ArticleCancer management and research2021
Development and Validation of a Novel Prognostic Model for Endometrial Cancer Based on Clinical Characteristics.
Article in Cancer management and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Preoperative risk stratification in endometrial carcinoma: a pragmatic, complementary nomogram using readily available clinical variables.Frontiers in oncology · 2026Article
- Development and Validation of a Prognostic Nomogram for Endometrial Cancer Based on Systemic Immune-Inflammation Index and Key Clinicopathological Features.Cancer management and research · 2026Article
- New online dynamic nomograms to predict recurrence-free and overall survival after resection of endometrial cancer: a single-institution retrospective cohort study.Archives of gynecology and obstetrics · 2024Article
- Endometrial carcinoma: association between mutational status, sites of metastasis, recurrence, and correlation with overall survival.Abdominal radiology (New York) · 2023Article
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7 authors.
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Abstract
objectiveExisting prognostic models for endometrial cancer are short of facility and effective validation. In this study, we aim to develop and validate a novel prognostic model for endometrial cancer based on clinical characteristics.
methodsThe clinical data such as age, BMI (body mass index), FIGO stage, surgical approach, myometrial invasion, grade, lymph node metastasis, pathology and menopause status were collected for constructing and validating the prognostic model from The Cancer Genome Atlas (TCGA) and Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, respectively. COX regression and the least absolute shrinkage and selection operator (LASSO) COX were applied to identify the significant predictors of overall survival (OS) and construct the prognostic model. The discrimination, calibration, and clinical usefulness of the model were evaluated in both cohorts.
resultsThree hundred and sixty-seven and 286 EC patients were collected for training and validation cohort, respectively. A clinical prognostic model integrating six clinical variables including age, BMI, FIGO stage, surgical approach, myometrial invasion and grade was established. K-M analysis shows a significant difference between the low- and high-risk groups. The area under the receiver operating characteristic curve (AUC-ROC) was 0.775 (95% CI, 0.708 to 0.843) and 0.870 (95% CI, 0.758 to 0.982) for the training and validation cohorts which indicating reliable discrimination. The calibration curve revealed excellent predictive accuracy and the Hosmer-Lemeshow test also verified this. Decision curve analysis (DCA) for the prognostic model indicated that it would add more benefits than either the detect-all-patients scheme or the detect-none scheme. In addition, our model has a superior AUC comparing with any single factor as predicting OS.
conclusionOur predictive model offers a convenient and accurate tool for clinicians to estimate the prognosis of EC patients.
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