ArticleJournal of clinical and translational hepatology2022
A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps.
Article in Journal of clinical and translational hepatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 10 citations in OpenAlex.
- Predicting Neoplastic Polyp in Patients With Gallbladder Polyps Using Interpretable Machine Learning Models: Retrospective Cohort Study.Cancer medicine · 2025Article
- Prediction of neoplastic gallbladder polyps in patients with different age level based on preoperative ultrasound: a multi-center retrospective real-world study.BMC gastroenterology · 2024Article
- Advances in the management of gallbladder polyps: establishment of predictive models and the rise of gallbladder-preserving polypectomy procedures.BMC gastroenterology · 2024Review
- Article
- A Bayesian network model to predict neoplastic risk for patients with gallbladder polyps larger than 10 mm based on preoperative ultrasound features.Surgical endoscopy · 2023Article
- A Nomogram-Based Model for Predicting the Risk of Severe Acute Cholangitis Occurrence.International journal of general medicine · 2023Article
- Analysis of Pathogenic Bacteria Distribution and Related Factors in Recurrent Acute Cholangitis.Infection and drug resistance · 2023Article
- Editorial: The use of data mining in radiological-pathological images for personal medicine.Frontiers in genetics · 2023Article
- Diacerein ameliorates acetaminophen hepatotoxicity in rats via inhibiting HMGB1/TLR4/NF-κB and upregulating PPAR-γ signal.Molecular biology reports · 2022Article
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Gallbladder polyp (GBP) assessment aims to identify the early stages of gallbladder carcinoma. Many studies have analyzed the risk factors for malignant GBPs. In this retrospective study, we aimed to establish a more accurate predictive model for potential neoplastic polyps in patients with GBPs. Methods: We developed a nomogram-based model in a training cohort of 233 GBP patients. Clinical information, ultrasonographic findings, and blood test findings were analyzed. Mann-Whitney U test and multivariate logistic regression analyses were used to identify independent predictors and establish the nomogram model. An internal validation was conducted in 225 consecutive patients. Performance and clinical benefit of the model were evaluated using receiver operating characteristic curves and decision curve analysis (DCA), respectively. Results: Age, cholelithiasis, carcinoembryonic antigen, polyp size, and sessile shape were confirmed as independent predictors of GBP neoplastic potential in the training group. Compared with five other proposed prediction methods, the established nomogram model presented better discrimination of neoplastic GBPs in the training cohort (area under the curve [AUC]: 0.846) and the validation cohort (AUC: 0.835). DCA demonstrated that the greatest clinical benefit was provided by the nomogram compared with the other five methods. Conclusions: Our developed preoperative nomogram model can successfully be used to evaluate the neoplastic potential of GBPs based on simple clinical variables that maybe useful for clinical decision-making.
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