Digestion最新文献

{"title":"Efficacy and Safety of Etrasimod in Patients with Ulcerative Colitis in Japan: Data from the Phase 3 ELEVATE UC 12 and ELEVATE UC 40 JAPAN Trials.","authors":"Ken Takeuchi, Tadakazu Hisamatsu, Hiroshi Nakase, Katsuyoshi Matsuoka, Michael Keating, Hirotoshi Yuasa, Motoki Oe, Shoko Arai, Rafal Mazur, Toshifumi Hibi","doi":"10.1159/000541383","DOIUrl":"10.1159/000541383","url":null,"abstract":"<p><strong>Introduction: </strong>Etrasimod is an oral, once-daily (QD), selective sphingosine 1-phosphate (S1P)1,4,5 receptor modulator for the treatment of moderately to severely active ulcerative colitis (UC). Here, we report the primary analysis of a phase 3 trial evaluating the efficacy and safety of etrasimod in patients from Japan with moderately to severely active UC.</p><p><strong>Methods: </strong>Patients from Japan who completed the 12-week ELEVATE UC 12 induction trial could enroll in the 40-week ELEVATE UC 40 JAPAN maintenance trial for a combined 52-week treatment period. Patients in this Japan cohort continued their baseline assigned treatment (etrasimod 2 mg QD or placebo) from ELEVATE UC 12. Efficacy was assessed at week 12 and week 52. Treatment-emergent adverse events (TEAEs) pooled from both trials were assessed up to 52 weeks of exposure.</p><p><strong>Results: </strong>The Japan cohort comprised 32 and 16 patients who received etrasimod and placebo, respectively. A numerically greater proportion of patients who received etrasimod versus placebo achieved clinical remission at week 12 (etrasimod: 14.3%; placebo: 7.1%) and week 52 (etrasimod: 25.0%; placebo: 7.1%); a similar trend was observed for all key secondary efficacy endpoints. TEAEs occurred in 84.4% (27/32) and 62.5% (10/16) of patients who received etrasimod and placebo, respectively. No new safety signals were detected.</p><p><strong>Conclusion: </strong>In these induction and maintenance trials evaluating etrasimod in patients from Japan with UC, numerically higher proportions of patients who received etrasimod versus placebo achieved efficacy endpoints. Efficacy and safety findings were consistent with those from the global ELEVATE UC trial populations.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"167-175"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12129419/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning-Based Detection of Malignant Bile Duct Stenosis in Fluoroscopy Images of Endoscopic Retrograde Cholangiopancreatography.","authors":"Kien Vu Trung, Marcus Hollenbach, Gregory Patrick Veldhuizen, Oliver Lester Saldanha, Jakob Garbe, Jonas Rosendahl, Sebastian Krug, Patrick Michl, Jürgen Feisthammel, Thomas Karlas, Jochen Hampe, Albrecht Hoffmeister, Jakob Nikolas Kather","doi":"10.1159/000543049","DOIUrl":"10.1159/000543049","url":null,"abstract":"<p><strong>Introduction: </strong>The accurate distinction between benign and malignant biliary strictures (BSs) poses a significant challenge. Despite the use of bile duct biopsies and brush cytology via endoscopic retrograde cholangiopancreaticography (ERCP), the results remain suboptimal. Single-operator cholangioscopy can enhance the diagnostic yield in BS, but its limited availability and high costs are substantial barriers. Convolutional neural network-based systems may improve the diagnostic process and enhance reproducibility. Therefore, we assessed the feasibility of using deep learning to differentiate BS using fluoroscopy images during ERCP.</p><p><strong>Methods: </strong>We conducted a retrospective review of adult patients (n = 251) from three university centers in Germany (Leipzig, Dresden, Halle) who underwent ERCP. We developed and evaluated a deep learning-based model using fluoroscopy images. The performance of the classifier was evaluated by measuring the area under the receiver operating characteristic curve (AUROC), and we utilized saliency map analyses to understand the decision-making process of the model.</p><p><strong>Results: </strong>In cross-validation experiments, malignant BSs were detected with a mean AUROC of 0.89 ± 0.03. The test set of the Leipzig cohort demonstrated an AUROC of 0.90. In two independent external validation cohorts (Dresden, Halle), the deep learning-based classifier achieved an AUROC of 0.72 and 0.76, respectively. The artificial intelligence model's predictions identified plausible characteristics within the fluoroscopy images.</p><p><strong>Conclusion: </strong>By using a deep learning model, we were able to discriminate malignant BS from benign biliary conditions. The application of artificial intelligence enhances the diagnostic yield of malignant BS and should be validated in a prospective design.