跳至主要内容
临床试验/NCT05191095
NCT05191095已完成不适用

The Accuracy of Human Endoscopic Detection of Submucosal Invasive Cancer in Colorectal Polyps - Analysis of 739 Individual Assessments of Large Non-pedunculated Colorectal Polyps Using a Novel Clinical Decision Support Tool

University Hospital, Ghent1 个研究点 分布在 1 个国家目标入组 82 人开始时间: 2021年3月1日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
82
试验地点
1
主要终点
The accuracy of endoscopic assessment as to the risk of SMI within LNPCPs from a standardised endoscopic video, using a novel, freely accessible, web-based simple clinical decision support tool as versus expert opinion.

研究概览

简要总结

Colorectal cancer (CRC) is a leading cause of death in the Western world. It can be effectively prevented by removal of pre-malignant polyps (polypectomy) during colonoscopy. Large (≥20mm) non-pedunculated colorectal polyps (LNPCPs) represent 2-3% of colorectal polyps, and require special attention prior to treatment. If submucosal invasion (SMI) is suspected careful decision making is required to exclude features which unacceptably increase the risk of lymph node metastases and render local treatment (endoscopic) non-curative. Such patients require a multi-disciplinary approach and consideration of surgery +/- systemic therapy.

Recently the endoscopic imaging characteristics which precisely determine the risk of SMI within colon polyps have been elucidated. This suggests endoscopic imaging may be the ideal investigation to stratify the presence and extent of SMI within LNPCP, particularly as it can be applied in real-time at the time of planned endoscopic treatment.

Unfortunately, current classification systems are complex, require extensive training and technology not available in the majority of non-tertiary hospitals. They are therefore underused leading to incorrect decision making and negative patient outcome (e.g piecemeal resection without the chance of endoscopic cure or unnecessary further procedures in referral centres with resultant surgery anyway or surgery for benign disease)

A simple clinical support tool was created, based on well-established parameters (i.e., presence of a demarcated area within a polyp, size of the polyp, Paris classification, location within the colon and granularity) to identify OVERT (visible on the surface) and COVERT (hidden) submucosal invasion (SMI) within LNPCPs. Crucially this tool only uses what is reproducible in the majority of endoscopy units in the Western world (i.e. standard magnification, no extra chromic dyes etc). predict SMI within LNPCPs and we translated it into a single web-based clinical support tool that can be used by every endoscopist (expert and non-expert).

To evaluate the tool, a survey will be send to participants. The survey consist of a 10-minute educational video where the use of the tool will be explained. Then 20 standardised videos of LNPCPs will be shown. Participants are first asked about their first impression regarding the presence of SMI. Then they are redirected to the web-based tool. After filling the required data from a standardised video (45 seconds to minute, no focus on one particular area of the polyp) the score generated by our tool is copied to the participants computer clipboard and then pasted in the survey so that we could analyse it.

研究设计

研究类型
Observational
观察模型
Case Only
时间视角
Prospective

入排标准

性别
All
接受健康志愿者

入选标准

  • Gastrointestinal endoscopic experience (trainees, student, gastroenterologist consult, surgeon)

排除标准

  • No connection with endoscopy in gastroenterology

结局指标

主要结局

The accuracy of endoscopic assessment as to the risk of SMI within LNPCPs from a standardised endoscopic video, using a novel, freely accessible, web-based simple clinical decision support tool as versus expert opinion.

时间窗: 30 minutes

Can participants, using the tool, identify SMI within LNPCPs?

次要结局

  • The inter-observer agreement of a novel simple clinical decision support tool to determine the risk of SMI within LNPCPs from a standardised endoscopic video as versus expert opinion.(30 minutes)

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

Loading locations...

相似试验