Predicting cancer-specific mortality in patients with parotid gland carcinoma by competing risk nomogram.

BACKGROUND: The aim of the present study was to establish a competing risk nomogram to predict parotid gland cancer-specific mortality (PGC-SM). METHODS: Seven thousand nine hundred and sixty-two patients extracted from SEER database were randomly categorized into training and validation sets. The competing risk model was used to identify factors associated with PGC-SM. The nomogram was evaluated via concordance indexes (C-indexes), calibration plots, and decision curve analysis (DCA). RESULTS: Male, elderly, white, widowed, larger tumor, no surgery, advanced tumor grade, lymph node (LN) metastasis, adenocarcinoma (ADC), and higher TNM stage were associated with higher incidence of PGC-SM. Calibration plots showed that the nomogram was well calibrated. C-indexes for nomogram were 0.84 (95% CI: 0.81-0.86) and 0.84 (95% CI: 0.82-0.86) in training and validation sets, respectively. DCA demonstrated the clinical usefulness of nomogram. CONCLUSIONS: The competing risk nomogram shows high performance in predicting PGC-SM, which might enable clinicians formulate suitable treatment protocols for patients with parotid gland carcinoma (PGC).