A Nomogram Prediction Model for Predicting Pathological Stage and Grade of Endometrial Carcinoma Based on Inflammation and Cancer Antigen 125

Objective To investigate the predictive value of inflammatory markers and Cancer antigen 125 (CA125) for preoperative pathological staging and grading of endometrial carcinoma (EC) . Methods A selection of 214 EC patients admitted from 2021-2023, randomized into the training set (134 cases) and validation set (80 cases) . Inflammatory markers (NLR, PLR, SII) and CA125 levels were measured in all patients. The pathological and stages grades of EC patients were evaluated, and the differences in inflammatory markers and CA125 levels among patients with different pathological stages and grades were compared, Establish a column chart prediction model to analyze the predictive value of inflammation indicators and CA125 for preoperative early EC pathological and stages grades. Results There were 120 cases of TNM stage Ⅰ, 4 cases of stage Ⅱ and 10 cases of stage Ⅲ in the training set. 16 cases of International Federation of Gynecology and Obstetrics (FIGO) grade 1, 79 cases of grade 2 and 39 cases of grade 3 in the training set. NLR, PLR, and CA125 in EC patients with TNM pathological stages Ⅱ and Ⅲ were higher than those TNM in pathological stage I (P < 0.05) . NLR, PLR, and CA125 in EC patients with FIGO grades 2 and 3 were higher than those in FIGO grade 1 (P < 0.05) . Based on NLR, PLR, SII and CA125, a nomogram prediction model for EC TNM pathological stage and FIGO grade in the training set was established. Bootstrap method was used to verify the model discrimination and draw the calibration curve. The results showed that the calibration curve Y and X lines of the training set and the validation set were similar, and the nomogram model discrimination was good. The ROC curve revealed that the AUC of the nomogram model between the training set and the validation set for predicting the risk of high preoperative EC stage and high pathological grade was > 0.90, which had a high predictive value. Conclusion The nomogram prediction model based on inflammation and CA125 has a high predictive value for the pathological stage and grade of preoperative EC.