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Predicting systemic spread in early colorectal cancer: Can we do better?

Through the implementation of national bowel cancer screening programmes we have seen a three-fold increase in early pT1 colorectal cancers, but how these lesions should be managed is currently unclear. Local excision can be an attractive option, especially for fragile patients with multiple comorbi...

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Detalles Bibliográficos
Autores principales: Brockmoeller, Scarlet Fiona, West, Nicholas Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589731/
https://www.ncbi.nlm.nih.gov/pubmed/31249447
http://dx.doi.org/10.3748/wjg.v25.i23.2887
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author Brockmoeller, Scarlet Fiona
West, Nicholas Paul
author_facet Brockmoeller, Scarlet Fiona
West, Nicholas Paul
author_sort Brockmoeller, Scarlet Fiona
collection PubMed
description Through the implementation of national bowel cancer screening programmes we have seen a three-fold increase in early pT1 colorectal cancers, but how these lesions should be managed is currently unclear. Local excision can be an attractive option, especially for fragile patients with multiple comorbidities, but it is only safe from an oncological point of view in the absence of lymph node metastasis. Patient risk stratification through careful analysis of histopathological features in local excision or polypectomy specimens should be performed according to national guidelines to avoid under- or over-treatment. Currently national guidelines vary in their recommendations as to which factors should be routinely reported and there is no established multivariate risk stratification model to determine which patients should be offered major resectional surgery. Conventional histopathological parameters such as tumour grading or lymphovascular invasion have been shown to be predictive of lymph node metastasis in a number of studies but the inter- and intra-observer variation in reporting is high. Newer parameters including tumour budding and poorly differentiated clusters have been shown to have great potential, but again some improvement in the inter-observer variation is required. With the implementation of digital pathology into clinical practice, quantitative parameters like depth/area of submucosal invasion and proportion of stroma can be routinely assessed. In this review we present the various histopathological risk factors for predicting systemic spread in pT1 colorectal cancer and introduce potential novel quantitative variables and multivariable risk models that could be used to better define the optimal treatment of this increasingly common disease.
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spelling pubmed-65897312019-06-27 Predicting systemic spread in early colorectal cancer: Can we do better? Brockmoeller, Scarlet Fiona West, Nicholas Paul World J Gastroenterol Minireviews Through the implementation of national bowel cancer screening programmes we have seen a three-fold increase in early pT1 colorectal cancers, but how these lesions should be managed is currently unclear. Local excision can be an attractive option, especially for fragile patients with multiple comorbidities, but it is only safe from an oncological point of view in the absence of lymph node metastasis. Patient risk stratification through careful analysis of histopathological features in local excision or polypectomy specimens should be performed according to national guidelines to avoid under- or over-treatment. Currently national guidelines vary in their recommendations as to which factors should be routinely reported and there is no established multivariate risk stratification model to determine which patients should be offered major resectional surgery. Conventional histopathological parameters such as tumour grading or lymphovascular invasion have been shown to be predictive of lymph node metastasis in a number of studies but the inter- and intra-observer variation in reporting is high. Newer parameters including tumour budding and poorly differentiated clusters have been shown to have great potential, but again some improvement in the inter-observer variation is required. With the implementation of digital pathology into clinical practice, quantitative parameters like depth/area of submucosal invasion and proportion of stroma can be routinely assessed. In this review we present the various histopathological risk factors for predicting systemic spread in pT1 colorectal cancer and introduce potential novel quantitative variables and multivariable risk models that could be used to better define the optimal treatment of this increasingly common disease. Baishideng Publishing Group Inc 2019-06-21 2019-06-21 /pmc/articles/PMC6589731/ /pubmed/31249447 http://dx.doi.org/10.3748/wjg.v25.i23.2887 Text en ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial.
spellingShingle Minireviews
Brockmoeller, Scarlet Fiona
West, Nicholas Paul
Predicting systemic spread in early colorectal cancer: Can we do better?
title Predicting systemic spread in early colorectal cancer: Can we do better?
title_full Predicting systemic spread in early colorectal cancer: Can we do better?
title_fullStr Predicting systemic spread in early colorectal cancer: Can we do better?
title_full_unstemmed Predicting systemic spread in early colorectal cancer: Can we do better?
title_short Predicting systemic spread in early colorectal cancer: Can we do better?
title_sort predicting systemic spread in early colorectal cancer: can we do better?
topic Minireviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6589731/
https://www.ncbi.nlm.nih.gov/pubmed/31249447
http://dx.doi.org/10.3748/wjg.v25.i23.2887
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