用于检测无法切除的肝癌患者高风险静脉曲张的无创模型的开发与验证

IF 11.6 1区 医学 Q1 GASTROENTEROLOGY & HEPATOLOGY
Neehar D Parikh, Patricia Jones, Reena Salgia, Irun Bhan, Lauren T Grinspan, Janice H Jou, Kali Zhou, Prasun Jalal, Giorgio Roccaro, Amol S Rangnekar, Jihane N Benhammou, Anjana Pillai, Neil Mehta, Joel Wedd, Ju Dong Yang, Amy K Kim, Andres Duarte-Rojo, Omobonike O Oloruntoba, Amit Tevar, Jennifer S Au, Yamile Blain, Sanjana Rao, Onofrio A Catalano, Sara Lewis, Mishal Mendiratta-Lala, Kevin King, Lekha Sachdev, Edward W Lee, Jill Bruno, Ihab Kamel, Celestina Tolosa, Karissa Kao, Tarek Badawi, Eric M Przybyszewski, Lisa Quirk, Piyush Nathani, Brandy Haydel, Emily Leven, Nicole Wong, Robert Albertian, Ariana Chen, Fuad Z Aloor, Islam B Mohamed, Ahmed Elkheshen, Charles Marvil, Gerard Issac, Joseph W Clinton, Stephanie M Woo, Jung Yum, Erin Rieger, Alan L Hutchison, Don A Turner, Manaf Alsudaney, Perla Hernandez, Ziyi Xu, Abdullah Khalid, Bethany Barrick, Bo Wang, Elliot B Tapper, Wei Hao, Amit G Singal
{"title":"用于检测无法切除的肝癌患者高风险静脉曲张的无创模型的开发与验证","authors":"Neehar D Parikh, Patricia Jones, Reena Salgia, Irun Bhan, Lauren T Grinspan, Janice H Jou, Kali Zhou, Prasun Jalal, Giorgio Roccaro, Amol S Rangnekar, Jihane N Benhammou, Anjana Pillai, Neil Mehta, Joel Wedd, Ju Dong Yang, Amy K Kim, Andres Duarte-Rojo, Omobonike O Oloruntoba, Amit Tevar, Jennifer S Au, Yamile Blain, Sanjana Rao, Onofrio A Catalano, Sara Lewis, Mishal Mendiratta-Lala, Kevin King, Lekha Sachdev, Edward W Lee, Jill Bruno, Ihab Kamel, Celestina Tolosa, Karissa Kao, Tarek Badawi, Eric M Przybyszewski, Lisa Quirk, Piyush Nathani, Brandy Haydel, Emily Leven, Nicole Wong, Robert Albertian, Ariana Chen, Fuad Z Aloor, Islam B Mohamed, Ahmed Elkheshen, Charles Marvil, Gerard Issac, Joseph W Clinton, Stephanie M Woo, Jung Yum, Erin Rieger, Alan L Hutchison, Don A Turner, Manaf Alsudaney, Perla Hernandez, Ziyi Xu, Abdullah Khalid, Bethany Barrick, Bo Wang, Elliot B Tapper, Wei Hao, Amit G Singal","doi":"10.1016/j.cgh.2024.07.008","DOIUrl":null,"url":null,"abstract":"<p><strong>Background & aims: </strong>Noninvasive variceal risk stratification systems have not been validated in patients with hepatocellular carcinoma (HCC), which presents logistical barriers for patients in the setting of systemic HCC therapy. We aimed to develop and validate a noninvasive algorithm for the prediction of varices in patients with unresectable HCC.</p><p><strong>Methods: </strong>We performed a retrospective cohort study in 21 centers in the United States including adult patients with unresectable HCC and Child-Pugh A5-B7 cirrhosis diagnosed between 2007 and 2019. We included patients who completed an esophagogastroduodonoscopy (EGD) within 12 months of index imaging but before HCC treatment. We divided the cohort into a 70:30 training set and validation set, with the goal of maximizing negative predictive value (NPV) to avoid EGD in low-risk patients.</p><p><strong>Results: </strong>We included 707 patients (median age, 64.6 years; 80.6% male; 74.0% White). Median time from HCC diagnosis to EGD was 47 (interquartile range, 114) days, with 25.0% of patients having high-risk varices. A model using clinical variables alone achieved an NPV of 86.3% in the validation cohort, whereas a model integrating clinical and imaging variables had an NPV 97.4% in validation. The clinical and imaging model would avoid EGDs in more than half of low-risk patients while misclassifying 7.7% of high-risk patients.</p><p><strong>Conclusions: </strong>A model incorporating clinical and imaging data can accurately predict the absence of high-risk varices in patients with HCC and avoid EGD in many low-risk patients before the initiation of systemic therapy, thus expediting their care and avoiding treatment delays.