Risk stratification scores for lymph node metastases in T1 colorectal cancer—A systematic review
Aim Local resection, by an endoscopic or surgical approach, has the potential to completely treat T1 colorectal cancers (CRCs). However, T1 CRCs have a 10% risk of lymph node metastasis (LNM), requiring colonic resection and lymph node dissection. Several high‐risk clinico‐histopathological features...
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Veröffentlicht in: | Colorectal disease 2025-01, Vol.27 (1), p.n/a |
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creator | Quinn, Rakesh Jamsari, Giuleta MacDermid, Ewan |
description | Aim
Local resection, by an endoscopic or surgical approach, has the potential to completely treat T1 colorectal cancers (CRCs). However, T1 CRCs have a 10% risk of lymph node metastasis (LNM), requiring colonic resection and lymph node dissection. Several high‐risk clinico‐histopathological features are associated with LNMs and multiple risk stratification scores have been developed. In this systematic review, we aimed to analyse these scores to identify which is most accurate and clinically useful.
Method
A search of MEDLINE, Cochrane Database of Systematic Review and EMBASE for T1 CRC risk assessment scores was performed following PRISMA guidelines.
Results
Of 323 studies, 22 full texts and three s met the inclusion criteria. Twelve studies developed clinicopathological scores presented as nomograms or algorithms. They used an average of 4.8 (SD ±1.72) parameters, the most utilized being tumour grade, lymphovascular invasion and tumour budding. Two studies incorporated preoperative CT results in their risk score. Artificial intelligence (AI) machine learning models were used for 10 studies, with pathologist‐dependent parameters and pathologist‐independent whole‐slide imaging. The area under the curve (AUC) of the scores ranged from 0.57 to 0.99. Only two scores were externally validated, including a nomogram with an AUC of 0.77 and an AI model with an AUC of 0.83. The generalizability of several scores is limited by using special histopathology tests and AI programming/equipment.
Conclusion
There are several promising risk stratification scores for predicting LNM, particularly with the advent of AI. However, no score adequately stratifies the independent risks of rectal and colonic malignant polyps. Further studies are required to address the heterogeneity and lack of external validation within these nonrandomized trials to provide a more accurate risk stratification of LNMs. |
doi_str_mv | 10.1111/codi.17265 |
format | Article |
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Local resection, by an endoscopic or surgical approach, has the potential to completely treat T1 colorectal cancers (CRCs). However, T1 CRCs have a 10% risk of lymph node metastasis (LNM), requiring colonic resection and lymph node dissection. Several high‐risk clinico‐histopathological features are associated with LNMs and multiple risk stratification scores have been developed. In this systematic review, we aimed to analyse these scores to identify which is most accurate and clinically useful.
Method
A search of MEDLINE, Cochrane Database of Systematic Review and EMBASE for T1 CRC risk assessment scores was performed following PRISMA guidelines.
Results
Of 323 studies, 22 full texts and three s met the inclusion criteria. Twelve studies developed clinicopathological scores presented as nomograms or algorithms. They used an average of 4.8 (SD ±1.72) parameters, the most utilized being tumour grade, lymphovascular invasion and tumour budding. Two studies incorporated preoperative CT results in their risk score. Artificial intelligence (AI) machine learning models were used for 10 studies, with pathologist‐dependent parameters and pathologist‐independent whole‐slide imaging. The area under the curve (AUC) of the scores ranged from 0.57 to 0.99. Only two scores were externally validated, including a nomogram with an AUC of 0.77 and an AI model with an AUC of 0.83. The generalizability of several scores is limited by using special histopathology tests and AI programming/equipment.
