上海口腔医学

上海口腔医学 ›› 2021, Vol. 30 ›› Issue (6): 644-648.doi: 10.19439/j.sjos.2021.06.016

• 论著 • 上一篇    下一篇

基于SEER数据库的颊黏膜鳞状细胞癌的预后列线图构建

林阳*, 蒋位财*, 邱宇, 高炳菊, 李军, 陈鹏, 林李嵩   

  1. 福建医科大学附属第一医院 口腔颌面外科,福建 福州 350005
  • 收稿日期:2020-08-11 修回日期:2020-10-30 发布日期:2022-03-09
  • 通讯作者: 林李嵩,E-mail: dr_lls@163.com
  • 作者简介:林阳（1992-）,男,住院医师,E-mail: komesly@163.com;蒋位财（1993-）,男,在读硕士研究生,E-mail: doctor_jiangwc@163.com。*并列第一作者
  • 基金资助:
    福建省科技创新联合资金（2019Y9128）

Construction of prognostic nomogram for squamous cell carcinoma of the buccal mucosa based on SEER database

LIN Yang, JIANG Wei-cai, QIU Yu, GAO Bing-ju, LI Jun, CHEN Peng, LIN Li-song   

  1. Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Fujian Medical University. Fuzhou 350005, Fujian Province, China
  • Received:2020-08-11 Revised:2020-10-30 Published:2022-03-09

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摘要： 目的: 基于监测、流行病学和最终结果（SEER）数据库构建颊黏膜鳞状细胞癌（BMSCC）患者预后列线图模型。方法: 通过SEER数据库,纳入原发性BMSCC患者583例。利用R语言（R 3.6.0）进行列线图模型构建,Cox比例风险模型分析与BMSCC预后相关的危险因素,最终根据Cox比例风险模型分析结果构建列线图。通过与TNM分期系统比较一致性与区分度,评估模型的预测效果;绘制校准曲线与一致性指数,评价模型的一致性。采用SPSS 22.0软件包绘制受试者工作特征曲线与Kaplan-Meier生存曲线,评价模型的区分度。结果: 多因素Cox分析显示,年龄、T分期、N分期是BMSCC患者预后的独立危险因素并纳入列线图构建。列线图组的校准曲线与一致性指数均显著优于TNM分期组。列线图组受试者工作特征曲线与Kaplan-Meier生存曲线区分度均优于TNM分期组。列线图模型在BMSCC患者生存率预测的一致性与区分度上均优于TNM分期系统。结论: 基于SEER数据库构建的针对BMSCC预后的列线图预测模型,比TNM分期系统具有更好的预测效能。

关键词: 颊黏膜, 鳞状细胞癌, 监测、流行病学和最终结果数据库, 列线图

Abstract: PURPOSE: To construct a nomogram for predicting prognosis of buccal mucosal squamous cell carcinoma (BMSCC) patients based on the surveillance, epidemiology and end results (SEER) database. METHODS: Five hundred and eight-three patients with primary BMSCC were included through the SEER database. R 3.6.0 was used to construct the nomogram model, Cox regression model was used to analyze the risk factors related to the prognosis of BMSCC, and construct the nomogram. The predictive capacity of the model was evaluated by comparison of calibration and discrimination with TNM (tumor, node, metastasis) staging system. Calibration curve and consistency index were used to evaluate the calibration of the model. SPSS 22.0 software package was used to construct receiver operating characteristic (ROC) curve and Kaplan-Meier survival curve was used to evaluate the discrimination of the model. RESULTS: Multivariate Cox analysis showed that age, T stage, and N stage were independent risk factors for the prognosis of BMSCC patients and were included in the construction of a nomogram. The calibration curve and consistency index of the nomogram group were significantly better than the TNM staging group. The discrimination between ROC curve and Kaplan-Meier survival curve in the nomogram group were better than the TNM staging group. This nomogram model was superior to the TNM staging system in terms of calibration and discrimination in predicting prognosis of BMSCC patients. CONCLUSIONS: A nomogram is constructed for predicting prognosis of BMSCC patients based on the SEER database which has better predictive performance than the TNM staging system.

Key words: Buccal mucosa, Squamous cell carcinoma, Surveillance,epidemiology and end results database, Nomogram

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