Imaging features and predictive factors for recurrence after lung nodule resection: A single-center retrospective study with propensity score matching

Lung nodule resection is a key treatment for malignant lung nodules, yet recurrence remains a significant challenge. Accurate prediction of recurrence risk is essential for optimizing postoperative management. This single-center, retrospective study included 1,132 patients who underwent lung nodule resection between 2022 and 2024. A total of 82 patients who developed recurrence within 1-2 years post-surgery were matched 1:1 with 82 non-recurrence patients using propensity score matching (PSM). Clinical, radiological, and pathological data were analyzed to identify predictors of recurrence. Logistic regression and Kaplan-Meier survival analysis were used to assess risk factors and recurrence-free survival (RFS). The final cohort consisted of 164 patients, with a median follow-up of 24 months. Logistic regression identified age (OR = 1.031, P = 0.003), nodule size (OR = 1.095, P = 0.012), and poor tumor differentiation (OR = 1.916, P = 0.006) as independent predictors of recurrence. The recurrence group had a median RFS of 13.4 months (95% CI: 11.2 – 15.6), significantly shorter than that of the non-recurrence group (P < 0.001). Age, nodule size, and poor tumor differentiation are significant predictors of recurrence following lung nodule resection. These findings may guide postoperative monitoring and risk stratification in lung cancer management, although further validation in larger cohorts is needed.