Prognostic factors for overall survival in patients with Merkel cell carcinoma
10.3760/cma.j.cn.115807-20200601-00170
- VernacularTitle:皮肤Merkel细胞癌患者总生存率的预测模型建立及其效果评价
- Author:
Rujing PAN
1
;
Xuan XUAN
;
Liyue HOU
;
Jingjing LIU
Author Information
1. 温州医科大学附属第一医院皮肤科 325000
- From:
Chinese Journal of Endocrine Surgery
2020;14(5):422-427
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To identify prognosis factors in patients with resected Merkel cell carcinoma and construct a nomogram for predicting 3- and 5-year overall survival.Methods:A total of 1271 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. According to the ratio of 70:30, patients were randomly divided into training cohort ( n=891) and validation cohort ( n=380) . Cox regression model was fitted with R software, thus the prognostic factors for 3- and 5-year overall survival were confirmed and a nomogram to predict overall survival was established. C-index was used to evaluate model discrimination and the calibration plot was used to evaluate model accuracy.The predictive power of the model was compared with the eighth TNM staging system. Results:Multivariable cox analysis indicated age, sex, tumor size, N stage, M stage, marital status and radiation therapy were associated with overall survival. The above predictors were employed to build a new nomogram, and we found that the new predictive model was better at predicting 3- and 5- year overall survival than the latest TNM staging system. The C-index of the training cohort using the new model for survival prediction was 0.72, and the C-index of the training cohort using TNM staging system was only 0.64. The C-index of the validation cohort using the new model for survival prediction was 0.73, while the C-index of the validation cohort using TNM staging system was 0.63. The nomogram also displayed a good calibration.Conclusions:The new predictive model with comprehensive prognostic factors is superior to the 8th TNM staging system in predicting overall survival of patients with Merkel cell carcinoma. This new model can help doctors to predict the prognosis of each patient more accurately, and assist clinical decision-making and individualized treatment.
