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| ⅢC1r期宫颈癌患者盆腔淋巴结转移预测模型的建立及评价 |
| Establishment and Evaluation of a Nomogram for Pelvic Lymph Node Metastasis in Stage ⅢC1r Cervical Cancer Patients |
| 投稿时间：2025-06-18 修订日期：2025-10-09 |
| DOI： |
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| 中文关键词: 宫颈肿瘤 淋巴结转移 危险因素 预测模型 |
| 英文关键词:cervical cancer lymph node metastasis risk factors prediction model |
| 基金项目: |
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| 摘要点击次数: 142 |
| 全文下载次数: 3 |
| 中文摘要: |
| [目的] 基于基线临床数据、血清肿瘤标志物水平和系统性炎症免疫指标构建ⅢC1r期宫颈癌患者盆腔淋巴结转移的预测模型。[方法] 选取郑州大学第三附属医院妇科2018年1月至2024年12月收治的254例术前影像学提示淋巴结转移且最大径<20 mm的ⅢC1r期宫颈癌患者，患者接受了根治性子宫切除术及盆腔淋巴结清扫术，部分患者同时行腹主动脉旁淋巴结清扫术。术后病理显示盆腔淋巴结转移134例(52.76%)，无盆腔淋巴结转移120例(47.24%)。研究采用R4.4.3软件将254例研究对象通过随机抽样法按7:3比例拆分为训练集（n=178）与验证集（n=76）。采用多因素Logistic回归分析确定影响ⅢC1r期宫颈癌患者盆腔淋巴结转移的独立危险因素，据此构建列线图预测模型，采用受试者工作特征（receiver operating characteristic, ROC）曲线及校准曲线对模型进行验证。[结果] ①多因素 Logistic回归分析发现鳞状细胞癌抗原(squamous cell carcinoma antigen ,SCC-Ag)≥3.42 ng/ml (OR=3.517, P=0.004)、系统性免疫炎症指数(systemic immune-inflammation index, SII)≥367.38 (OR=3.695, P=0.004)、肿瘤直径≥32.95 mm(OR=3.151, P=0.009)、淋巴结最大径≥11.25 mm(OR=10.898, P=0.000)是ⅢC1r期宫颈癌患者盆腔淋巴结转移的独立危险因素。②基于以上4项独立危险因素构建了盆腔淋巴结转移风险预测模型。在模型效能验证中，训练集和验证集的ROC曲线下面积分别达0.828（95% CI:0.768~0.883）和0.833(95%CI :0.737~0.919）。经验证校准曲线接近理想曲线。[结论] 基于SCC-Ag、SII、肿瘤直径和淋巴结最大径构建的预测模型用于预测ⅢC1r期宫颈癌患者的盆腔淋巴结转移效能较佳，为 ⅢC1r期宫颈癌患者的个体化诊疗提供科学的参考依据。 |
| 英文摘要: |
| [Objective] A predictive model for pelvic lymph node metastasis in stage Ⅲ C1r cervical cancer patients was constructed based on baseline clinical data, serum tumor marker levels, and systemic inflammatory immune markers. [Methods] A total of 254 patients with stage Ⅲ C1r cervical cancer, who had preoperative imaging findings suggestive of lymph node metastasis and maximum diameter <20 mm, were enrolled from January 2018 to December 2024 at the Department of Gynecology, The Third Affiliated Hospital of Zhengzhou University. All patients underwent radical hysterectomy and pelvic lymph node dissection, some also underwent para-aortic lymph node dissection. Postoperative pathology revealed pelvic lymph node metastasis in 134 cases (52.76%) and no pelvic lymph node metastasis in 120 cases (47.24%). The study employed R4.4.3 software to randomly divide 254 subjects into a training set (n=178) and a validation set (n=76) at a 7:3 ratio. Multivariate logistic regression analysis was employed to identify independent risk factors influencing pelvic lymph node metastasis in stage ⅢC1r cervical cancer patients. Based on these findings, a nomogram prediction model was constructed and validated using receiver operating characteristic (ROC) curves and calibration curves. [Results] ①Multivariate logistic regression analysis revealed that squamous cell carcinoma antigen (SCC-Ag) ≥3.42 ng/mL (OR=3.517,P=0.004), systemic immune-inflammation index (SII) ≥367.38 (OR=3.695,P=0.004), tumor diameter≥32.95mm (OR=3.151,P=0.009), and maximum lymph node diameter ≥11.25mm (OR=10.898, P=0.000) were identified as independent risk factors for pelvic lymph node metastasis in stage ⅢC1r cervical cancer patients.②Based on the above four independent risk factors, a predictive model for pelvic lymph node metastasis risk was constructed. In model validation, the area under the ROC curve reached 0.828 (95% CI: 0.768~0.883) for the training set and 0.833 (95% CI: 0.737~0.919) for the validation set. The calibration curve approached the ideal curve upon verification. [Conclusions] A predictive model incorporating SCC-Ag, SII, tumor diameter, and maximum lymph node diameter demonstrated superior efficacy in predicting pelvic lymph node metastasis in stage ⅢC1r cervical cancer patients, providing a scientifically sound reference for individualized diagnosis and treatment of this patient population. |
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