Trial reportSurgical endoscopy2023
The effectiveness of endoscopic ultrasonography findings to distinguish benign and malignant intraductal papillary mucinous neoplasm.
Trial report in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Pancreatic cystic lesions: position paper of the SIRM-AISP multidisciplinary group.La Radiologia medica · 2026Guideline
- Cancer Risk After Initial Surveillance of Intraductal Papillary Mucinous Neoplasms (IPMNs): Are We Missing the Window for Prevention?Annals of surgical oncology · 2026Article
- Value of Endoscopic Ultrasonography for Distinguishing Malignant from Benign Non-pancreatic Periampullary Lesions: An Explainable Machine Learning Study.Digestive diseases and sciences · 2026Article
- Article
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsAccurate evaluation of intraductal papillary mucinous neoplasm (IPMN) is necessary to inform clinical decision-making. But it is still difficult to distinguish benign and malignant IPMN preoperatively. This study aims to evaluate the utility of EUS to predict the pathology of IPMN.
methodsPatients with IPMN who underwent endoscopic ultrasound within 3 months before surgery were collected from six centers. Logistic regression model and random forest model were used to determine risk factors associated with malignant IPMN. In both models, 70% and 30% of patients were randomly assigned to the exploratory group and validation group, respectively. Sensitivity, specificity, and ROC were used in model assessment.
resultsOf the 115 patients, 56 (48.7%) had low-grade dysplasia (LGD), 25 (21.7%) had high-grade dysplasia (HGD), and 34 (29.6%) had invasive cancer (IC). Smoking history (OR = 6.95, 95%CI: 1.98-24.44, p = 0.002), lymphadenopathy (OR = 7.91, 95%CI: 1.60-39.07, p = 0.011), MPD > 7 mm (OR = 4.75, 95%CI: 1.56-14.47, p = 0.006) and mural nodules > 5 mm (OR = 8.79, 95%CI: 2.40-32.24, p = 0.001) were independent risk factors predicting malignant IPMN according to the logistic regression model. The sensitivity, specificity, and AUC were 0.895, 0.571, and 0.795 in the validation group. In the random forest model, the sensitivity, specificity, and AUC were 0.722, 0.823, and 0.773, respectively. In patients with mural nodules, random forest model could reach a sensitivity of 0.905 and a specificity of 0.900.
conclusionsUsing random forest model based on EUS data is effective to differentiate benign and malignant IPMN in this cohort, especially in patients with mural nodules.
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