中国口腔颌面外科杂志 ›› 2025, Vol. 23 ›› Issue (5): 469-475.doi: 10.19438/j.cjoms.2025.05.007

• 论著 • 上一篇    下一篇

T1-T2期口腔鳞癌根治术后颈淋巴结转移的影响因素分析及预测模型构建

章旺茹1, 陈媛媛1, 李志萍2, 孟箭2, 彭森3   

  1. 1.徐州医科大学徐州临床医学院,江苏 徐州 221000;
    2.徐州市中心医院 口腔科,3.病理科,江苏 徐州 221000
  • 收稿日期:2024-11-25 修回日期:2025-03-04 发布日期:2025-10-10
  • 通讯作者: 李志萍,E-mail:jslzp@163.com
  • 作者简介:章旺茹(1996-),女,硕士,E-mail:2522499323@qq.com
  • 基金资助:
    徐州市重点科技项目(KC20088); 国家口腔疾病临床医学研究中心开放课题(NCRCO-202101)

Influencing factors of cervical lymph node metastasis after radical surgery for oral squamous cell carcinoma in stages T1 and T2 and construction of a prediction model

Zhang Wangru1, Chen Yuanyuan1, Li Zhiping2, Meng Jian2, Peng Sen3   

  1. 1. Xuzhou Clinical Medical College of Xuzhou Medical University. Xuzhou 221000;
    2. Department of Stomatology, 3. Department of Pathology, Xuzhou Central Hospital. Xuzhou 221000, Jiangsu Province, China
  • Received:2024-11-25 Revised:2025-03-04 Published:2025-10-10

摘要: 目的: 探讨T1-T2期口腔鳞状细胞癌(口腔鳞癌,oral squamous cell carcinoma,OSCC)根治术后淋巴结转移的相关危险因素,并构建列线图风险预测模型。方法: 收集徐州市中心医院134例T1-T2期OSCC患者的临床资料,包括一般情况、颈淋巴结转移情况、组织分化程度、肿瘤出芽、浸润深度、淋巴管血管侵犯、周围神经侵犯、鳞状细胞癌抗原(SCC-Ag)等相关指标。通过logistic回归分析筛选出颈淋巴结转移的独立影响因素,进一步构建列线图,使预测模型可视化。绘制受试者工作特征曲线、校准曲线和临床决策曲线,依次对预测模型的区分度、校准度及临床有效性进行评价。结果: T分期、组织分化程度、浸润深度、淋巴管血管侵犯是早期OSCC发生颈淋巴结转移的独立影响因素。列线图预测模型的曲线下面积(AUC)为0.875,灵敏度为87.80%,特异度为72.04%,表明该模型具有良好的区分度和校准度。临床决策曲线显示,该列线图预测早期OSCC颈淋巴结转移风险的净获益较大,具有良好的临床有效性。结论: T分期、组织分化程度、浸润深度及淋巴管血管侵犯是影响T1-T2期OSCC颈淋巴结转移的独立危险因素,据此建立的列线图预测模型具有良好的检测效能,可为早期OSCC患者制订精准临床治疗方案提供参考。

关键词: 口腔鳞癌, 头颈癌, 颈淋巴结转移, 浸润深度, 淋巴管血管侵犯, 列线图, 预测模型

Abstract: PURPOSE: To investigate the influencing factors for cervical lymph node metastasis in stage T1 and T2 oral squamous cell carcinoma(OSCC) after radical surgery and to construct nomogram prediction models. METHODS: This retrospective cohort study collected clinical data from 134 patients diagnosed with stage T1-T2 OSCC at Xuzhou Central Hospital. The data included patients' general information, cervical lymph node metastasis, tissue differentiation degree, tumor budding, depth of invasion, lymphovascular invasion, peripheral nerve invasion, squamous cell carcinoma antigen (SCC-Ag) levels, et al. Logistic regression analysis was employed to identify independent factors influencing cervical lymph node metastasis, leading to the construction of a nomogram to visualize the prediction model. The study also involved drawing receiver operating characteristic curves, calibration curves, and clinical decision curves to evaluate the discrimination, calibration, and clinical validity of the prediction model. RESULTS: T stage, degree of tissue differentiation, depth of invasion and lymphovascular invasion were independent factors influencing cervical lymph node metastasis in early OSCC. The area under the curve(AUC) for the nomogram prediction model was 0.875, with a sensitivity of 87.80% and a specificity of 72.04%, demonstrating good discrimination and calibration. The clinical decision curve analysis revealed that this nomogram offered a significant net benefit in predicting the risk of cervical lymph node metastasis in early-stage OSCC, affirming its clinical validity. CONCLUSIONS: T stage, degree of tissue differentiation, depth of invasion, and lymphovascular invasion were independent risk factors for cervical lymph node metastasis in patients with T1-T2 stage oral squamous cell carcinoma. The established nomogram prediction model demonstrated strong detection performance and could be effectively utilized for patients with clinically early-stage OSCC. These precise treatment plans offered valuable reference points.

Key words: Oral squamous cell carcinoma, Head and neck cancer, Cervical lymph node metastasis, Depth of infiltration, Lymphatic vascular invasion, Nomogram, Predictive model

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