Construction of a Nomogram Model for the Risk of Recurrence After Tumor Cytoreductive Surgery in Ovarian Cancer Patients
Objective To construct a nomogram model for the risk of postoperative recurrence in ovarian cancer patients undergoing tumor cytoreductive surgery(CRS).Methods Retrospectively select 52 ovarian cancer patients who experienced recurrence within 1 year after receiving CRS treatment at Zhengzhou Central Hospital Affiliated to Zhengzhou University from June 2019 to June 2022 as the occurrence group,and another 52 ovarian cancer patients who did not relapse within 1 year after receiving CRS treatment at the hospital during the same period as the non-occurrence group.The clinical medical records were compared between the two groups,and a column chart prediction model for postoperative recurrence risk of CRS in ovarian cancer patients was constructed through logistic regression analysis.The predictive performance was evaluated through receiver operating characteristic(ROC)curve.Results The proportion of diabetes history,preoperative carbohydrate antigen(CA125)level,and human epididymal protein 4(HE4)level in the occurrence group were higher than those in the non-occurrence group,while the ALB level was lower than that in the non-occurrence group(P＜0.05).Logistic regression analysis showed that diabetes CA125,HE4,albumin(ALB)were the influencing factors for the recurrence of ovarian cancer patients after CRS(P＜0.05).Draw a column chart to construct a risk prediction model for postoperative recurrence of CRS in ovarian cancer patients,and verify that the model's discrimination shows a C-index value of 0.904,which has good discrimination.The results of the Hosmer-Lemeshow goodness of fit test show that the model fits well(P=0.327).Draw a standard curve to show that the calibration curve is similar to the Y-X line,and the model accuracy was good.The predictive performance of the model was validated,and the results showed that the area under the curve(AUC)of the predictive model for evaluating postoperative recurrence of CRS in ovarian cancer patients was 0.904,indicating good predictive performance.The decision curve shows that the column chart risk prediction model has important clinical value in predicting postoperative recurrence of CRS in ovarian cancer patients.Conclusion Diabetes,preoperative CA125,HE4 and preoperative ALB are the influencing factors of postoperative recurrence of ovarian cancer patients with CRS.The nomogram risk prediction model based on the above indicators has good predictive value.
ovarian cancertumor cytoreductive surgeryrecurrencenomogram model
万方数据
维普