Conclusion
There are several promising risk stratification scores for predicting LNM, particularly with the advent of AI. However, no score adequately stratifies the independent risks of rectal and colonic malignant polyps. Further studies are required to address the heterogeneity and lack of external validation within these nonrandomized trials to provide a more accurate risk stratification of LNMs.</description><identifier>ISSN: 1462-8910</identifier><identifier>EISSN: 1463-1318</identifier><identifier>DOI: 10.1111/codi.17265</identifier><language>eng</language><publisher>Chichester: Wiley Subscription Services, Inc</publisher><subject>Artificial intelligence ; Colorectal carcinoma ; colorectal neoplasms ; Lymph nodes ; lymphatic metastasis ; Lymphatic system ; Metastases ; Nomograms ; Polyps ; Reviews ; Risk assessment ; Systematic review ; Tumors</subject><ispartof>Colorectal disease, 2025-01, Vol.27 (1), p.n/a</ispartof><rights>2024 Association of Coloproctology of Great Britain and Ireland.</rights><rights>2025 The Association of Coloproctology of Great Britain and Ireland.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1905-fbced5977f7404e856314eb96a2dd361b6b6c5e8b8c8e742b84b594a59d257183</cites><orcidid>0000-0002-6731-6101 ; 0000-0001-5630-9961 ; 0009-0005-1978-0080</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fcodi.17265$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fcodi.17265$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Quinn, Rakesh</creatorcontrib><creatorcontrib>Jamsari, Giuleta</creatorcontrib><creatorcontrib>MacDermid, Ewan</creatorcontrib><title>Risk stratification scores for lymph node metastases in T1 colorectal cancer—A systematic review</title><title>Colorectal disease</title><description>Aim
Local resection, by an endoscopic or surgical approach, has the potential to completely treat T1 colorectal cancers (CRCs). However, T1 CRCs have a 10% risk of lymph node metastasis (LNM), requiring colonic resection and lymph node dissection. Several high‐risk clinico‐histopathological features are associated with LNMs and multiple risk stratification scores have been developed. In this systematic review, we aimed to analyse these scores to identify which is most accurate and clinically useful.
Method
A search of MEDLINE, Cochrane Database of Systematic Review and EMBASE for T1 CRC risk assessment scores was performed following PRISMA guidelines.
Results
Of 323 studies, 22 full texts and three s met the inclusion criteria. Twelve studies developed clinicopathological scores presented as nomograms or algorithms. They used an average of 4.8 (SD ±1.72) parameters, the most utilized being tumour grade, lymphovascular invasion and tumour budding. Two studies incorporated preoperative CT results in their risk score. Artificial intelligence (AI) machine learning models were used for 10 studies, with pathologist‐dependent parameters and pathologist‐independent whole‐slide imaging. The area under the curve (AUC) of the scores ranged from 0.57 to 0.99. Only two scores were externally validated, including a nomogram with an AUC of 0.77 and an AI model with an AUC of 0.83. The generalizability of several scores is limited by using special histopathology tests and AI programming/equipment.
Conclusion
There are several promising risk stratification scores for predicting LNM, particularly with the advent of AI. However, no score adequately stratifies the independent risks of rectal and colonic malignant polyps. Further studies are required to address the heterogeneity and lack of external validation within these nonrandomized trials to provide a more accurate risk stratification of LNMs.</description><subject>Artificial intelligence</subject><subject>Colorectal carcinoma</subject><subject>colorectal neoplasms</subject><subject>Lymph nodes</subject><subject>lymphatic metastasis</subject><subject>Lymphatic system</subject><subject>Metastases</subject><subject>Nomograms</subject><subject>Polyps</subject><subject>Reviews</subject><subject>Risk assessment</subject><subject>Systematic