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Nomogram to predict the prognosis of parotid gland mucoepidermoid carcinoma: a population-based study of 1306 cases
Author(s) -
Jian Sun,
Yang Sun,
Fei Yang,
Qianrong Zhou,
Wenjuan Liu,
Yong Cheng,
Xingwen Wu,
Tinglan Chen,
Ruixue Li,
Borui Huang,
Wael Att,
Youcheng Yu,
Wei Bi
Publication year - 2019
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.7237
Subject(s) - nomogram , mucoepidermoid carcinoma , medicine , proportional hazards model , oncology , parotid gland , stage (stratigraphy) , epidemiology , t stage , population , cancer , survival analysis , carcinoma , pathology , biology , paleontology , environmental health
Background Mucoepidermoid carcinoma (MEC) is a common cancer in the oral salivary gland malignancy, which mainly occurs in the parotid gland. The aim of this study is to identify independent prognostic factors and establish a nomogram model for parotid gland mucoepidermoid carcinoma (P-MEC) patients using the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database. Method Patients with P-MEC were selected from between 2004 and 2015. The overall survival (OS) and cancer-specific survival (CSS) rates were estimated using the Kaplan-Meier method with the log-rank test. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify the independent prognostic factors. Results A total of 1,306 patients with P-MEC were enrolled. Age, grade, T stage, N stage, M stage, chemotherapy, and surgery type were independent prognostic factors for OS and CSS. A nomogram for OS was formulated based on these independent prognostic factors and validated using an internal bootstrap resampling approach, which showed that the nomogram exhibited a sufficient level of discrimination according to the C-index (0.877, 95% CI [0.855–0.898]). Conclusion Several prognostic factors for P-MEC were identified. The nomogram developed in this study accurately predicted the 5- and 10-year OS rates of American patients with P-MEC based on individual characteristics. Risk stratification using the survival nomogram can optimize individual therapies and follow-up.

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