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"287-302"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12324797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Endoscopic Resection for Colorectal Tumors.","authors":"Yuichiro Hirai, Naoya Toyoshima, Yutaka Saito","doi":"10.1159/000541605","DOIUrl":"10.1159/000541605","url":null,"abstract":"<p><strong>Background: </strong>Endoscopic resection techniques for colorectal tumors are constantly evolving with improvements.</p><p><strong>Summary: </strong>Over the past decade, there has been a paradigm shift toward cold polypectomy for the removal of small lesions (<10 mm), known as the \"cold revolution\". In recent years, underwater endoscopic mucosal resection (EMR) has emerged as an alternative to conventional EMR and has been gaining popularity for resection of intermediate and large-sized lesions (≥10 mm). Although colorectal endoscopic submucosal dissection (ESD) requires a high level of advanced skills, improvements in dissection techniques and devices have facilitated the procedure. In Japan, the safety and efficacy of ESD for resecting large lesions (≥20 mm) have been demonstrated in a large-scale, multicenter, prospective cohort study (CREATE-J). ESD is also being increasingly adopted in Western countries. As endoscopic resection continues to advance and include large and more complex defects, a variety of closure techniques and new devices are being developed. Meanwhile, the number of endoscopic resections for T1-colorectal cancer (T1-CRC), including those intended for total excisional biopsy, has been increasing owing to the aging population and improvements in endoscopic technique.</p><p><strong>Key messages: </strong>This review provides a broad summary of endoscopic resection for colorectal tumors including advancements in closure techniques and devices for mucosal defects, as well as the potential role of endoscopic resection for patients with T1-CRC.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"115-121"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142575600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Interpretation of Magnifying Endoscopy for the Diagnosis of Colorectal Lesions.","authors":"Naohisa Yoshida, Ken Inoue, Elsayed Ghoneem, Yoshikazu Inagaki, Reo Kobayashi, Naoto Iwai, Osamu Dohi, Ryohei Hirose, Yoshito Itoh","doi":"10.1159/000543996","DOIUrl":"10.1159/000543996","url":null,"abstract":"<p><strong>Background: </strong>Accurate endoscopic diagnosis is crucial for determining the appropriate treatment strategy for colorectal lesions, which may include cold snare polypectomy, endoscopic mucosal resection, or endoscopic submucosal dissection.</p><p><strong>Summary: </strong>While white light imaging (WLI) serves as the basic and initial method for endoscopic diagnosis, additional techniques such as narrow band imaging (NBI), blue laser/light imaging (BLI), and magnified observation of pit patterns are necessary when WLI results are inconclusive. These advanced diagnostic methods enable precise differentiation of lesions such as adenoma, T1 cancer, and sessile serrated lesion. Furthermore, recent advancements in endoscopic systems have enhanced image clarity and detail, thereby improving diagnostic accuracy.</p><p><strong>Key messages: </strong>This review provides an in-depth discussion on how magnified endoscopy, utilizing the Japan NBI Expert Team (JNET) classification with NBI/BLI and pit pattern classification with chromoendoscopy, aids in the accurate diagnosis of colorectal lesions.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"107-114"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143188489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Machine Learning Algorithms to Screen for Advanced Liver Fibrosis in Metabolic Dysfunction-Associated Steatotic Liver Disease: An In-Depth Explanatory Analysis.","authors":"Shoham Dabbah, Itamar Mishani, Yana Davidov, Ziv Ben Ari","doi":"10.1159/000542241","DOIUrl":"10.1159/000542241","url":null,"abstract":"<p><strong>Introduction: </strong>This study aimed to train machine learning algorithms (MLAs) to detect advanced fibrosis (AF) in metabolic dysfunction-associated steatotic liver disease (MASLD) patients at the level of primary care setting and to explain the predictions to ensure responsible use by clinicians.