Validation of a novel BCM model for recurrence risk prediction after mucosectomy of colorectal lateral spreading tumors in a European cohort

IF 2.6 4区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Clinics and research in hepatology and gastroenterology Pub Date : 2024-07-05 DOI:10.1016/j.clinre.2024.102414
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Abstract

Background and aim

Piecemeal endoscopic mucosal resection (pEMR) is the best approach to resect large lateral spreading tumors (LST, > 20 mm width). However, it is associated with early recurrence (ER) and late recurrence (LR). This study aims to assess the risk factors associated with ER and LR and to validate different predictive scores (SMSA, SERT, and BCM) in identifying the risk of ER and LR after LST resected by pEMR in a European cohort.

Methods

Retrospective observational cohort study, based on a prospectively collected database, of large LST submitted to pEMR.

Results

A total of 108 patients were included in the study and the incidence rates of ER and LR were 22 % and 8 %, respectively. The lesion's size, SERT, and BCM scores were independent predictor factors of ER (p-value < 0.05), while the lesion's site and BCM score were independent predictor factors of LR (p-value < 0.05). For the prediction of ER, the SERT score (cut-off > 1) presented the highest AUROC (0.758 vs 0.697 from BCM and 0.647 from SMSA). Regarding LR, the BCM model (cut-off > 2) presented the highest AUROC (0.817 vs 0.708 from SERT and 0.691 from SMSA).

Conclusions

We present the first external validation of the three scores mentioned in an European cohort. SERT and BCM scores had an acceptable performance in predicting ER and LR. However, the BCM model was the only score that proved to be an independent predictor of both ER and LR, proving to be valuable for both applications.

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在欧洲队列中验证用于预测结直肠侧向扩散肿瘤黏膜切除术后复发风险的新型 BCM 模型。
背景和目的:片状内镜粘膜切除术(pEMR)是切除大的侧向扩散肿瘤(LST,宽度大于 20 毫米)的最佳方法。然而,它与早期复发(ER)和晚期复发(LR)有关。本研究旨在评估与ER和LR相关的风险因素,并在欧洲队列中验证不同预测评分(SMSA、SERT和BCM)在确定pEMR切除LST后的ER和LR风险方面的作用:方法:基于前瞻性收集的数据库,对接受 pEMR 的大型 LST 进行回顾性队列观察研究:结果:共有108名患者参与研究,ER和LR的发生率分别为22%和8%。病灶大小、SERT和BCM评分是ER的独立预测因素(P值<0.05),而病灶部位和BCM评分是LR的独立预测因素(P值<0.05)。在预测ER方面,SERT评分(临界值>1)的AUROC最高(0.758 vs BCM评分0.697 vs SMSA评分0.647)。在LR方面,BCM模型(临界值大于2)的AUROC最高(0.817 vs SERT评分为0.708,SMSA评分为0.691):我们首次在欧洲队列中对上述三种评分进行了外部验证。SERT和BCM评分在预测ER和LR方面表现尚可。然而,BCM模型是唯一一个能独立预测ER和LR的评分,证明其对这两种应用都有价值。
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来源期刊
CiteScore
4.30
自引率
3.70%
发文量
198
审稿时长
42 days
期刊介绍: Clinics and Research in Hepatology and Gastroenterology publishes high-quality original research papers in the field of hepatology and gastroenterology. The editors put the accent on rapid communication of new research and clinical developments and so called "hot topic" issues. Following a clear Editorial line, besides original articles and case reports, each issue features editorials, commentaries and reviews. The journal encourages research and discussion between all those involved in the specialty on an international level. All articles are peer reviewed by international experts, the articles in press are online and indexed in the international databases (Current Contents, Pubmed, Scopus, Science Direct). Clinics and Research in Hepatology and Gastroenterology is a subscription journal (with optional open access), which allows you to publish your research without any cost to you (unless you proactively chose the open access option). Your article will be available to all researchers around the globe whose institution has a subscription to the journal.
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