Risk factors and clinical risk stratification of distant metastasis in early-stage lung cancer in never smokers.

BACKGROUND

Risk factors for distant metastasis in early-stage lung cancer in never smokers (LCINS) remain poorly understood. This study aimed to identify key risk factors and to develop a clinical risk stratification model for early-stage LCINS.

METHODS

We retrospectively analyzed patients diagnosed with early-stage LCINS at West China Hospital, Sichuan University, from 2015 to 2020. Univariable and multivariable Cox regression analyses were performed to identify independent risk factors for distant metastasis. A predictive model was developed and internally validated using bootstrap resampling, with performance assessed by the concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis.

RESULTS

A total of 1,406 patients with pathological stage I-II LCINS were included, among whom 76 (5.41%) developed distant metastasis during follow-up. Multivariable Cox regression analysis revealed that independent risk factors included advanced pathological T and N stages, higher consolidation-to-tumor ratio, and histologic subtype, particularly solid/micropapillary predominant adenocarcinoma. Based on these predictors, a predictive model was developed, demonstrating strong discrimination with a C-index of 0.799 and AUC values of 0.809, 0.791, and 0.783 for predicting 1-, 2-, and 3-year distant metastasis, respectively. Calibration and decision curve analyses confirmed the reliability and clinical utility of the model.

CONCLUSIONS

This study identified risk factors and developed a clinical risk stratification model for distant metastasis in early-stage LCINS. This validated model enables risk stratification and personalized monitoring to facilitate early detection of distant recurrence in LCINS.