</p><p><strong>Methods: </strong>Readily available features of 618 MASLD patients followed up at a tertiary center were used to train five MLAs. AF was defined as liver stiffness ≥9.3 kPa, measured via 2-dimension shear wave elastography (n = 495) or liver biopsy ≥F3 (n = 123). MLAs were compared to Fibrosis-4 index (FIB-4) and non-alcoholic fatty liver disease (NAFLD) fibrosis score (NFS) on 540 MASLD patients from the primary care setting as validation. Feature importance, partial dependence, and shapely additive explanations (SHAPs) were utilized for explanation.</p><p><strong>Results: </strong>Extreme gradient boosting (XGBoost) achieved an AUC = 0.91, outperforming FIB-4 (AUC = 0.78) and NFS (AUC = 0.81, both p < 0.05) with specificity = 76% versus 59% and 48% for FIB-4 ≥1.3 and NFS ≥-1.45, respectively (p < 0.05). Its sensitivity (91%) was superior to FIB-4 (79%). XGBoost confidently excluded AF (negative predictive value = 99%) with the highest positive predictive value (31%), superior to FIB-4 and NFS (all p < 0.05). The most important features were HbA1c and gamma glutamyl transpeptidase (GGT) with a steep increase in AF probability at HbA1c >6.5%. The strongest interaction was between AST and age. XGBoost, but not logistic regression, extracted informative patterns from ALT, low-density lipoprotein cholesterol, and alkaline phosphatase (p < 0.001). One-quarter of the false positives (FPs) were correctly reclassified with only one additional false negative based on the SHAP values of GGT, platelets, and ALT which were found to be associated with a FP classification.</p><p><strong>Conclusions: </strong>An explainable XGBoost algorithm was demonstrated superior to FIB-4 and NFS for screening of AF in MASLD patients at the primary care setting. The algorithm also proved safe for use as clinicians can understand the predictions and flag FP classifications.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"189-202"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12129435/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142497008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Endocuff Vision-Assisted Colonoscopy Significantly Improves Adenoma Detection in a Shorter Withdrawal Time Compared with Standard Colonoscopy: A Randomized Controlled Trial.","authors":"Duc Trong Quach, Thu Anh Nguyen, Mai Ngoc Luu, Uyen Pham-Phuong Vo, Vy Ly-Thao Tran, Truc Le-Thanh Tran, Tai Duy Nguyen, Nhan Quang Le, Toru Hiyama, Shinji Tanaka","doi":"10.1159/000543630","DOIUrl":"10.1159/000543630","url":null,"abstract":"<p><strong>Introduction: </strong>Although several studies in Western countries have shown that Endocuff Vision-assisted colonoscopy (EC) can improve the colorectal adenoma detection rate (ADR), such evidence in Asia is still scarce. This study aimed to evaluate the performance of EC in detecting colorectal adenomas in Vietnamese patients.</p><p><strong>Methods: </strong>This was a randomized controlled trial conducted at a tertiary hospital in Vietnam. Subjects aged ≥18 years referred for colonoscopy for symptomatic investigation or screening were randomly assigned to the EC group or standard colonoscopy (SC) group. The primary outcome was the ADR. The secondary outcomes included the mean number of adenomas per procedure (MAP), cecal intubation time, and withdrawal time.</p><p><strong>Results: </strong>There were 476 participants (241 in the EC group, 235 in the SC group) with a median age of 52 (interquartile range [IR]: 46, 58) years. There were no significant differences between the two groups regarding age, sex, smoking status, family history of colorectal cancer, or indications for colonoscopy. Compared with the SC group, the EC group had significantly higher ADRs (35.7% vs. 22.6%, p = 0.002) and MAPs (0.68 vs. 0.39, p = 0.004). The intubation durations were comparable between the two groups. The withdrawal time in the EC group was shorter than that in the SC group (median [seconds]: 266 [IR: 224, 314] vs. 360 [IR: 310, 390], p < 0.001).</p><p><strong>Conclusions: </strong>Compared with SC, EC significantly increased both the ADR and MAP in a shorter inspection time and could be a better choice for colonoscopy screening.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"327-337"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143002056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current Status of Artificial Intelligence Use in Colonoscopy.","authors":"Masashi Misawa, Shin-Ei Kudo","doi":"10.1159/000543345","DOIUrl":"10.1159/000543345","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) has significantly impacted medical imaging, particularly in gastrointestinal endoscopy. Computer-aided detection and diagnosis systems (CADe and CADx) are thought to enhance the quality of colonoscopy procedures.