Prognostic Significance of preoperative serum CA125, CA19-9, CA72-4, CEA, and AFP in Patients with Endometrial cancer

Objective: To determine preoperative serum CA125, CA19-9, CA72-4, CEA, and AFP with prognostic value, and to establish a risk score based on CA125, CEA, AFP levels for predicting the overall survival (OS) and progression-free survival (PFS) of endometrial cancer (EC) patients. Methods: A retrospective cohort study with 2081 EC patients was conducted at Shengjing Hospital of China Medical University. Patient baseline information, tumor characteristics, and data on five serum biomarkers (CA125, CA19-9, CA72-4, CEA, and AFP) were collected. Hazard ratios (HRs) and 95% confidence intervals (CIs) were determined using univariate or multivariate Cox proportional hazard models. log-rank test and Kaplan-Meier analysis were used to compared survival, Data were randomly divided into a training cohort (50%, N = 1041) and an external validation cohort (50%, n = 1040). the least absolute shrinkage and selection operator (Lasso)-Cox regression model was used to screen the independent factors for establishing risk score. And develop nomograms for survival rate prediction. Results: Multivariate analysis showed Elevated CA125 (P<0.0001) AFP (P <0.0001) and CEA(P=0.037) were identified as independent biomarkers for PFS. Increased CA125 (P = 0.003) AFP (P <0.0001) and CEA(P=0.014) were independent factors associated with OS. CA125, AFP and CEA were thus incorporated in an innovative Risk score (RS) by Lasso-Cox regression model, The RS was also an independent indicator for PFS (P<0.0001) and OS (P<0.0001). Furthermore, we developed and validated nomogram based on Cox regression models. The discriminative ability and calibration of the nomograms revealed good predictive ability, as indicated by the calibration plots. Conclusion: This study suggests that the risk score based on preoperative serum levels of CA125, CEA, and AFP was prognostic biomarkers for predicting progression-free survival and overall survival for EC patients. Nomograms based on the RS and clinicopathological features accurately predict Prognosis of EC patients. ### Competing Interest Statement The authors have declared no competing interest.