Integration of pretreatment tumor markers in a nomogram model for prognostic prediction of FIGO stage I endometrial cancer: A multi-institutional cohort study.

Abstract

Traditionally, the prognosis of patients with FIGO stage I endometrial cancer is determined by clinicopathological risk factors. In this study, we assessed the potential contribution of pretreatment carcinoembryonic antigen (CEA) and carbohydrate antigen-125 (CA-125) levels to estimating the prognosis of these patients and aimed to develop and validate a prognostic nomogram. This retrospective study included patients with FIGO stage I endometrial cancer who underwent treatment between January 2009 and December 2021 in the four institutes of Chang Gung Memorial Hospital. To identify optimal cutoff values of CEA and CA-125 for predicting survival, receiver operating characteristic (ROC) curves were generated, the Kaplan-Meier method was used to estimate survival, and a Cox regression model was used to analyze the independent prognostic factors. Finally, a nomogram and calibration curve were constructed to predict patient survival probability. Of the 1559 patients evaluated, the optimal cutoff values of CEA and CA-125 were 1.44 ng/mL (area under the ROC curve [AUC] 0.601) and 39.77 U/mL (AUC 0.503), respectively. Multivariate Cox regression analysis showed that pretreatment CEA (hazard ratio [HR] 2.11, 95% confidence interval [95% CI] 1.35-3.28), CA-125 (HR 2.07, 95% CI 1.31-3.27), age >70 years (HR 12.54, 95% CI 5.05-31.11), myometrial invasion >50% (HR 1.69, 95% CI 1.03-2.73), non-endometrioid histology (HR 1.83, 95% CI 1.14-2.95), high-grade tumor (HR 2.41, 95% CI 1.46-3.97), and lymphovascular space invasion (HR 2.32, 95% CI 1.26-4.25) were significant variables associated with overall survival. These factors were used to construct the nomogram model, which showed good concordance and accuracy. Integration of pretreatment CEA and CA-125 in a prognostic nomogram is feasible. Our prediction model has the potential to assist clinicians in guiding appropriate clinical practice.