Chang-Dong Yeo

There have been previous studies conducted to predict postoperative lung function with pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure small airway walls’ thickness, lung volume, pulmonary vessel volume, and emphysema area, which reflect the severity of respiratory diseases. These measurements are considered imaging biomarkers. This study aimed to predict postoperative lung function with imaging biomarkers. A retrospective analysis of 79 patients with lung cancer who had undergone lung surgery was completed. Postoperative lung function measured by forced expiratory volume in one second (FEV1) was defined as an outcome. Preoperative clinico-pathological parameters and imaging biomarkers representing airway walls’ thickness, severity of emphysema, total lung volume, and pulmonary vessel volume were measured quantitatively in chest CT by an automated segmentation software, AVIEW COPD. Pi1 was defined as the first percentile along the histogram of lung attenuation that represents the degree of emphysema. Wafw was defined as the airway thickness, which was calculated by the full-width at half-maximum method. Logistic and linear regressions were used to assess these variables. If the actual postoperative FEV1 was higher than the postoperative FEV1 projected by a formula, the group was considered to be preserved. Among the 79 patients, 16 of the patients were grouped as a non-preserved group, and 63 of them were grouped as a preserved group. The patients in the preserved FEV1 group had a higher vessel volume than the non-preserved group. Pi1 and Wafw were independent predictors of postoperative lung function. Imaging biomarkers can be considered significant variables in predicting postoperative lung function in patients with lung cancer.

Background Patients with locally advanced, unresectable, non‐small cell lung cancer (NSCLC) receiving definitive concurrent chemoradiation therapy (CCRT) benefit from durvalumab consolidation therapy. However, predictive factors for early relapse during durvalumab maintenance have not yet been identified. Methods The present study included the lung cancer cohort of the Catholic Medical Centers at the Catholic University of Korea from January 2018 to December 2021. A total of 51 NSCLC patients treated with durvalumab consolidation therapy after definitive CCRT were included in the analysis. Early relapse was defined as patients experiencing relapse within 6 months of starting initial durvalumab therapy. Results Among the 51 patients, 15 (29.4%) relapsed during the study period. Median time from initial therapy of durvalumab to progression was 451.00 ± 220.87 days (95% confidence interval [CI]: 18.10–883.90) in overall patients. In multivariate analysis, younger age (adjusted odds ratio [aOR], 0.792; 95% CI: 0.642–0.977; p = 0.030), higher pack‐years (aOR, 1.315; 95% CI: 1.058–1.635; p = 0.014), non‐COPD (aOR, 0.004; 95% CI: 0.000–0.828; p = 0.004) and anemia (aOR, 234.30; 95% CI: 1.212–45280.24; p = 0.042), were independent predictive factors for early relapse during durvalumab consolidation therapy. Conclusion Younger age, higher number of pack‐years, non‐COPD, and anemia were independent predictive factors for early relapse during durvalumab consolidation therapy in patients with unresectable stage III NSCLC after definitive CCRT. Careful patient selection and clinical attention are needed for high‐risk individuals.