Background: To determine the factors related to overall survival (OS) and progression-free survival (PFS) in endometrial carcinoma (EC) patients. Methods: A retrospective cohort study of 906 EC patients was conducted at Shengjing Hospital, China Medical University. Baseline information about the patients, tumor characteristics, and data on five serum biomarkers (CA125, CA19-9, CA72-4, CEA, and AFP) were collected. Groups and their survival rates were compared using log-rank tests and Kaplan-Meier analysis, respectively. Hazard ratios (HRs) and 95% confidence intervals (CIs) were determined using univariate or multivariate Cox proportional hazard models. The outcome measures used were OS, defined as the time between surgery and death or last follow-up for surviving patients, and PFS, defined as the time from the completion of initial surgery to either first progression, disease recurrence, or death. Results: Multivariate analysis showed lower PFS associated with age ≥ 66 years (P < 0.001), non-endometrioid histology (P = 0.015), low degree of tumor differentiation (P = 0.004), and FIGO stage III & IV (P = 0.002). Elevated CA125 (P = 0.042) and AFP (P = 0.016) were identified as independent biomarkers for PFS. Increased CA125 (P = 0.013), age ≥ 66 years (P < 0.001), non-endometrioid histology (P＜0.001), and FIGO stage III & IV (P = 0.015) were independent factors associated with OS. Analysis of the CA125 sub-group showed that individuals with elevated CA125 andAFP (P = 0.049) had significantly lower PFS. Conclusion: This study suggests that CA125 and AFP are prognostic biomarkers for EC

Objective: To investigate the clinical value of serological biomarkers (white blood cell count [WBC], neutrophil/lymphocyte ratio [NLR], prealbumin [PA], platelet distribution width [PDW], mean platelet volume [MPV], CA125,and D-dimer) to diagnose ruptured ovarian endometrioma and construct a prediction model. Design: Case-control study Setting:Single-center Population:Seven hundred and eighty-five women diagnosed with ruptured (n=181) and unruptured ovarian endometrioma (n=604) between January 2011 and December 2021. Methods:The differences in serological biomarkers (WBC, NLR, PA, PDW, MPV, CA125, and D-dimer) between the two groups were analyzed using logistic univariate analysis to select independent variables. Biomarkers with statistically significant differences were included in a logistic multivariate analysis to construct a regression model and thereby predict ruptured ovarian endometrioma. Operating characteristic (ROC) curves were used to evaluate the diagnostic value of the predictive model. Main outcome measures:serological biomarkers (WBC, NLR, PA, PDW, MPV, CA125,and D-dimer in ruptured ovarian endometrioma. Results: Univariate analysis revealed that WBC, NLR, PA, PDW, MPV, CA125,and D-dimer levels were correlated with ovarian endometrioma rupture (P<0.05). The optimal cut-off values were determined using the ROC curves,and multivariate analysis showed that WBC>7.81×109/L, NLR>2.65, PDW>15.55fL,MPV<9.50fL, PA<0.189g/L,CA125>94.63U/mL, and D-dimer>195.5ug/L were independent predictors of ovarian endometrioma rupture. The area under the curve(AUC) of the model was 0.983.The sensitivity and specificity of the predictive model were high (93.4% and 96.4%,respectively). Conclusion:WBC,NLR, PA, PDW, MPV,CA125,and D-dimer can be used to facilitate early identification of ruptured ovarian endometrioma and early intervention. The diagnostic model established in this study is of great importance for diagnosing ruptured endometriotic cysts.