ArticleTranslational cancer research2026
Nomogram for predicting cancer-specific mortality risk in endometrial cancer after postoperative radiotherapy.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Erratum: Nomogram for predicting cancer-specific mortality risk in endometrial cancer after postoperative radiotherapy.Translational cancer research · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Endometrial cancer (EC) incidence keeps rising amid population aging and obesity. This study aimed to investigate independent prognostic factors for the overall survival (OS) and cancer-specific survival (CSS) in postmenopausal EC patients treated with surgery and radiotherapy, and to construct a nomogram to predict survival rate. Methods: We analyzed postmenopausal EC patients who had undergone surgery and radiotherapy between 2010 and 2015, using data from the Surveillance Epidemiology and End Results (SEER) database. The patients were divided into the training and validation cohorts using a ratio of 7:3. Prognostic factors were identified using univariate and multivariate analyses, and a nomogram was developed to predict OS and CSS using Cox proportional hazards and Fine-Gray compete-risk models. We evaluated the nomogram's performance using C-index, receiver operating characteristic (ROC) curve, and calibration plot, and compared it with American Joint Committee on Cancer (AJCC) staging model to assess the impact of surgical modality, radiotherapy modality, chemotherapy or not, and pathological types on OS in different risk stratifications. Results: A total of 10,906 EC patients were enrolled in the study and randomly assigned to the training (n=7,633) and validation (n=3,273) cohorts. The competing risk nomogram finalized 13 prognostic variables including age, tissue type, brain metastasis, lung metastasis, marital status, T-stage, N-stage, stage, grade, radiotherapy modality, tumor size, surgical site, and regional lymphadenectomy. The nomogram showed good performance in predicting CSS with C-indexes of 0.800 and 0.755 for the training and validation sets, respectively. The nomogram performed significantly better than AJCC staging model. In addition to the above variables, the Cox proportional hazards model incorporated bone metastasis, chemotherapy, and the total number of Conclusions: Our study developed and validated a nomogram for predicting OS and CSS in postmenopausal EC patients treated with surgery and radiotherapy. These findings provide valuable insights for individualized risk assessment and treatment decision.
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