</p><p><strong>Summary: </strong>Colonoscopy is essential for colorectal cancer screening but often misses a significant percentage of adenomas. AI-assisted systems employing deep learning offer improved detection and differentiation of colorectal polyps, potentially increasing adenoma detection rates by 8%-10%. The main benefit of CADe is in detecting small adenomas, whereas it has a limited impact on advanced neoplasm detection. Recent advancements include real-time CADe systems and CADx for histopathological predictions, aiding in the differentiation of neoplastic and nonneoplastic lesions. Biases such as the Hawthorne effect and potential overdiagnosis necessitate large-scale clinical trials to validate the long-term benefits of AI. Additionally, novel concepts such as computer-aided quality improvement systems are emerging to address limitations facing current CADe systems.</p><p><strong>Key messages: </strong>Despite the potential of AI for enhancing colonoscopy outcomes, its effectiveness in reducing colorectal cancer incidence and mortality remains unproven. Further prospective studies are essential to establish the overall utility and clinical benefits of AI in colonoscopy.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"138-145"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of a Protease Inhibitor Camostat Mesilate on Gut Microbial Function in Patients with Irritable Bowel Syndrome: A Pilot Randomized Placebo-Controlled Study.","authors":"Motoyori Kanazawa, Kentaro Miyamoto, Michiko Kano, Kyoko Inooka, Kentaro Oka, Motomichi Takahashi, Nariyasu Mano, Shin Fukudo","doi":"10.1159/000542758","DOIUrl":"10.1159/000542758","url":null,"abstract":"<p><strong>Introduction: </strong>Increased fecal protease activity, which may induce visceral hypersensitivity, has been observed in patients with irritable bowel syndrome (IBS). Serine proteases modulate FK506 binding protein (FKBP)-type peptidylprolyl cis-trans isomerase (PPIase) activity associated with immune and glucocorticoid receptor functions. The aim was to investigate whether camostat mesilate (CM), a serine protease inhibitor, modifies fecal bacterial function related to FKBP-type PPIases in patients with IBS.</p><p><strong>Methods: </strong>Randomly assigned 16 patients with IBS received 200 mg po tid of CM and 16 patients received placebo for 14 days. Self-reported adequate relief (AR) as a primary endpoint, IBS Symptom Severity Scale (IBS-SSS), and colonic motor and pain thresholds to colorectal distention were assessed before and after treatment. The fecal bacterial content was inferred from 16S rRNA gene sequence data using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States and the Kyoto Encyclopedia of Genes and Genomes database.</p><p><strong>Results: </strong>CM significantly increased the relative abundance of Streptococcus and the functional abundances of serine protease and FKBP-type PPIase FkpA, FklB and SlyD more than placebo after treatment. CM treatment was not superior to placebo in proportion of AR although colonic motor response partially changed.</p><p><strong>Conclusion: </strong>CM modulated the fecal microbiome composition and functional potentials that are related to FKBP-type PPIase activity in IBS patients. These findings suggest that protease inhibitors may modify gut microbial function along with abnormal immunological and/or stress responses that underlie pathophysiology of IBS.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"265-276"},"PeriodicalIF":3.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12324801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence for Contrast-Enhanced Ultrasound of the Liver: A Systematic Review.","authors":"James A Brooks, Michael Kallenbach, Iuliana-Pompilia Radu, Annalisa Berzigotti, Christoph F Dietrich, Jakob N Kather, Tom Luedde, Tobias P Seraphin","doi":"10.1159/000541540","DOIUrl":"10.1159/000541540","url":null,"abstract":"<p><strong>Introduction: </strong>The research field of artificial intelligence (AI) in medicine and especially in gastroenterology is rapidly progressing with the first AI tools entering routine clinical practice, for example, in colorectal cancer screening. Contrast-enhanced ultrasound (CEUS) is a highly reliable, low-risk, and low-cost diagnostic modality for the examination of the liver. However, doctors need many years of training and experience to master this technique and, despite all efforts to standardize CEUS, it is often believed to contain significant interrater variability. As has been shown for endoscopy, AI holds promise to support examiners at all training levels in their decision-making and efficiency.