A Nomogram Prediction Model For Lymph Node Metastasis In Endometrial Cancer Patients

Objectives:The determination of lymph node(LN)status is critical for evaluating prognosis and identifying the necessity of adjuvant therapy of endometrial cancer(EC)patients.However,the significance of systematic lymphadenectomy remains controversial.This study aimed to explore the risk factors for lymph node metastasis(LNM)in patients with EC and develop a clinically useful nomogram based on clinicopathological parameters to predict it.Methods:The date of patients who underwent staging surgery including hysterectomy,pelvic lymphadenectomy(more than 15 LN removed)with or without para-aortic lymphadenectomy for EC were abstracted from Qilu Hospital of Shandong University,from 2005.01.01 to 2019.06.30.All the patients did not receive other treatments such as radiotherapy,chemotherapy or hormones before surgery.Patients with sarcoma,carcinosarcoma,leiomyosarcoma,a double primary tumor,or other metastatic cancer were excluded.Clinicopathological parameters were collected and determined as followed:patient-related characteristics(age at diagnosis,gestation,production,abortion,symptoms before diagnosis including abnormal vaginal fluid and abnormal vaginal bleeding,comorbidities including endocrine and cardiovascular diseases,history of smoking,history of and drinking,menopause),tumor characteristics(histological type,histological grade,FIGO stage,depth of myometrial invasion,lymphovascular invasion(LVSI),cervical involvement,and parametrial involvement)and the results of preoperative hematologic examination(white blood cell(WBC)count,red blood cell(RBC)count,hemoglobin(HGB),blood platelet(PLT),lymphocyte,albumin/globulin ratio,total cholesterol,and triglyceride).Parameters including patient-related,tumor-related,and preoperative hematologic examination-related were analyzed by univariate and multivariate logistic regression to determine the correlation with LNM.Based on the analysis results,a nomogram was constructed to predict for LNM by R software.Internal validation of the nomogram was conducted via a bootstrap method.Concordance index(c-index)was used to evaluate the accuracy of the prediction.Results:1、The overall data from the 1517 patients who met the inclusion criteria were analyzed.105(6.29%)patients had LNM.Among them,74(4.87%)patients had pelvic LNM,5(0.33%)patients had para-aortic LNM,and 26(1.71%)patients had both pelvic and para-aortic LNM,respectively.2、According the univariate analysis,age,histological type,histological grade,depth of myometrial invasion,LVSI,cervical involvement,parametrial involvement,HGB,albumin/globulin ratio,total cholesterol and triglyceride were all significantly associated with LNM,whereas other parameters were not.3、By multivariate logistic regression analysis,LVSI is the most predictive factor for LNM,patients with positive LVSI had 8.853-fold increased risk for LNM(95%CI:5.326-14.715;P<0.001).In addition,histological type(OR:3.195;95%CI:1.825-5.596;P<0.001),histological grade(OR:2.326;95%CI:1.157-4.676;P=0.018),depth of myometrial invasion(OR:2.362;95%CI:1.423-3.920;P=0.001),parametrial involvement(OR:7.77;95%CI:2.442-24.723;P=0.001)and HGB(OR:0.985;95%CI:0.972-0.997;P=0.016)remained significant predictors of LNM,whereas cervical involvement was borderline significant(OR:1.77;95%CI:0.9783.203;P=0.059,).4、The nomogram was constructed and incorporated clinical variables from the final multivariate model including histological type,histological grade,depth of myometrial invasion,LVSI,cervical involvement,parametrial involvement,and HGB levels.The sensitivity was 94.29%,the specificity was 69.62%,the positive predictive value was 18.8%,and the negative predictive value was 99.4%.The nomogram was crossvalidated internally by the 200 repetitions of bootstrap sample corrections,and the mean absolute error(MAE)is 0.015.For the prediction of LN involvement,the nomogram showed good discrimination accuracy with the C-index of 0.899(95%CI:0.870-0.927).Conclusions:LNM can be predicted by histological type,histological grade,depth of myometrial invasion,LVSI,cervical involvement,parametrial involvement,and HGB levels.This study successfully established an LNM prediction model for EC patients based on nomograms,with high accuracy and high clinical value.