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A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps
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 p...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
XIA & HE Publishing Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039700/ https://www.ncbi.nlm.nih.gov/pubmed/35528981 http://dx.doi.org/10.14218/JCTH.2021.00078 |
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author | Zhang, Xudong Wang, Jincheng Wu, Baoqiang Li, Tao Jin, Lei Wu, Yong Gao, Peng Zhang, Zhen Qin, Xihu Zhu, Chunfu |
author_facet | Zhang, Xudong Wang, Jincheng Wu, Baoqiang Li, Tao Jin, Lei Wu, Yong Gao, Peng Zhang, Zhen Qin, Xihu Zhu, Chunfu |
author_sort | Zhang, Xudong |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9039700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | XIA & HE Publishing Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90397002022-05-06 A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps Zhang, Xudong Wang, Jincheng Wu, Baoqiang Li, Tao Jin, Lei Wu, Yong Gao, Peng Zhang, Zhen Qin, Xihu Zhu, Chunfu J Clin Transl Hepatol Original Article 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. XIA & HE Publishing Inc. 2022-04-28 2021-06-30 /pmc/articles/PMC9039700/ /pubmed/35528981 http://dx.doi.org/10.14218/JCTH.2021.00078 Text en © 2022 Authors. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Zhang, Xudong Wang, Jincheng Wu, Baoqiang Li, Tao Jin, Lei Wu, Yong Gao, Peng Zhang, Zhen Qin, Xihu Zhu, Chunfu A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps |
title | A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps |
title_full | A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps |
title_fullStr | A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps |
title_full_unstemmed | A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps |
title_short | A Nomogram-based Model to Predict Neoplastic Risk for Patients with Gallbladder Polyps |
title_sort | nomogram-based model to predict neoplastic risk for patients with gallbladder polyps |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039700/ https://www.ncbi.nlm.nih.gov/pubmed/35528981 http://dx.doi.org/10.14218/JCTH.2021.00078 |
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