</p>","PeriodicalId":10347,"journal":{"name":"Clinical Gastroenterology and Hepatology","volume":null,"pages":null},"PeriodicalIF":11.6000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development and Validation of a Noninvasive Model for the Detection of High-Risk Varices in Patients with Unresectable HCC.\",\"authors\":\"Neehar D Parikh, Patricia Jones, Reena Salgia, Irun Bhan, Lauren T Grinspan, Janice H Jou, Kali Zhou, Prasun Jalal, Giorgio Roccaro, Amol S Rangnekar, Jihane N Benhammou, Anjana Pillai, Neil Mehta, Joel Wedd, Ju Dong Yang, Amy K Kim, Andres Duarte-Rojo, Omobonike O Oloruntoba, Amit Tevar, Jennifer S Au, Yamile Blain, Sanjana Rao, Onofrio A Catalano, Sara Lewis, Mishal Mendiratta-Lala, Kevin King, Lekha Sachdev, Edward W Lee, Jill Bruno, Ihab Kamel, Celestina Tolosa, Karissa Kao, Tarek Badawi, Eric M Przybyszewski, Lisa Quirk, Piyush Nathani, Brandy Haydel, Emily Leven, Nicole Wong, Robert Albertian, Ariana Chen, Fuad Z Aloor, Islam B Mohamed, Ahmed Elkheshen, Charles Marvil, Gerard Issac, Joseph W Clinton, Stephanie M Woo, Jung Yum, Erin Rieger, Alan L Hutchison, Don A Turner, Manaf Alsudaney, Perla Hernandez, Ziyi Xu, Abdullah Khalid, Bethany Barrick, Bo Wang, Elliot B Tapper, Wei Hao, Amit G Singal\",\"doi\":\"10.1016/j.cgh.2024.07.008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background & aims: </strong>Noninvasive variceal risk stratification systems have not been validated in patients with hepatocellular carcinoma (HCC), which presents logistical barriers for patients in the setting of systemic HCC therapy. We aimed to develop and validate a noninvasive algorithm for the prediction of varices in patients with unresectable HCC.</p><p><strong>Methods: </strong>We performed a retrospective cohort study in 21 centers in the United States including adult patients with unresectable HCC and Child-Pugh A5-B7 cirrhosis diagnosed between 2007 and 2019. We included patients who completed an esophagogastroduodonoscopy (EGD) within 12 months of index imaging but before HCC treatment. We divided the cohort into a 70:30 training set and validation set, with the goal of maximizing negative predictive value (NPV) to avoid EGD in low-risk patients.</p><p><strong>Results: </strong>We included 707 patients (median age, 64.6 years; 80.6% male; 74.0% White). Median time from HCC diagnosis to EGD was 47 (interquartile range, 114) days, with 25.0% of patients having high-risk varices. A model using clinical variables alone achieved an NPV of 86.3% in the validation cohort, whereas a model integrating clinical and imaging variables had an NPV 97.4% in validation. The clinical and imaging model would avoid EGDs in more than half of low-risk patients while misclassifying 7.7% of high-risk patients.</p><p><strong>Conclusions: </strong>A model incorporating clinical and imaging data can accurately predict the absence of high-risk varices in patients with HCC and avoid EGD in many low-risk patients before the initiation of systemic therapy, thus expediting their care and avoiding treatment delays.</p>\",\"PeriodicalId\":10347,\"journal\":{\"name\":\"Clinical Gastroenterology and Hepatology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.6000,\"publicationDate\":\"2024-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Gastroenterology and Hepatology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.cgh.2024.07.008\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Gastroenterology and Hepatology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.cgh.2024.07.008","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

