Observational studyArchives of gynecology and obstetrics2022
Developing a validated nomogram for predicting ovarian metastasis in endometrial cancer patients: a retrospective research.
Observational study in Archives of gynecology and obstetrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Development and Validation of a Nomogram Based on Metabolic Risk Score for Assessing Lymphovascular Space Invasion in Patients with Endometrial Cancer.International journal of environmental research and public health · 2022Trial
- Efficacy and Safety of Niraparib as First-Line Maintenance Treatment for Patients with Advanced Ovarian Cancer: Real-World Data from a Multicenter Study in China.Targeted oncology · 2023Article
- Comprehensive analysis of novel prognosis-related proteomic signature effectively improve risk stratification and precision treatment for patients with cervical cancer.Archives of gynecology and obstetrics · 2023Article
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Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo explore risk factors and develop a prediction model for ovarian metastasis in endometrial cancer (EC), as well as providing provide a reference for clinical ovarian preservation.
methodsWe conducted a retrospective observational study enrolling 1496 EC patients having received complete staging surgery from Qilu Hospital of Shandong University from 2012 to 2018. These patients were randomly divided into two cohorts: training cohort (n = 1046) and validation cohort (n = 448). A nomogram prediction model was developed based on univariate, least absolute shrinkage and selection operator (Lasso), and multivariate logistic regression. Then, the nomogram model's performance was evaluated in discrimination, calibration, and clinical utility three aspects.
resultsParametrium invasion, lymph node metastasis, and oviduct metastasis were finally contained in the nomogram prediction model. The AUC of the model in the training cohort was 0.85 compared with 0.72 in the validation cohort. It also behaved well in calibration and had good clinical utility. With a threshold probability of 20% ~ 80%, the nomogram increased the net benefit by 0 ~ 13.6 per 100 patients than surgery for all patients upon validation.
conclusionsWe develop a nomogram with good performances for predicting ovarian metastasis in EC patients, which may help clinicians identify candidate patients appropriate for ovarian preservation in premenopausal EC patients.
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