Development and validation of a nomogram for prognosis of sinonasal squamous cell carcinoma

Autor:	Lifen Zou, Huatao Quan, Shengzi Wang, Wei Yuan, Haiyan Zhang, Li Yan
Rok vydání:	2019
Předmět:	Counseling Male Oncology medicine.medical_specialty Multivariate analysis Nose Neoplasms Malignancy Cohort Studies 03 medical and health sciences 0302 clinical medicine Predictive Value of Tests Internal medicine Paranasal Sinuses Epidemiology medicine Humans Immunology and Allergy Basal cell Neoplasm Metastasis Stage (cooking) 030223 otorhinolaryngology Aged Neoplasm Staging Aged 80 and over business.industry Proportional hazards model Reproducibility of Results Middle Aged Nomogram Prognosis medicine.disease Survival Analysis Nomograms 030228 respiratory system Otorhinolaryngology Carcinoma Squamous Cell T-stage Female business
Zdroj:	International Forum of Allergy & Rhinology. 9:1030-1040
ISSN:	2042-6984 2042-6976
DOI:	10.1002/alr.22354
Popis:	Background Sinonasal squamous cell carcinoma (SNSCC) is a rare malignancy with varied outcomes. The aim of this study was to develop a nomogram for predicting survival of patients with SNSCC. Methods From the Surveillance, Epidemiology, and End Results database, we identified 1766 patients diagnosed with SNSCC between 2004 and 2015. Patients were randomly separated into a training set and a validation set in 4:1 ratio. An external validation was also performed by a set of 74 SNSCC patients who had been treated in our department. We used the training set to build a nomogram based on stratified multivariable Cox proportional hazard models for predicting overall survival. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index and calibration curve. Results Based on 1412 cases of the training cohort, our Cox regression analysis revealed that age, marital status, primary site, differentiation, T stage, N classification, M stage, and treatment modalities were associated with overall survival. A nomogram was established based on the results of multivariate analysis. The C-index values of the nomogram for predicting survival were superior to those of the tumor-node-metastasis staging system (0.745 vs 0.679 in the training cohort, 0.752 vs 0.656 in the validation set, and 0.678 vs 0.596 in the external validation set). The calibration plots demonstrated good consistency between the predicted and observed results. Conclusion We have developed a nomogram to accurately predict the clinical outcomes of SNSCC patients. This model was effective and can help clinicians to improve patient counseling.
Databáze:	OpenAIRE
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