A simplified algorithm to evaluate the risk of submucosal invasive cancer in large (>/=20mm) non-pedunculated colonic polyps.


Journal

Endoscopy
ISSN: 1438-8812
Titre abrégé: Endoscopy
Pays: Germany
ID NLM: 0215166

Informations de publication

Date de publication:
06 Mar 2024
Historique:
medline: 7 3 2024
pubmed: 7 3 2024
entrez: 6 3 2024
Statut: aheadofprint

Résumé

Recognition of submucosal invasive cancer (SMIC) in large (20mm) non-pedunculated colonic polyps (LNPCPs) informs selection of the optimal resection strategy. LNPCP location, morphology and size influence the risk of SMIC, however currently no meaningful application of this information has simplified the process to make it accessible and broadly applicable. We developed a decision-making algorithm to simplify the identification of LNPCP subtypes with increased risk of potential SMIC. Patients referred for LNPCP resection from September 2008-November 2022 were enrolled. LNPCPs with SMIC were identified from endoscopic resection specimens, lesion biopsies, or surgical outcomes. Decision tree analysis of lesion characteristics identified in multivariable analysis was used to create a hierarchical classification of SMIC prevalence. 2451 LNPCPs were analysed. 1289 (52.6%) were flat, 1043 (42.6%) nodular and 118 (4.8%) depressed. SMIC was confirmed in 273 (11.1%) of LNPCPs and associated with depressed and nodular versus flat morphology (OR 35.7 CI 22.6-56.5 and 3.5 CI 2.6-4.9, p<0.001 respectively); left versus right colon location (OR 3.2, CI 2.5-4.1, p<0.001); non-granular (NG) versus granular (G) (OR 2.4 CI 1.9-3.1, p<0.001) and size (OR 1.12 per 10mm increase CI 1.05-1.19, p<0.001). Decision tree analysis targeting SMIC identified 8 terminal nodes: SMIC prevalence was 62% in depressed LNPCPs, 19% in nodular left colon LNPCPs and 20% in nodular right colon NG LNPCPs. This decision-making algorithm simplifies identification of LNPCPs with an increased risk of potential SMIC. When combined with surface optical evaluation, it facilitates accurate lesion characterisation and resection choices.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
Recognition of submucosal invasive cancer (SMIC) in large (20mm) non-pedunculated colonic polyps (LNPCPs) informs selection of the optimal resection strategy. LNPCP location, morphology and size influence the risk of SMIC, however currently no meaningful application of this information has simplified the process to make it accessible and broadly applicable. We developed a decision-making algorithm to simplify the identification of LNPCP subtypes with increased risk of potential SMIC.
METHODS METHODS
Patients referred for LNPCP resection from September 2008-November 2022 were enrolled. LNPCPs with SMIC were identified from endoscopic resection specimens, lesion biopsies, or surgical outcomes. Decision tree analysis of lesion characteristics identified in multivariable analysis was used to create a hierarchical classification of SMIC prevalence.
RESULTS RESULTS
2451 LNPCPs were analysed. 1289 (52.6%) were flat, 1043 (42.6%) nodular and 118 (4.8%) depressed. SMIC was confirmed in 273 (11.1%) of LNPCPs and associated with depressed and nodular versus flat morphology (OR 35.7 CI 22.6-56.5 and 3.5 CI 2.6-4.9, p<0.001 respectively); left versus right colon location (OR 3.2, CI 2.5-4.1, p<0.001); non-granular (NG) versus granular (G) (OR 2.4 CI 1.9-3.1, p<0.001) and size (OR 1.12 per 10mm increase CI 1.05-1.19, p<0.001). Decision tree analysis targeting SMIC identified 8 terminal nodes: SMIC prevalence was 62% in depressed LNPCPs, 19% in nodular left colon LNPCPs and 20% in nodular right colon NG LNPCPs.
CONCLUSIONS CONCLUSIONS
This decision-making algorithm simplifies identification of LNPCPs with an increased risk of potential SMIC. When combined with surface optical evaluation, it facilitates accurate lesion characterisation and resection choices.

Identifiants

pubmed: 38447957
doi: 10.1055/a-2282-4794
doi:

Types de publication

Clinical Trial

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Thieme. All rights reserved.

Déclaration de conflit d'intérêts

Michael J Bourke - Research Support: Olympus Medical, Cook Medical, Boston Scientific The remaining authors have no financial, professional, or personal conflicts of interest to disclose

Auteurs

Timothy O'Sullivan (T)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.
Medical School, The University of Sydney Sydney Medical School, Sydney, Australia.

Ana Craciun (A)

Gastroenterology, Westmead Hospital, Sydney, Australia.
Department of Gastroenterology and Hepatology, Centro Hospitalar Universitario de Lisboa Norte, Lisboa, Portugal.

Karen Byth (K)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.

Sunil Gupta (S)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.
Medicine, The University of Sydney Westmead Clinical School, Westmead, Australia.

Julia Louisa Gauci (JL)

Department of Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.

Oliver Cronin (O)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.

Anthony Whitfield (A)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.

Muhammad Abuarisha (M)

Gastroenterology, Westmead Hospital, Sydney, Australia.

Stephen John Williams (SJ)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.

Eric Yong Tat Lee (EYT)

Gastroenterology and Hepatology, Westmead Hospital, Sydney, Australia.

Nicholas Graeme Burgess (NG)

Gastroenterology and Hepatology, Westmead Hospital, Westmead, Australia.
School of Medicine, University of Sydney, Sydney, Australia.

Michael J Bourke (MJ)

Gastroenterology, Westmead Hospital, Sydney, Australia.

Classifications MeSH