Purpose: To explore the value of integrating clinical and computed tomography (CT) features to predict multidrug-resistant pulmonary tuberculosis (MDR-PTB).
Patients and Methods: The study included 212 patients with MDR-PTB and 180 patients with drug-sensitive pulmonary tuberculosis (DS-PTB) who referred to our institute in China between January 2016 and March 2021. The clinical and CT characteristics were analyzed and compared between both groups. Multivariable logistic regression analysis was performed to identify independent factors that can be used to predict MDR-PTB. Furthermore, 115 patients admitted to another center from January 2019 to January 2022 were included as external validation cohort.
Results: For clinical characteristics, five parameters were significantly different between the two groups (all P < 0.05). With regard to CT features, nine parameters were significantly different between the two groups (all P < 0.05). Multivariable logistic regression analysis using the aforementioned differential features showed that male sex, retreated history, longer duration of previous anti-TB treatment, lower CD4⁺ T lymphocyte count, thick-walled cavity, centrilobular micronodules and tree-in-bud sign, bronchial stenosis, pleural and pericardial thickening were the most effective variations associated with MDR-PTB with an area under the curve (AUC) of 0.849 and accuracy of 78.6%. Furthermore, the external validation cohort that contains 115 patients obtained an AUC of 0.933 and accuracy of 81.7%.
Conclusion: MDR-PTB and DS-PTB have different clinical and imaging characteristics. A combined model incorporating these differential features can promptly diagnose MDR-PTB and develop subsequent therapeutic strategies.
Keywords: tuberculosis, multidrug-resistant tuberculosis, computed tomography