基于随机生存森林分析，开发和验证一种预测口腔鳞状细胞癌患者特定疾病生存率的模型。
Development and validation of a model for the prediction of disease-specific survival in patients with oral squamous cell carcinoma: based on random survival forest analysis.
发表日期：2023 Aug 03
作者：
Na Wang, Yulan Lin, Haoyuan Song, Weihai Huang, Jingyao Huang, Liling Shen, Fa Chen, Fengqiong Liu, Jing Wang, Yu Qiu, Bin Shi, Lisong Lin, Baochang He
来源：
Cell Death & Disease
摘要：
建立一个用于预测口腔鳞状细胞癌（OSCC）患者疾病特异性生存率（DSS）的模型。从Surveillance, Epidemiology, and End Results（SEER）数据库中收集口腔鳞状细胞癌（OSCC）患者，并将其随机分为开发组（n=14,495）和内部验证组（n=9,625）。此外，还使用了一个来自中国东南部医院的队列进行外部验证（n=582）。根据开发组的TNM分期、辅助治疗、手术、肿瘤部位、年龄、分级和性别构建RSF模型。通过不同队列中的时间依赖ROC曲线确认了该模型的有效性。由于OSCC引起的死亡风险得分几乎呈指数增加，因此患者预后的风险得分较高的组别（所有对数秩和P<0.05）在开发、内部和外部验证队列中的预后明显较差。基于RSF，本研究创建了一个高性能的OSCC预后预测模型，并进行了验证。© 2023. 作者独家授权Springer-Verlag GmbH Germany、Springer Nature出版。
To establish a model for predicting the disease-specific survival (DSS) of patients with oral squamous cell carcinoma (OSCC).Patients diagnosed with OSCC from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into development (n = 14,495) and internal validation cohort (n = 9625). Additionally, a cohort from a hospital located in Southeastern China was utilized for external validation (n = 582).TNM stage, adjuvant treatment, surgery, tumor sites, age, grade, and gender were used for RSF model construction based on the development cohort. The effectiveness of the model was confirmed through time-dependent ROC curves in different cohorts. The risk score exhibited an almost exponential increase in the hazard ratio of death due to OSCC. In development, internal, and external validation cohorts, the prognosis was significantly worse for patients in groups with higher risk scores (all log-rank P < 0.05).Based on RSF, a high-performance prediction model for OSCC prognosis was created and verified in this study.© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.