子宫颈腺癌患者总生存列线图预测模型的建立和验证

Establishment and Validation of Nomogram Predicting the Overall Survival of Patients with Endocervical Adenocarcinoma

目的:探讨影响子宫颈腺癌(ECA)患者总生存预后的影响因素,并建立预测ECA患者总生存的列线图模型并验证。方法:检索SEER数据库中2004~2015年的子宫颈癌患者,纳入符合标准的模型组中ECA患者5952例及子宫颈鳞癌(CSCC)患者15593例,采用倾向性评分进行1∶1配对(各4941例),采用单因素和多因素Cox回归模型分析ECA对子宫颈癌预后的影响及ECA预后的影响因素,并基于Cox回归模型建立列线图预测模型。选择安徽医科大学第一附属医院ECA患者共122例进行验证,通过ECA患者模型组(5952例)和验证组(122例)验证的C指数、受试者工作特征曲线下面积(AUC)、校准曲线和决策曲线分析评估列线图的预测能力和临床应用价值。结果:(1)ECA是影响子宫颈癌预后的独立危险因素(HR 1.183,95%CI 1.096~1.277,P<0.001),其发病占比随时间的推移呈上升趋势。(2)年龄、种族、婚姻状况、分化程度、肿瘤大小、分期、手术、放疗和化疗均是影响ECA预后的影响因素。(3)列线图的模型组、国际妇产科联盟(FIGO)分期及验证组的C指数分别为0.863、0.761及0.792,均大于0.750。列线图模型组的1、3、5年曲线下面积(AUC)分别为0.927、0.902、0.886,验证组的AUC分别为0.872、0.739、0.870。决策曲线分析表明,在较宽的阈值概率范围内,列线图的净收益大于FIGO分期预测模型。结论:对影响ECA总生存的9个独立预后因素经过内外部验证,建立的ECA总生存列线图预测模型具有良好的预测能力和临床应用价值。

Objective:To explore the influencing factors of the overall survival prognosis of endocervical adenocarcinoma(ECA) patients, and establish and validate a nomogram for predicting the overall survival of patients with ECA.Methods:Endocervical carcinoma patients from 2004 to 2015 in SEER database were retrieved.5952 ECA patients and 15593 cervical squamous cell carcinoma(CSCC) patients were included in the model group which met the criteria.1∶1 matching(4941 patients each) was performed with the propensity score.Univariate and multivariate Cox regression models were used to analyze the impact of ECA on the prognosisand the prognostic factors for endocervical carcinoma.Nomogram was developed based on the Cox regression models.A total of 122 ECA patients from the First Affiliated Hospital of Anhui Medical University were selected for validation.The predictive ability and clinical application value of the nomogram were evaluated by the Harrell′s C-index, area under the subject′s working characteristic curve(AUC),calibration plots and DCA validated by ECA patient model group(5952 cases)and validation group(122 cases).Results:(1)ECA was an independent risk factor for the prognosis and survival of cervical cancer(HR 1.183,95%CI 1.096-1.277,PSymbol|@@0.001),and its incidence rate increased slightly with time.(2)Age, race, marital status, degree of differentiation, tumour size, stage, surgery, radiotherapy and chemotherapy were all independent factors related to prognosis of ECA.(3)The C-index of the model group, the International Federation of Gynecology and Obstetrics(FIGO) stage group and the validation group of the nomogram were 0.863,0.761 and 0.792,respectively, which were all greater than 0.750.The 1,3 and 5 year AUCs for the nomogram model group were 0.927,0.902,0.886,respectively, and the AUCs of the validation group were 0.872,0.739 and 0.870 respectively.The analysis of decision curve showed that the net benefit of OS nomogram was larger than that if FIGO stage prediction model in a wide range of threshold probabilities.Conclusions:The nomogram prediction model for overall survival of ECA,which was established based on the nine independent prognostic factors affecting overall survival of ECA,has good predictive ability and clinical application value after internal and external validation.