LAUSR

Background To develop nomograms for predicting recurrence risk and long-term survival in patients with parotid gland cancer (PGC). Methods A total of 301 consecutive patients with PGC who underwent surgery were enrolled and randomly divided into a training cohort (n=210) and a validation cohort (n=91). Predictive nomograms were constructed based on the independent indicators of overall survival (OS) and disease-free survival (DFS) as determined by multivariate Cox regression analysis. The discrimination and calibration of nomograms were evaluated using C-indices and calibration curves. Results Six independent predictors of OS were identified. Incorporating these factors, the nomogram showed good concordance statistics of 0.84 and 0.78 in predicting the 5-year OS in the training and validation cohorts. Five independent predictors of DFS were identified and integrated into the nomogram. The concordance statistics were 0.84 and 0.74 in predicting the 5-year DFS in the training and validation cohorts. The predictive performance of the nomograms outperformed the TNM model. Additionally, the patients were divided into two groups according to the nomogram score, and significant differences in OS and DFS were observed between the high risk and low risk groups. Finally, the role of postoperative treatments was evaluated based on the risk stratification; patients at high risk of disease recurrence showed an improvement in DFS after receiving postoperative treatments. Conclusions The nomogram showed good performance in predicting both OS and DFS in patients with PGC. It might be useful for selecting patients for postoperative treatments.