【摘要】 目的:探讨局部晚期子宫颈癌(LACC)患者的预后因素，并构建列线图模型。方法:选择2004年1月1日至2015年12月31日于监测、流行病学和最终结果(SEER)数据库LACC患者2021例为研究对象，按7∶3分为训练集(1414例)及内部验证集(607例),再选择2015年1月1日至2017年12月31日于山西医科大学第二医院确诊的134例LACC患者为外部验证集。通过LASSO-Cox回归分析筛选LACC的预后因素，构建LACC患者3、5、8年列线图模型，采用受试者工作特征(ROC)曲线、校准曲线和临床决策曲线分析(DCA)评估列线图的性能。并根据列线图得分将患者划分为低风险组和高风险组，绘制Kaplan-Meier曲线。结果:(1)年龄、种族、肿瘤直径、FIGO分期、手术、放疗、化疗和淋巴结切除数以及手术联合放化疗是影响患者总生存期(OS)的独立预后因素(P<0.05),采用以上9个关键变量构建预测LACC患者3、5、8年OS列线图模型。(2)模型具有较好的区分度，其3、5、8年AUC:训练集分别为0.663、0.681、0.681,内部验证集分别为0.705、0.721、0.721,外部验证集分别为0.707、0.726、0.726,AUC均大于0.65。校准曲线显示预测结果和实际结果高度吻合；DCA表明模型有良好的临床效用和应用价值。(3)Kaplan-Meier生存曲线分析显示列线图具有较好地识别高风险人群的能力。结论:基于多个独立预后因素建立LACC患者的生存预测模型具有良好的临床应用价值，为临床医生在评估患者预后和制定个性化治疗策略提供了重要的工具。更多还原

【Abstract】 Objective:To explore the prognostic factors in patients with locally advanced cervical cancer(LACC) and construct a nomogram model.Methods:A retrospective analysis was conducted on 2021 patients with LACC from the SEER database between January 1,2004,and December 31,2015.These patients were randomly divided into a training cohort and an internal validation cohort at a ratio of 7∶3.Additionally,134 patients diagnosed with LACC at the Second Hospital of Shanxi Medical University between January 1,2015,and December 12,2017,were included as an external validation cohort.Prognostic factors for LACC were screened using LASSO-Cox regression analysis, and nomogram models for predicting 3-,5-,and 8-year outcomes were constructed.The performance of the nomogram was evaluated using receiver operating characteristic(ROC) curves, calibration curves, and decision curve analysis(DCA).Based on the nomogram scores, patients were stratified into low-and high-risk groups, and Kaplan-Meier survival curves were plotted.Results:(1)Age, race, tumor diameter, FIGO stage, surgical status, radiotherapy status, chemotherapy status, number of lymph nodes removed, and surgery combined with radiotherapy or chemotherapy were identified as independent factors affecting overall survival(OS) in patients(P<0.05).Based on these nine key variables, a nomogram model was constructed to predict 3-,5-,and 8-year OS in LACC patients.(2)The model demonstrated good discriminative ability.In the training cohort, the AUCs values for 3-,5-,and 8-year OS were 0.663,0.681,and 0.681,respectively.In the internal validation cohort, the corresponding AUCs were 0.705,0.721,and 0.721.In the external validation cohort, the AUCs were 0.707,0.726,and 0.726.The AUC values are all greater than 0.65.The calibration curves showed good agreement between predicted and observed outcomes.DCA indicated that the model has favorable clinical utility and application value.(3)Kaplan-Meier analysis demonstrated that the nomogram effectively identified high-risk patient groups.Conclusions:The survival prediction model for LACC patients, based on multiple independent prognostic factors, demonstrates significant clinical application value.It provides clinicians with an important tool for assessing patient prognosis and formulating personalized treatment strategies.更多还原