review</subject><subject>Tumors</subject><issn>1462-8910</issn><issn>1463-1318</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><recordid>eNp9kM1OwzAMxyMEEmNw4QkicUPqiNskTY_T-Jo0aRIa5ypJU5HRNiPpmHrjIXhCnoRs44xl2Zb8sy3_EboGMoFod9pVdgJ5ytkJGgHlWQIZiNNDnSaiAHKOLkJYEwI8BzFC6sWGdxx6L3tbWx2j63DQzpuAa-dxM7SbN9y5yuDW9DJEjx3b4RVg7ZrI6V42WMtOG__z9T3FYQi9aeMijb35tGZ3ic5q2QRz9ZfH6PXxYTV7ThbLp_lsukg0FIQltdKmYkWe1zkl1AjGM6BGFVymVZVxUFxxzYxQQguT01QJqlhBJSuqlMVfsjG6Oe7dePexNaEv127ru3iyzIAVBERKWaRuj5T2LgRv6nLjbSv9UAIp9xqWew3Lg4YRhiO8s40Z_iHL2fJ-fpz5BeK2dZs</recordid><startdate>202501</startdate><enddate>202501</enddate><creator>Quinn, Rakesh</creator><creator>Jamsari, Giuleta</creator><creator>MacDermid, Ewan</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7T5</scope><scope>7TM</scope><scope>7TO</scope><scope>H94</scope><orcidid>https://orcid.org/0000-0002-6731-6101</orcidid><orcidid>https://orcid.org/0000-0001-5630-9961</orcidid><orcidid>https://orcid.org/0009-0005-1978-0080</orcidid></search><sort><creationdate>202501</creationdate><title>Risk stratification scores for lymph node metastases in T1 colorectal cancer—A systematic review</title><author>Quinn, Rakesh ; Jamsari, Giuleta ; MacDermid, Ewan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1905-fbced5977f7404e856314eb96a2dd361b6b6c5e8b8c8e742b84b594a59d257183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Artificial intelligence</topic><topic>Colorectal carcinoma</topic><topic>colorectal neoplasms</topic><topic>Lymph nodes</topic><topic>lymphatic metastasis</topic><topic>Lymphatic system</topic><topic>Metastases</topic><topic>Nomograms</topic><topic>Polyps</topic><topic>Reviews</topic><topic>Risk assessment</topic><topic>Systematic review</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Quinn, Rakesh</creatorcontrib><creatorcontrib>Jamsari, Giuleta</creatorcontrib><creatorcontrib>MacDermid, Ewan</creatorcontrib><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><jtitle>Colorectal disease</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Quinn, Rakesh</au><au>Jamsari, Giuleta</au><au>MacDermid, Ewan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk stratification scores for lymph node metastases in T1 colorectal cancer—A systematic review</atitle><jtitle>Colorectal disease</jtitle><date>2025-01</date><risdate>2025</risdate><volume>27</volume><issue>1</issue><epage>n/a</epage><issn>1462-8910</issn><eissn>1463-1318</eissn><abstract>Aim
Local resection, by an endoscopic or surgical approach, has the potential to completely treat T1 colorectal cancers (CRCs). However, T1 CRCs have a 10% risk of lymph node metastasis (LNM), requiring colonic resection and lymph node dissection. Several high‐risk clinico‐histopathological features are associated with LNMs and multiple risk stratification scores have been developed. In this systematic review, we aimed to analyse these scores to identify which is most accurate and clinically useful.
Method
A search of MEDLINE, Cochrane Database of Systematic Review and EMBASE for T1 CRC risk assessment scores was performed following PRISMA guidelines.
Results
Of 323 studies, 22 full texts and three s met the inclusion criteria. Twelve studies developed clinicopathological scores presented as nomograms or algorithms. They used an average of 4.8 (SD ±1.72) parameters, the most utilized being tumour grade, lymphovascular invasion and tumour budding. Two studies incorporated preoperative CT results in their risk score. Artificial intelligence (AI) machine learning models were used for 10 studies, with pathologist‐dependent parameters and pathologist‐independent whole‐slide imaging. The area under the curve (AUC) of the scores ranged from 0.57 to 0.99. Only two scores were externally validated, including a nomogram with an AUC of 0.77 and an AI model with an AUC of 0.83. The generalizability of several scores is limited by using special histopathology tests and AI programming/equipment.
Conclusion
There are several promising risk stratification scores for predicting LNM, particularly with the advent of AI. However, no score adequately stratifies the independent risks of rectal and colonic malignant polyps. Further studies are required to address the heterogeneity and lack of external validation within these nonrandomized trials to provide a more accurate risk stratification of LNMs.</abstract><cop>Chichester</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1111/codi.17265</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-6731-6101</orcidid><orcidid>https://orcid.org/0000-0001-5630-9961</orcidid><orcidid>https://orcid.org/0009-0005-1978-0080</orcidid></addata></record> |
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subjects | Artificial intelligence Colorectal carcinoma colorectal neoplasms Lymph nodes lymphatic metastasis Lymphatic system Metastases Nomograms Polyps Reviews Risk assessment Systematic review Tumors |
title | Risk stratification scores for lymph node metastases in T1 colorectal cancer—A systematic review |
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