ArticleScientific reports2022
Predictive model for the preoperative assessment and prognostic modeling of lymph node metastasis in endometrial cancer.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.
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16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- The prognostic significance and role of adjuvant therapy for low-volume nodal metastasis in apparent early stage endometrial cancer: an updated systematic review and meta-analysis.Journal of gynecologic oncology · 2025Pooled it
- The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis.Frontiers in oncology · 2023Pooled it
- Predictive models for lymph node metastasis in endometrial cancer: A systematic review and bibliometric analysis.Women's health (London, England)Pooled it
- Preoperative prediction of lymph node metastasis in endometrial carcinoma based on MRI radiomic, clinical, and sonographic features: a clinical dual-center study.Abdominal radiology (New York) · 2026Article
- Development and validation of a prediction model for lymph node metastasis based on molecular typing in clinically early-stage endometrial carcinoma.Journal of gynecologic oncology · 2026Article
- Preoperative clinical predictors of lymph node metastasis in endometrial cancer: a retrospective cohort study.BMC women's health · 2026Article
- A clinically translatable pathomics-based predictive model for preoperative prognostic assessment in patients with endometrial cancer.Discover oncology · 2026Article
- Machine Learning Based Assessment of Inguinal Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Vulva.Journal of clinical medicine · 2025Article
- External validation of CEA and CA125 prediction model for lymph node metastasis in endometrial cancer: A multi-institute cohort study.Cancer biomarkers : section A of Disease markers · 2025Article
- Malignant Peritoneal Cytology Predicts Poor Prognosis and Differential Adjuvant Therapy Benefit in Endometrioid Endometrial Carcinoma: A SEER-Based Propensity Score-Matched Analysis.International journal of women's health · 2025Article
- Fully-connected network-based prediction model for lymph node metastasis in clinical early-stage endometrial cancer: development and validation in two centers.Frontiers in oncology · 2025Article
- Artificial intelligence-assisted magnetic resonance imaging technology in the differential diagnosis and prognosis prediction of endometrial cancer.Scientific reports · 2024Article
- Prognostic significance of lymphovascular space invasion in early-stage low-grade endometrioid endometrial cancer: a fifteen-year retrospective Chinese cohort study.World journal of surgical oncology · 2024Article
- Construction and validation of a clinical risk model based on machine learning for screening characteristic factors of lymphovascular space invasion in endometrial cancer.Scientific reports · 2024Article
- Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows.Journal of clinical medicine · 2023Review
- Microbiology and prognostic prediction model of bloodstream infection in patients with hematological malignancies.Frontiers in cellular and infection microbiology · 2023Article
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Authors and funding
16 authors at 6 institutions in 1 country.
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Abstract
Lymph node metastasis (LNM) is a well-established prognostic factor in endometrial cancer (EC). We aimed to construct a model that predicts LNM and prognosis using preoperative factors such as myometrial invasion (MI), enlarged lymph nodes (LNs), histological grade determined by endometrial biopsy, and serum cancer antigen 125 (CA125) level using two independent cohorts consisting of 254 EC patients. The area under the receiver operating characteristic curve (AUC) of the constructed model was 0.80 regardless of the machine learning techniques. Enlarged LNs and higher serum CA125 levels were more significant in patients with low-grade EC (LGEC) and LNM than in patients without LNM, whereas deep MI and higher CA125 levels were more significant in patients with high-grade EC (HGEC) and LNM than in patients without LNM. The predictive performance of LNM in the HGEC group was higher than that in the LGEC group (AUC = 0.84 and 0.75, respectively). Patients in the group without postoperative pathological LNM and positive LNM prediction had significantly worse relapse-free and overall survival than patients with negative LNM prediction (log-rank test, P < 0.01). This study showed that preoperative clinicopathological factors can predict LNM with high precision and detect patients with poor prognoses. Furthermore, clinicopathological factors associated with LNM were different between HGEC and LGEC patients.
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