Clinicopathological characterization and prognostic risk modeling in patients with synchronous ovarian and endometrial cancer: a population-based study

同步性卵巢癌和子宫内膜癌患者的临床病理特征及预后风险模型:一项基于人群的研究

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Abstract

INTRODUCTION: Ovarian cancer (OC) and endometrial cancer (EC) represent two prevalent tumors within the female reproductive system, characterized by high incidence rates. Nonetheless, the clinicopathological features of synchronous endometrial and ovarian cancer (SEOC) have received limited research attention. The present study endeavors to identify prognostic factors for SEOC through a comparative analysis of survival outcomes between SEOC and single-primary OC patients. METHOD: Clinical data (2010-2015) were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were diagnosed with OC as their first primary tumor and EC as their second primary tumor. Survival outcomes were estimated utilizing Kaplan-Meier survival curves and subsequently compared via the log-rank test. Using Cox proportional hazards models to identify independent prognostic factors. The prognostic model predicted malignancy-specific mortality, evaluated by c-index, calibration, receiver operating characteristic (ROC), and area under the ROC curve (AUC). RESULTS: A total of 447 SEOC patients and 20 769 single-primary OC patients were enrolled in this study. The dual-primary group exhibited more survival benefits compared to the single-primary group. This study identified key independent prognostic factors for SEOC, including age, marital status, histological type, tumor size, SEER stage, and AJCC (American Joint Committee on Cancer) stage. The predictive model demonstrated strong discriminatory capability, with AUC values of 0.880, 0.872, and 0.872 for predicting 1-, 2-, and 3-year specific mortality. Calibration curves confirmed a high level of concordance between observed and predicted outcomes, underscoring the model's reliability. CONCLUSION: These findings provide critical insights into improving prognosis evaluation and formulating individualized treatment strategies for SEOC patients.

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