 and 2005 in the Piedmont region of Italy, this study estimated the effect of selected determinants on the success of standardised short-course chemotherapy (SSCC).
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.
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