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Prediction of malignant intraductal papillary mucinous neoplasm: A nomogram based on clinical information and radiological outcomes

Authors :
Xiaorui Huang
Tong Guo
Zhiwei Zhang
Ming Cai
Xinyi Guo
Jingzhao Zhang
Yahong Yu
Source :
Cancer Medicine, Vol 12, Iss 16, Pp 16958-16971 (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract Objective Clinical practitioners face a significant challenge in maintaining a healthy balance between overtreatment and missed diagnosis in the management of intraductal papillary mucinous neoplasm (IPMN). The current study aimed to identify significant risk factors of malignant IPMN from a series of clinical and radiological parameters that are widely available and noninvasive and develop a method to individually predict the risk of malignant IPMN to improve its management. Methods We retrospectively investigated 168 patients who were pathologically diagnosed with IPMN after individualized pancreatic resection between June, 2012 and December, 2020. Independent predictors determined using both univariate and multivariate analyses to construct a predictive model. The discriminatory power of the nomogram was assessed using the area under the receiver operating characteristic curve (AUC). Decision curve analysis was performed to demonstrate the clinical usefulness of the nomogram. Internal cross validation was performed to assess the validity of the predictive model. Results In the multivariate analysis, five significant independent risk factors were identified: increased serum CA19‐9 level, low prognostic nutritional index (PNI), cyst size, enhancing mural nodule, and main pancreatic duct diameter. The nomogram based on the parameters mentioned above had outstanding performance in distinguishing malignancy, with an AUC of 0.907 (95% confidence interval: 0.859–0.956, p

Details

Language :
English
ISSN :
20457634
Volume :
12
Issue :
16
Database :
Directory of Open Access Journals
Journal :
Cancer Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.f1bb45c7e5334d8f866c321680ed1c9e
Document Type :
article
Full Text :
https://doi.org/10.1002/cam4.6326