Nomogram for predicting recurrence and metastasis of stage IA lung adenocarcinoma treated by videoassisted thoracoscopic lobectomy

This study aimed to construct a nomogram to effectively predict recurrence and metastasis in patients with stage 1A lung adenocarcinoma after video-assisted thoracoscopic surgery (VATS) lobectomy.Our study included 337 patients. The 3-year recurrence-free survival rate and the 5-year recurrence-free survival (5-RFS) rate were analyzed. Multivariate Cox proportional hazards regression was conducted to identify independent risk factors. We established a nomogram and performed Harrell's Concordance index, calibration plots, integrated discrimination improvement, and decision curve analyses to assess its discrimination and calibration.The median follow-up time was 45 months. In a multivariate analysis, tumor diameter, pathological subtype, preoperative carcinoembryonic antigen level, and preoperative CYFRA21-1 level were independent prognostic factors for RFS (P < 0.05). These risk factors were used to construct a nomogram to predict postoperative recurrence and metastasis in these patients. Internal verification was performed using the bootstrap method. The C-index was 0.946 (95% confidence interval: 0.923-0.970), indicating that the model had a good predictive performance. Using the nomogram and X-tile software, the patients were divided into two groups: the high-risk (5-RFS rate, 0.10-0.90) and low-risk groups (5-RFS rate, 0.90-0.99); the difference in the RFS rate between the groups was significant (χ2 = 86.705, P < 0.001).Our nomogram had a better predictive ability for recurrence and metastasis in patients with stage 1A lung adenocarcinoma after VATS lobectomy resection than the Tumor-Node-Metastasis staging system and other predictive models. This nomogram can help provide individualized treatment strategies and follow-up times.