建立与验证局部晚期宫颈癌患者放疗学结局的列线图

Development and validation of a novel nomogram for radiotherapy outcomes in locally advanced cervical cancer patients.

目的:建立并验证局部晚期宫颈癌(LACC)患者放疗学结局的列线图。方法:回顾分析江西省妇幼保健院肿瘤科2013年1月至2017年12月收治的1567例LACC患者的临床病理资料。结果:随机将1567例LACC患者分为训练集(1097例)和验证集(470例)。收集的数据包括临床特征和随访信息。缺失数据采用多重推断方法进行估计。单因素分析发现,年龄、FIGO分期、T分期、N分期、肿瘤最大径线、治疗方案、总治疗时间是影响LACC患者放疗学结局的危险因素,通过正向逐步选择对多变量Cox比例风险模型中的变量进行识别并创立列线图,包括T分期、N分期、年龄、肿瘤最大经线、治疗方式、总治疗时间。C指数与AUC显示,列线图模型具有良好的预测能力。列线图在临床适用性校准和决策曲线分析中表现良好。按列线图评分分层的3个风险组中,患者的OS存在显著差异(P<0.001)。结论:本研究开发了一种新的列线图来预测LACC患者经标准治疗的总生存率。列线图具有显著的鉴别能力和预测精度,有助于临床医生评估LACC患者的预后,并制定个体化的治疗和随访策略。

Objective:Development and validation of a novel nomogram to predict overall survival in locally advanced cervical cancer patients with radiotherapy outcomes.Methods:A retrospective study was conducted on the case data of LACC patients admitted to the Oncology Department of Jiangxi Maternal and Child Health Hospital from January 2013 to December 2017.Results:A total of 1567 LACC patients were analyzed and randomly divided into a training set(1097 cases,70%)and a validation set(470 cases,30%).The collected data included clinical features and follow-up information.Missing data was estimated using multiple inference methods.Univariate analysis identified seven risk factors(age,FIGO stage,T stage,N stage,tumor maximum diameter,and treatment plan,overall treatment time),identified the variables in the multivariate Cox proportional risk model through positive stepwise selection,and created a column chart,including T stage,N stage,age,maximum tumor meridian,and treatment method.The C index and AUC showed that the column chart model had good predictive ability.In addition,the column chart performed well in clinical applicability calibration and decision curve analysis.Among the three risk groups graded according to the column chart,there was a significant difference in patient OS(P<0.001).Conclusion:This study developed a new column chart to predict the overall survival rate of LACC patients after standard treatment.The column chart has a significant discriminative ability and predictive accuracy,which can help clinical doctors evaluate the prognosis of LACC patients and develop personalized treatment and follow-up strategies.