Lung Cancer in Patients With COPD: Predictors of Surgery and Long-Term Survival Following Lung Resection
Abstract
Background: Lung resection is the preferred treatment option for lung cancer. Patients with chronic obstructive pulmonary disease (COPD) may be denied surgery due to lung function impairment or other comorbidities. Objective: We aimed to describe the predictors of lung resection and long-term survival in patients with COPD with early-stage nonsmall cell lung cancer (NSCLC). Study Design and Methods: This is a retrospective cohort study of patients with COPD who were treated for resectable NSCLC between 2009 and 2019 in a tertiary care hospital. The decision to operate or not followed a thorough clinical evaluation. Survival status was obtained from a provincial registry. A multivariable logistic regression analysis was used to determine predictors of surgery. A propensity score technique was used to control for confounding by indication. Hazard ratios for survival were estimated from a Cox regression model, adjusted for measured baseline confounders and propensity score as covariates. Results: A total of 1307 patients with COPD were included, including 918 who underwent surgery. Of those, 147 (38%) did not have surgery and were treated with stereotactic body radiotherapy, 86 (22%) were treated with conventional radiotherapy, and 156 (40%) did not receive any active treatment. Predictors of surgery included age, forced expiratory volume in 1 second, adenocarcinoma versus squamous cell carcinoma, and stage 2A versus stage 1A. Propensity score-adjusted survival was significantly reduced with nonsurgical versus surgical approaches. Interpretation: Lung resection was associated with better survival in patients with COPD and resectable lung cancer compared to nonsurgical approaches.
Fields of Study & Subjects
Lung Cancer Diagnosis and Treatment
Lung Cancer Research Studies
Lung Cancer Treatments and Mutations
Publication details
- Journal / source
- Chronic Obstructive Pulmonary Diseases Journal of the COPD Foundation
- Volume
- 1
- Issue
- 13
- Pages
- 29–29
- Publication date
- 1 January 2026
- Language
- EN