基于Nomogram预测模型分析血清人附睾蛋白4对卵巢癌复发的影响  

The effect of HE4 on recurrence of ovarian cancer:based on Nomogram prediction model

作　　者：古丽加那提 王家俊[1] 孙柳柳[1] 赵敏[1] 赵绍杰[1] GULI Jianati;WANG Jiajun;SUN Liuliu;ZHAO Min;ZHAO Shaojie(Department of Gynaecology,Wuxi Maternal and Child Health Hospital,Wuxi 214002,Jiangsu,China)

机构地区：[1]无锡市妇幼保健院妇科,江苏无锡214002

出　　处：《中国性科学》2021年第9期80-83,共4页Chinese Journal of Human Sexuality

基　　金：2020年无锡市卫健委科研项目(M202053)。

摘　　要：目的探究影响卵巢癌复发风险的危险因素并构建预测模型,改善患者预后情况。方法选取2017年1月至2018年10月在无锡市妇幼保健院妇科确诊的109例卵巢癌患者作为研究对象。经过手术治疗后对患者进行为期2年的随访,根据随访结果将患者分为复发组和未复发组。比较两组的基线资料,通过Cox回归分析影响卵巢癌复发的危险因素,构建卵巢癌复发风险Nomogram预测模型,并采用受试者工作特征(ROC)曲线比较单一指标、卵巢恶性肿瘤风险评估(ROMA)指数、哥本哈根指数(CPH-I)和预测模型对患者复发风险的诊断效能。结果年龄≥56岁、肿瘤大小≥53mm、国际妇产科联盟(FIGO)分期为Ⅲ期、血清人附睾蛋白4(HE4)≥182.50pmol/L、糖类抗原125(CA125)≥37U/mL为卵巢癌患者术后复发的独立危险因素。根据以上因素构建预测卵巢癌复发风险的Nomogram模型,ROC曲线分析结果显示,预测模型对卵巢癌复发风险的预测价值大于HE4、CA125单独的预测价值,优于ROMA指数和CPH-I指数。结论以患者年龄、肿瘤大小、FIGO分期、HE4和CA125水平等因素构建的Nomogram预测模型,对卵巢癌患者术后复发风险有较好的诊断效能,对改善患者预后有重要参考价值。Objective To explore the factors that affect the risk of ovarian cancer recurrence and build a predictive model to improve the prognosis of patients.Methods 109 ovarian cancer patients diagnosed in Wuxi Maternal and Child Health Hospital from January 2017 to October 2018 were selected as the research subjects.Patients were followed up for 2 years after surgery,and were divided into recurrence group and non-recurrence group according to the follow-up results.To establish a Nomogram prediction model for ovarian cancer recurrence by Cox regression analysis,the baseline data of the two groups were compared.Receiver operating characteristic(ROC)curves were used to compare the diagnostic efficacy of a single indicator,the risk of ovarian malignancy algorithm(ROMA)index,the Copenhagen index(CPH-I),and the predictive model for recurrence risk.Results Age≥56 years,tumor size≥53 mm,FIGO stageⅢ,serum human epididymal protein 4(HE4)≥182.50 pmol/L,sugar antigen 125(CA125)≥37 U/mL were independent risk factors for postoperative recurrence of ovarian cancer.Based on the above factors,a Nomogram model is constructed to predict the risk of ovarian cancer recurrence.ROC curve analysis shows that the prediction value of the model is greater than that of HE4 and CA125 alone,and better than ROMA index and CPH-I index.Conclusions The Nomogram prediction model,constructed with factors such as patient age,tumor size,FIGO stage,HE4 and CA125 levels,has a good diagnostic performance for the risk of recurrence in patients with ovarian cancer,and has important reference value for improving the prognosis of patients.

关 键 词：卵巢癌 复发 血清人附睾蛋白4 Nomogram预测模型 

分 类 号：R711[医药卫生—妇产科学]