Department of Dermatology, The First Affiliated Hospital of Jinan University, Jinan University Institute of Dermatology, Guangzhou, China.
School of Basic Medicine and Public Health, Jinan University, Guangzhou, China.
Int J Clin Pract. 2023 Feb 24;2023:3016994. doi: 10.1155/2023/3016994. eCollection 2023.
The objective of this study is to determine the prognostic factors of keratinizing squamous cell carcinoma of the tongue (KTSCC) and to establish a prognostic nomogram of KTSCC to assist clinical diagnosis and treatment.
This study identified 3874 patients with KTSCC from the Surveillance, Epidemiology, and End Results (SEER) database, and these patients were randomly divided into the training (70%, ( = 2711) and validation (30%, = 1163) cohorts. Cox regression was then used to filter variables. Nomograms were then constructed based on meaningful variables. Finally, the concordance index (C-index), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration charts, and decision-curve analysis (DCA), were used to evaluate the discrimination, accuracy and effectiveness of the model.
A nomogram model was established for predicting the 3-, 5-, and 8-year overall survival (OS) probabilities of patients with KTSCC. The model indicated that age, radiotherapy sequence, SEER stage, marital status, tumor size, American Joint Committee on Cancer (AJCC) stage, radiotherapy status, race, lymph node dissection status, and sex were factors influencing the OS of patients with KTSCC. Verified by C-index, NRI, IDI, calibration curve, and DCA curve, our model has better discrimination, calibration, accuracy and net benefit compared to the AJCC system.
This study identified the factors that affect the survival of KTSCC patients and established a prognostic nomogram that can help clinicians predict the 3-, 5-, and 8-year survival rates of KTSCC patients.
本研究旨在确定舌角化鳞状细胞癌(KTSCC)的预后因素,并建立 KTSCC 的预后列线图,以辅助临床诊断和治疗。
本研究从监测、流行病学和最终结果(SEER)数据库中确定了 3874 例 KTSCC 患者,这些患者被随机分为训练队列(70%,(=2711)和验证队列(30%,(=1163)。然后使用 Cox 回归筛选变量。根据有意义的变量构建列线图。最后,使用一致性指数(C 指数)、净重新分类指数(NRI)、综合判别改善(IDI)、校准图和决策曲线分析(DCA)评估模型的判别、准确性和有效性。
建立了一个预测 KTSCC 患者 3、5 和 8 年总生存率(OS)概率的列线图模型。该模型表明,年龄、放疗顺序、SEER 分期、婚姻状况、肿瘤大小、美国癌症联合委员会(AJCC)分期、放疗状况、种族、淋巴结清扫状况和性别是影响 KTSCC 患者 OS 的因素。通过 C 指数、NRI、IDI、校准曲线和 DCA 曲线验证,与 AJCC 系统相比,我们的模型具有更好的判别、校准、准确性和净效益。
本研究确定了影响 KTSCC 患者生存的因素,并建立了一个预后列线图,可帮助临床医生预测 KTSCC 患者 3、5 和 8 年的生存率。