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Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)

BACKGROUND: The diagnosis of solid pancreatic lesions is still a thorny problem for clinicians, even endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA) still face problems like false negative. The present study aimed to first establish a model to predict the malignancy in solid pan...

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Autores principales: Wei, Ning, Shi, Rui Hua, Yu, Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797840/
https://www.ncbi.nlm.nih.gov/pubmed/35117289
http://dx.doi.org/10.21037/tcr-20-2208
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author Wei, Ning
Shi, Rui Hua
Yu, Ting
author_facet Wei, Ning
Shi, Rui Hua
Yu, Ting
author_sort Wei, Ning
collection PubMed
description BACKGROUND: The diagnosis of solid pancreatic lesions is still a thorny problem for clinicians, even endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA) still face problems like false negative. The present study aimed to first establish a model to predict the malignancy in solid pancreatic lesions and then explored its validity with atypical diagnostic category diagnosed by cytologists after EUS-FNA. METHODS: Clinical information of 360 cases diagnosed with solid pancreatic lesions between June 2013 and July 2019, and another 20 cases with atypical diagnostic category were collected retrospectively. These cases were divided into group A and group B according to the order of admission. Using the data of group A, multivariate logistic regression analysis was performed to construct a malignancy prediction model which was then verified using group B. Furthermore, the characteristics of the malignancy between the group with atypical diagnostic category and group A were compared in order to evaluate the rationality of the model used in the atypical diagnostic category group, and its predictive ability in these lesions. RESULTS: Multivariate logistic regression analysis revealed that age, density, CA19-9 and carcinoembryonic antigen (CEA) grade, pancreatic duct, swollen lymph nodes, pancreas calcification, and weight loss were independent factors in predicting malignancy (P<0.05). The verification results showed that the area under the receiver operating characteristic (ROC) curve was 0.854±0.042; 95% CI: 0.771–0.936. Univariate analysis showed no significant difference between the malignancy in atypical diagnostic category group and that in group A. For the atypical diagnostic category group, the sensitivity of this model was 83.33%, specificity 100%, positive predictive value (PPV) 100%, negative predictive value (NPV) 40%. CONCLUSIONS: Advanced age, low density of lesions, high CA19-9 and CEA grade, dilatation of pancreatic duct, swollen lymph nodes and weight loss were risk factors for malignancy, while calcification was a protective factor. The model had a relatively high predictive ability on malignancy in both solid pancreatic lesions and atypical diagnostic category group.
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spelling pubmed-87978402022-02-02 Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA) Wei, Ning Shi, Rui Hua Yu, Ting Transl Cancer Res Original Article BACKGROUND: The diagnosis of solid pancreatic lesions is still a thorny problem for clinicians, even endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA) still face problems like false negative. The present study aimed to first establish a model to predict the malignancy in solid pancreatic lesions and then explored its validity with atypical diagnostic category diagnosed by cytologists after EUS-FNA. METHODS: Clinical information of 360 cases diagnosed with solid pancreatic lesions between June 2013 and July 2019, and another 20 cases with atypical diagnostic category were collected retrospectively. These cases were divided into group A and group B according to the order of admission. Using the data of group A, multivariate logistic regression analysis was performed to construct a malignancy prediction model which was then verified using group B. Furthermore, the characteristics of the malignancy between the group with atypical diagnostic category and group A were compared in order to evaluate the rationality of the model used in the atypical diagnostic category group, and its predictive ability in these lesions. RESULTS: Multivariate logistic regression analysis revealed that age, density, CA19-9 and carcinoembryonic antigen (CEA) grade, pancreatic duct, swollen lymph nodes, pancreas calcification, and weight loss were independent factors in predicting malignancy (P<0.05). The verification results showed that the area under the receiver operating characteristic (ROC) curve was 0.854±0.042; 95% CI: 0.771–0.936. Univariate analysis showed no significant difference between the malignancy in atypical diagnostic category group and that in group A. For the atypical diagnostic category group, the sensitivity of this model was 83.33%, specificity 100%, positive predictive value (PPV) 100%, negative predictive value (NPV) 40%. CONCLUSIONS: Advanced age, low density of lesions, high CA19-9 and CEA grade, dilatation of pancreatic duct, swollen lymph nodes and weight loss were risk factors for malignancy, while calcification was a protective factor. The model had a relatively high predictive ability on malignancy in both solid pancreatic lesions and atypical diagnostic category group. AME Publishing Company 2020-11 /pmc/articles/PMC8797840/ /pubmed/35117289 http://dx.doi.org/10.21037/tcr-20-2208 Text en 2020 Translational Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
spellingShingle Original Article
Wei, Ning
Shi, Rui Hua
Yu, Ting
Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)
title Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)
title_full Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)
title_fullStr Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)
title_full_unstemmed Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)
title_short Development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (EUS-FNA)
title_sort development and validation of a clinical prediction model to estimate the probability of malignancy in solid pancreatic lesions and explore its value in the atypical diagnostic category after endoscopic ultrasound-guided fine-needle aspiration biopsy (eus-fna)
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8797840/
https://www.ncbi.nlm.nih.gov/pubmed/35117289
http://dx.doi.org/10.21037/tcr-20-2208
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