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Nomograms for Predicting Overall and Cancer-Specific Survival Among Second Primary Endometrial Cancer in Primary Colorectal Carcinoma Patients

列线图 医学 子宫内膜癌 肿瘤科 内科学 结直肠癌 接收机工作特性 一致性 癌症 临床终点 临床试验
作者
Linli Liu
出处
期刊:Risk Management and Healthcare Policy [Dove Medical Press]
卷期号:Volume 17: 2959-2970
标识
DOI:10.2147/rmhp.s481880
摘要

Background: Endometrial cancer (EC) is one of the most frequent gynecologic cancers, approximately 20% of patients are regarded as high-risk with poor prognosis. However, more details of patients with second primary endometrial cancer (SPEC) after colorectal cancer (CRC) remain poorly understood. We therefore proposed to construct two nomograms to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates to facilitate clinical application. Methods: A total of 1631 participants were identified in the SEER database from 1973 to 2020. We constructed and validated the nomograms for predicting OS and CSS. The receiver operating characteristic curves, calibration plot, decision curve analysis, C-index, net reclassification improvement, and integrated discrimination improvement were applied to evaluate the predictive performance. Finally, the Prognostic index was calculated and used for risk stratification of Kaplan-Meier survival analysis based on different treatment options. Results: Nomograms of OS and CSS were formulated based on the independent prognostic factors utilizing the training set. The 3- and 5- years of OS nomogram demonstrated good discrimination (AUC = 0.840 and 0.829, respectively), well-calibrated power, and excellent clinical effectiveness. Our nomograms of predicting OS and CSS had a concordance index of 0.801 and 0.866 compared with 0.676 and 0.746 for the AJCC staging system, and more importantly, demonstrated a better forecast accuracy. Chemoradiotherapy displayed a significant survival benefit in the high-risk groups, but proceeding to surgery plus chemotherapy showed a favorable survival for the low groups based on all patients. Conclusion: We developed and internally validated multivariable models that predict OS and CSS risk of SPEC in patients with a CRC to help clinicians make applicable clinical decisions for patients. Keywords: endometrial neoplasms, colorectal carcinoma, nomogram, overall survival, cancer-specific survival

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