Establishment of prognostic nomogram for high-grade parotid gland mucoepidermoid carcinoma based on the SEER database

Abstract

Purpose: We aim to investigate the clinical factors that affect the prognosis of overall survival (OS) for patients with high-grade parotid gland mucoepidermoid carcinoma (high-grade pMEC) and construct a nomogram for prognosis prediction. Subjects and method: Totally, 519 patients diagnosed as high-grade pMEC from the surveillance, epidemiology, and end results (SEER) database between 2004 and 2015 were reviewed. Independent prognostic factors for OS were identified by univariate and multivariate Cox regression analyses. Nomogram was generated to predict the individual’s 3- and 5- year OS rates by using R software. Prediction ability was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) and model calibration was evaluated through calibration plots. Decision curve analysis (DCA) was used to assess the clinical usefulness and net benefit. Results: The results of univariate analysis demonstrated that age, AJCC stage, T stage, N stage, M stage, extraparenchymal lesions, regional lymph nodes status, lymph node dissection status, radiotherapy, chemotherapy, and surgery were significantly correlated with the OS (P < 0.05). Multivariate Cox regression analyses showed that older age at diagnosis, advanced AJCC stage, and positive regional lymph nodes were independent risk factors for OS. In addition, the present study revealed that radiotherapy and surgery were independent protective factors for OS (P < 0.05). The nomograms showed accurate prognostic ability that individually predict 3-years and 5-years overall survival (OS) rates based on age, AJCC stage, regional lymph nodes status, radiotherapy, and surgery. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram used to predict the 3-year and 5-year overall survival rate were 0.779 and 0.793, indicating that the model had a good predictive power for the overall survival in high-grade pMEC patient. Conclusions: Using the SEER database, we performed univariate and multivariate analyses to determine independent prognostic factors in high-grade pMEC patients. Subsequently, we constructed and validated a prognostic nomogram to predict 3-and 5-year OS rates based on the SEER database and can assist clinicians to intuitively evaluate prognosis of high-grade pMEC patients.