</p><p><strong>Methods: </strong>In this systematic review, we analyzed and compared original research studies applying AI methods to CEUS examinations of the liver published between January 2010 and February 2024. We performed a structured literature search on PubMed, Web of Science, and IEEE. Two independent reviewers screened the articles and subsequently extracted relevant methodological features, e.g., cohort size, validation process, machine learning algorithm used, and indicative performance measures from the included articles.</p><p><strong>Results: </strong>We included 41 studies with most applying AI methods for classification tasks related to focal liver lesions. These included distinguishing benign versus malignant or classifying the entity itself, while a few studies tried to classify tumor grading, microvascular invasion status, or response to transcatheter arterial chemoembolization directly from CEUS. Some articles tried to segment or detect focal liver lesions, while others aimed to predict survival and recurrence after ablation. The majority (25/41) of studies used hand-picked and/or annotated images as data input to their models. We observed mostly good to high reported model performances with accuracies ranging between 58.6% and 98.9%, while noticing a general lack of external validation.</p><p><strong>Conclusion: </strong>Even though multiple proof-of-concept studies for the application of AI methods to CEUS examinations of the liver exist and report high performance, more prospective, externally validated, and multicenter research is needed to bring such algorithms from desk to bedside.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"227-244"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12129427/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142307299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of Invasion Depth of Early Colorectal Cancer Using Endoscopic Ultrasonography and Magnifying Chromoendoscopy: A Meta-Analysis.","authors":"Runhua Chen, Yafang Huang, Fusheng Liu","doi":"10.1159/000542620","DOIUrl":"10.1159/000542620","url":null,"abstract":"<p><strong>Introduction: </strong>Magnifying chromoendoscopy (MCE) and endoscopic ultrasonography (EUS) are often used as diagnostic tools to estimate the depth of invasion in early colorectal cancers (CRCs). The aim of this study was to compare MCE with EUS in distinguishing between slight submucosal invasion (invasion depth <1,000 μm) and massively submucosal invasion in patients with early CRCs, since slight submucosal invasion is currently considered as an indication for endoscopic resection and submucosal cancer with massively submucosal invasion should be surgically treated due to an increased risk of lymph node metastasis.</p><p><strong>Methods: </strong>For this meta-analysis, relevant studies were identified from PubMed, Embase, and the Cochrane Library databases between the time of the establishment and April 2023. Data on the yield of tumors were extracted, pooled, and analyzed by STATA15.0 software. The sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio in differentiating massive submucosal invasion from slight submucosal invasion were calculated for both diagnostic modalities.</p><p><strong>Results: </strong>Twenty-six studies involving 12,586 lesions were included: sixteen were studies on MCE and 7 were studies on EUS and 3 were studies on both MCE and EUS. The pooled sensitivity of MCE was 0.78 (95% CI 0.72-0.83), the specificity was 0.95 (0.95% CI 0.91-0.97), the positive likelihood ratio was 15.4 (0.95% CI 8.7-27.4), and the negative likelihood ratio was 0.23 (0.95% CI 0.18-0.30). The pooled sensitivity of EUS was 0.88 (95% CI 0.81-0.93), the specificity was 0.87 (0.95% CI 0.80-0.91), the positive likelihood ratio was 6.7 (0.95% CI 4.4-10.3), and the negative likelihood ratio was 0.13 (0.95% CI 0.08-0.23).</p><p><strong>Conclusion: </strong>The sensitivity tended to be higher in EUS than MCE for early CRCs with massively submucosal invasion, whereas the specificity was significantly lower in EUS than in MCE.</p>","PeriodicalId":11315,"journal":{"name":"Digestion","volume":" ","pages":"245-264"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142738788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}