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Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients
BACKGROUND: Infliximab (IFX) is the first-line treatment for Crohn's disease (CD). However, the secondary loss of response (LOR) is common in IFX therapy. Therefore, non-invasive assessment of LOR in CD patients is the goal pursued by clinicians. METHODS: A multicenter study involving 181 CD pa...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161257/ https://www.ncbi.nlm.nih.gov/pubmed/37151630 http://dx.doi.org/10.1016/j.heliyon.2023.e14594 |
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author | Zhu, Chao Wang, Xingwei Wang, Shihui Hu, Jing Gao, Yankun Li, Cuiping Li, Jianying Wu, Xingwang |
author_facet | Zhu, Chao Wang, Xingwei Wang, Shihui Hu, Jing Gao, Yankun Li, Cuiping Li, Jianying Wu, Xingwang |
author_sort | Zhu, Chao |
collection | PubMed |
description | BACKGROUND: Infliximab (IFX) is the first-line treatment for Crohn's disease (CD). However, the secondary loss of response (LOR) is common in IFX therapy. Therefore, non-invasive assessment of LOR in CD patients is the goal pursued by clinicians. METHODS: A multicenter study involving 181 CD patients was conducted, with patients being split into a training cohort (n = 102), testing cohort (n = 45), and validation cohort (n = 34). The study evaluated various clinical factors to establish a clinical model, and a radiomics signature was constructed based on reproducible features from computed tomography enterography (CTE). Logistic regression modeling was used to create models based on the radiomics signature and significant clinical factors, with the receiver operating characteristic curve (ROC) used to compare their performance. RESULTS: The study found that 64 of the 181 CD patients included experienced secondary LOR. The radiomics signature performed well in predicting secondary LOR, showing good discrimination in the training cohort (AUC [area under the curve], 0.947; 95% confidence interval [CI], 0.910–0.976), the testing cohort (AUC, 0.860; 95% CI, 0.768–0.941), and the validation cohort (AUC, 0.921; 95% CI: 0.831–1.000). Decision curve analysis (DCA) demonstrated the clinical value of the radiomics nomogram. CONCLUSIONS: The CTE-based radiomics model showed good performance in predicting secondary LOR in CD patients. The nomogram can help clinicians choose alternative biologics early for CD patients. |
format | Online Article Text |
id | pubmed-10161257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101612572023-05-06 Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients Zhu, Chao Wang, Xingwei Wang, Shihui Hu, Jing Gao, Yankun Li, Cuiping Li, Jianying Wu, Xingwang Heliyon Research Article BACKGROUND: Infliximab (IFX) is the first-line treatment for Crohn's disease (CD). However, the secondary loss of response (LOR) is common in IFX therapy. Therefore, non-invasive assessment of LOR in CD patients is the goal pursued by clinicians. METHODS: A multicenter study involving 181 CD patients was conducted, with patients being split into a training cohort (n = 102), testing cohort (n = 45), and validation cohort (n = 34). The study evaluated various clinical factors to establish a clinical model, and a radiomics signature was constructed based on reproducible features from computed tomography enterography (CTE). Logistic regression modeling was used to create models based on the radiomics signature and significant clinical factors, with the receiver operating characteristic curve (ROC) used to compare their performance. RESULTS: The study found that 64 of the 181 CD patients included experienced secondary LOR. The radiomics signature performed well in predicting secondary LOR, showing good discrimination in the training cohort (AUC [area under the curve], 0.947; 95% confidence interval [CI], 0.910–0.976), the testing cohort (AUC, 0.860; 95% CI, 0.768–0.941), and the validation cohort (AUC, 0.921; 95% CI: 0.831–1.000). Decision curve analysis (DCA) demonstrated the clinical value of the radiomics nomogram. CONCLUSIONS: The CTE-based radiomics model showed good performance in predicting secondary LOR in CD patients. The nomogram can help clinicians choose alternative biologics early for CD patients. Elsevier 2023-03-18 /pmc/articles/PMC10161257/ /pubmed/37151630 http://dx.doi.org/10.1016/j.heliyon.2023.e14594 Text en © 2023 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Zhu, Chao Wang, Xingwei Wang, Shihui Hu, Jing Gao, Yankun Li, Cuiping Li, Jianying Wu, Xingwang Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients |
title | Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients |
title_full | Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients |
title_fullStr | Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients |
title_full_unstemmed | Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients |
title_short | Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients |
title_sort | development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in crohn's disease patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161257/ https://www.ncbi.nlm.nih.gov/pubmed/37151630 http://dx.doi.org/10.1016/j.heliyon.2023.e14594 |
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