ArticleCancer medicine2025
Risk Factor and Prediction Model for Malignant Transformation in Pancreatic Intraductal Papillary Mucinous Neoplasm.
Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Risk factor and prediction model for malignant pancreatic intraductal papillary mucinous neoplasm.World journal of surgical oncology · 2026Article
- Risk Factor and Prediction Model for Malignant Transformation in Pancreatic Intraductal Papillary Mucinous Neoplasm.Cancer medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
purposePancreatic intraductal papillary mucinous neoplasms (IPMN) are precursors to pancreatic cancer, with an increasing incidence due to advances in imaging techniques. This study aimed to identify risk factors for malignant transformation in IPMN and develop a predictive model using data from a large medical center in western China.
methodsPatients with IPMN admitted to West China Hospital between January 2010 and February 2022 were included in this study. They were divided into benign and malignant. Characteristic parameters and laboratory results were collected. The training set and test set were randomly divided at a ratio of 7:3. Least absolute shrinkage and selection operator regression was used to select potential prognostic factors. A nomogram was developed by logistic regression. Receiver operating characteristic curves and calibration curves were used to evaluate the model's predictive performance.
resultsWe retrospectively analyzed 182 patients, identifying six independent predictors of malignancy: classification, cyst wall thickening, abrupt changes in main pancreatic duct caliber, maximum tumor diameter, maximum main pancreatic duct diameter, and lnCA19-9. We developed a nomogram with an area under the curve of 0.86 in the training set and 0.81 in the test set. The model showed strong predictive ability, providing a valuable tool for clinicians to guide preoperative decision-making.
conclusionOur study offers the first predictive model for malignant IPMN in western China and highlights the importance of comprehensive risk assessment, incorporating clinical, imaging, and laboratory data.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.