Background: Tuberculosis-related pulmonary changes may overlap radiologically and clinically with lung cancer, complicating diagnostic interpretation, staging, and therapeutic planning. This study evaluated the relationship between tuberculosis status, thoracic imaging patterns, and clinical characteristics in patients diagnosed with lung cancer. Methods: A retrospective cohort study was conducted between February 2020 and December 2025 at the Clinical Pneumophtisiology Hospital, Constanța, Romania. A total of 620 patients with lung cancer were analyzed. Patients were classified into three groups: no tuberculosis, post-tuberculosis sequelae, and active tuberculosis. Demographic, clinical, laboratory, histopathological, functional, and radiological variables were assessed. Associations between tuberculosis status and imaging findings were evaluated using chi-square testing, effect-size analysis, and multinomial logistic regression. Results: Post-tuberculosis sequelae were identified in 337 patients (54.4%), active tuberculosis in 51 patients (8.2%), and no tuberculosis-related disease in 232 patients (37.4%). Adenocarcinoma was the most frequent histological type, occurring in 359 patients (57.9%). Significant associations with tuberculosis status were observed for fibrotic/interstitial or bronchial changes, infectious-inflammatory changes, cavitary/destructive lesions, atelectatic/retractile changes, pulmonary opacities, pleural involvement, and mediastinal/hilar adenopathy. The strongest effects were found for fibrotic/interstitial changes, infectious-inflammatory changes, and cavitary/destructive lesions. In regression analysis, active tuberculosis was most strongly associated with infectious-inflammatory changes, cavitary lesions, pulmonary opacities, and fibrotic abnormalities, while post-tuberculosis sequelae were mainly associated with chronic fibrotic and structural pulmonary changes. Conclusions: Tuberculosis-related abnormalities frequently coexist with lung cancer and may mimic or obscure malignant findings. Recognition of these overlapping patterns is essential for accurate radiological interpretation and individualized clinical management.
Cioti et al. (Mon,) studied this question.