背景和目的:无创静脉曲张风险分层系统尚未在肝细胞癌(HCC)患者中得到验证,这给接受全身性 HCC 治疗的患者带来了后勤障碍。我们的目的是开发并验证一种无创算法,用于预测无法切除的 HCC 患者的静脉曲张:我们在美国 21 个中心开展了一项回顾性队列研究,研究对象包括 2007 年至 2019 年期间确诊的不可切除 HCC 和 Child Pugh A5-B7 肝硬化的成年患者。我们纳入了在指数成像后 12 个月内但在 HCC 治疗前完成食管胃十二指肠镜 (EGD) 检查的患者。我们将队列分为 70:30 的训练集和验证集,目的是最大限度地提高阴性预测值 (NPV),避免低风险患者接受 EGD:我们共纳入了 707 名患者(中位年龄 64.6 岁,80.6% 为男性,74.0% 为白人)。从 HCC 诊断到 EGD 的中位时间为 47 天(IQR:114 天),25.0% 的患者有高风险静脉曲张。在验证队列中,仅使用临床变量的模型的净现值为 86.3%,而整合临床和影像学变量的模型的净现值为 97.4%。临床和成像模型可避免半数以上的低风险患者接受胃肠造影检查,但却误诊了7.7%的高风险患者:结论:结合临床和影像学数据的模型可以准确预测 HCC 患者是否存在高危静脉曲张,并避免许多低危患者在开始系统治疗前接受胃食管造影检查,从而加快患者的治疗,避免治疗延误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and Validation of a Noninvasive Model for the Detection of High-Risk Varices in Patients with Unresectable HCC.

Background & aims: Noninvasive variceal risk stratification systems have not been validated in patients with hepatocellular carcinoma (HCC), which presents logistical barriers for patients in the setting of systemic HCC therapy. We aimed to develop and validate a noninvasive algorithm for the prediction of varices in patients with unresectable HCC.

Methods: We performed a retrospective cohort study in 21 centers in the United States including adult patients with unresectable HCC and Child-Pugh A5-B7 cirrhosis diagnosed between 2007 and 2019. We included patients who completed an esophagogastroduodonoscopy (EGD) within 12 months of index imaging but before HCC treatment. We divided the cohort into a 70:30 training set and validation set, with the goal of maximizing negative predictive value (NPV) to avoid EGD in low-risk patients.

Results: We included 707 patients (median age, 64.6 years; 80.6% male; 74.0% White). Median time from HCC diagnosis to EGD was 47 (interquartile range, 114) days, with 25.0% of patients having high-risk varices. A model using clinical variables alone achieved an NPV of 86.3% in the validation cohort, whereas a model integrating clinical and imaging variables had an NPV 97.4% in validation. The clinical and imaging model would avoid EGDs in more than half of low-risk patients while misclassifying 7.7% of high-risk patients.

Conclusions: A model incorporating clinical and imaging data can accurately predict the absence of high-risk varices in patients with HCC and avoid EGD in many low-risk patients before the initiation of systemic therapy, thus expediting their care and avoiding treatment delays.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
16.90
自引率
4.80%
发文量
903
审稿时长
22 days
期刊介绍: Clinical Gastroenterology and Hepatology (CGH) is dedicated to offering readers a comprehensive exploration of themes in clinical gastroenterology and hepatology. Encompassing diagnostic, endoscopic, interventional, and therapeutic advances, the journal covers areas such as cancer, inflammatory diseases, functional gastrointestinal disorders, nutrition, absorption, and secretion. As a peer-reviewed publication, CGH features original articles and scholarly reviews, ensuring immediate relevance to the practice of gastroenterology and hepatology. Beyond peer-reviewed content, the journal includes invited key reviews and articles on endoscopy/practice-based technology, health-care policy, and practice management. Multimedia elements, including images, video abstracts, and podcasts, enhance the reader's experience. CGH remains actively engaged with its audience through updates and commentary shared via platforms such as Facebook and Twitter.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信