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Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model
BACKGROUND: China is a region with a high incidence of tuberculosis, and the incidence of IBD has also been rising rapidly in recent years. Differentiating Crohn’s disease(CD) from intestinal tuberculosis (ITB) has become a very challenging issue. We aimed to develop and assess a diagnostic nomogram...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670453/ https://www.ncbi.nlm.nih.gov/pubmed/36384447 http://dx.doi.org/10.1186/s12876-022-02519-z |
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author | Zeng, Shaoxiong Lin, Ying Guo, Jiaxiang Chen, Xi Liang, Qiong Zhai, Xiaoming Tao, Jin |
author_facet | Zeng, Shaoxiong Lin, Ying Guo, Jiaxiang Chen, Xi Liang, Qiong Zhai, Xiaoming Tao, Jin |
author_sort | Zeng, Shaoxiong |
collection | PubMed |
description | BACKGROUND: China is a region with a high incidence of tuberculosis, and the incidence of IBD has also been rising rapidly in recent years. Differentiating Crohn’s disease(CD) from intestinal tuberculosis (ITB) has become a very challenging issue. We aimed to develop and assess a diagnostic nomogram to differentiate between CD and ITB to improve the accuracy and practicability of the model. METHODS: A total of 133 patients (CD 90 and ITB 43) were analyzed retrospectively. Univariate and multivariate logistic regression analysis was included to determine the independent predictive factors and establish the regression equation. On this basis, the nomogram prediction model was constructed. The discrimination, calibration and clinical efficiency of the nomogram were assessed using area under the curve(AUC), C-index, calibration curve, decision curve analysis (DCA) and clinical impact curve. RESULTS: T-SPOT positive, cobblestone appearance, comb sign and granuloma were significant predictors in differentiating CD from ITB. Base on the above independent predictors, a diagnostic nomogram was successfully established. The sensitivity, specificity, accuracy of the prediction model are 94.4%, 93.0%, 94.0% respectively. The AUC and the C-index of the prediction model are both 0.988, which suggest that the model had a good discrimination power. The calibration curve indicated a high calibration degree of the prediction model. The DCA and clinical impact curve indicated a good clinical efficiency of the prediction model which could bring clinical benefits. CONCLUSION: A nomogram prediction model for distinguishing CD from ITB was developed and assessed, with high discrimination, calibration and clinical efficiency. It can be used as an accurate and convenient diagnostic tool to distinguish CD from ITB, facilitating clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02519-z. |
format | Online Article Text |
id | pubmed-9670453 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-96704532022-11-18 Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model Zeng, Shaoxiong Lin, Ying Guo, Jiaxiang Chen, Xi Liang, Qiong Zhai, Xiaoming Tao, Jin BMC Gastroenterol Research BACKGROUND: China is a region with a high incidence of tuberculosis, and the incidence of IBD has also been rising rapidly in recent years. Differentiating Crohn’s disease(CD) from intestinal tuberculosis (ITB) has become a very challenging issue. We aimed to develop and assess a diagnostic nomogram to differentiate between CD and ITB to improve the accuracy and practicability of the model. METHODS: A total of 133 patients (CD 90 and ITB 43) were analyzed retrospectively. Univariate and multivariate logistic regression analysis was included to determine the independent predictive factors and establish the regression equation. On this basis, the nomogram prediction model was constructed. The discrimination, calibration and clinical efficiency of the nomogram were assessed using area under the curve(AUC), C-index, calibration curve, decision curve analysis (DCA) and clinical impact curve. RESULTS: T-SPOT positive, cobblestone appearance, comb sign and granuloma were significant predictors in differentiating CD from ITB. Base on the above independent predictors, a diagnostic nomogram was successfully established. The sensitivity, specificity, accuracy of the prediction model are 94.4%, 93.0%, 94.0% respectively. The AUC and the C-index of the prediction model are both 0.988, which suggest that the model had a good discrimination power. The calibration curve indicated a high calibration degree of the prediction model. The DCA and clinical impact curve indicated a good clinical efficiency of the prediction model which could bring clinical benefits. CONCLUSION: A nomogram prediction model for distinguishing CD from ITB was developed and assessed, with high discrimination, calibration and clinical efficiency. It can be used as an accurate and convenient diagnostic tool to distinguish CD from ITB, facilitating clinical decision-making. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-022-02519-z. BioMed Central 2022-11-16 /pmc/articles/PMC9670453/ /pubmed/36384447 http://dx.doi.org/10.1186/s12876-022-02519-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Zeng, Shaoxiong Lin, Ying Guo, Jiaxiang Chen, Xi Liang, Qiong Zhai, Xiaoming Tao, Jin Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
title | Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
title_full | Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
title_fullStr | Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
title_full_unstemmed | Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
title_short | Differential diagnosis of Crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
title_sort | differential diagnosis of crohn’s disease and intestinal tuberculosis: development and assessment of a nomogram prediction model |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670453/ https://www.ncbi.nlm.nih.gov/pubmed/36384447 http://dx.doi.org/10.1186/s12876-022-02519-z |
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