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Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study
PURPOSE: Risk assessment of disease recurrence in pT1 colorectal cancer is crucial in order to select the appropriate treatment strategy. The study aimed to develop a prediction model, based on histopathological data, for the probability of disease recurrence and residual disease in patients with pT...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689518/ https://www.ncbi.nlm.nih.gov/pubmed/38036699 http://dx.doi.org/10.1007/s00384-023-04570-y |
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author | Ose, Ilze Levic, Katarina Thygesen, Lau Caspar Bulut, Orhan Bisgaard, Thue Gögenur, Ismail Kuhlmann, Tine Plato |
author_facet | Ose, Ilze Levic, Katarina Thygesen, Lau Caspar Bulut, Orhan Bisgaard, Thue Gögenur, Ismail Kuhlmann, Tine Plato |
author_sort | Ose, Ilze |
collection | PubMed |
description | PURPOSE: Risk assessment of disease recurrence in pT1 colorectal cancer is crucial in order to select the appropriate treatment strategy. The study aimed to develop a prediction model, based on histopathological data, for the probability of disease recurrence and residual disease in patients with pT1 colorectal cancer. METHODS: The model dataset consisted of 558 patients with pT1 CRC who had undergone endoscopic resection only (n = 339) or endoscopic resection followed by subsequent bowel resection (n = 219). Tissue blocks and slides were retrieved from Pathology Departments from all regions in Denmark. All original slides were evaluated by one experienced gastrointestinal pathologist (TPK). New sections were cut and stained for haematoxylin and eosin (HE) and immunohistochemical markers. Missing values were multiple imputed. A logistic regression model with backward elimination was used to construct the prediction model. RESULTS: The final prediction model for disease recurrence demonstrated good performance with AUC of 0.75 [95% CI 0.72–0.78], HL chi-squared test of 0.59 and scaled Brier score of 10%. The final prediction model for residual disease demonstrated medium performance with an AUC of 0.68 [0.63–0.72]. CONCLUSION: We developed a prediction model for the probability of disease recurrence in pT1 CRC with good performance and calibration based on histopathological data. Together with lymphatic and venous invasion, an involved resection margin (0 mm) as opposed to a margin of ≤ 1 mm was an independent risk factor for both disease recurrence and residual disease. |
format | Online Article Text |
id | pubmed-10689518 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-106895182023-12-02 Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study Ose, Ilze Levic, Katarina Thygesen, Lau Caspar Bulut, Orhan Bisgaard, Thue Gögenur, Ismail Kuhlmann, Tine Plato Int J Colorectal Dis Research PURPOSE: Risk assessment of disease recurrence in pT1 colorectal cancer is crucial in order to select the appropriate treatment strategy. The study aimed to develop a prediction model, based on histopathological data, for the probability of disease recurrence and residual disease in patients with pT1 colorectal cancer. METHODS: The model dataset consisted of 558 patients with pT1 CRC who had undergone endoscopic resection only (n = 339) or endoscopic resection followed by subsequent bowel resection (n = 219). Tissue blocks and slides were retrieved from Pathology Departments from all regions in Denmark. All original slides were evaluated by one experienced gastrointestinal pathologist (TPK). New sections were cut and stained for haematoxylin and eosin (HE) and immunohistochemical markers. Missing values were multiple imputed. A logistic regression model with backward elimination was used to construct the prediction model. RESULTS: The final prediction model for disease recurrence demonstrated good performance with AUC of 0.75 [95% CI 0.72–0.78], HL chi-squared test of 0.59 and scaled Brier score of 10%. The final prediction model for residual disease demonstrated medium performance with an AUC of 0.68 [0.63–0.72]. CONCLUSION: We developed a prediction model for the probability of disease recurrence in pT1 CRC with good performance and calibration based on histopathological data. Together with lymphatic and venous invasion, an involved resection margin (0 mm) as opposed to a margin of ≤ 1 mm was an independent risk factor for both disease recurrence and residual disease. Springer Berlin Heidelberg 2023-11-30 2023 /pmc/articles/PMC10689518/ /pubmed/38036699 http://dx.doi.org/10.1007/s00384-023-04570-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/) . |
spellingShingle | Research Ose, Ilze Levic, Katarina Thygesen, Lau Caspar Bulut, Orhan Bisgaard, Thue Gögenur, Ismail Kuhlmann, Tine Plato Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study |
title | Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study |
title_full | Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study |
title_fullStr | Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study |
title_full_unstemmed | Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study |
title_short | Prediction of disease recurrence or residual disease after primary endoscopic resection of pT1 colorectal cancer—results from a large nationwide Danish study |
title_sort | prediction of disease recurrence or residual disease after primary endoscopic resection of pt1 colorectal cancer—results from a large nationwide danish study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10689518/ https://www.ncbi.nlm.nih.gov/pubmed/38036699 http://dx.doi.org/10.1007/s00384-023-04570-y |
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