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Thiruvengadam NR, Gupta S, Buller S, Awad I, Gandhi D, Ibarra A, Latorre G, Riquelme A, Kochman ML, Cote G, Shah SC, Saumoy M. The Clinical Impact and Cost-Effectiveness of Surveillance of Incidentally Detected Gastric Intestinal Metaplasia: A Microsimulation Analysis. Clin Gastroenterol Hepatol 2024; 22:51-61. [PMID: 37302442 DOI: 10.1016/j.cgh.2023.05.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 05/23/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023]
Abstract
BACKGROUND & AIMS Gastric intestinal metaplasia (GIM) is associated with a higher risk of noncardia intestinal gastric adenocarcinoma (GA). The aim of this study was to estimate lifetime benefits, complications, and cost-effectiveness of GIM surveillance using esophagogastroduodenoscopy (EGD). METHODS We developed a semi-Markov microsimulation model of patients with incidentally detected GIM, to compare the effectiveness of EGD surveillance with no surveillance at 10-year, 5-year, 3-year, 2-year, and 1-year intervals. We modeled a simulated cohort of 1,000,000 US individuals aged 50 with incidental GIM. Outcome measures were lifetime GA incidence, mortality, number of EGDs, complications, undiscounted life-years gained, and incremental cost-effectiveness ratio with a willingness-to-pay threshold of $100,000/quality-adjusted life-year (QALY). RESULTS In the absence of surveillance, the model simulated 32.0 lifetime GA cases and 23.0 lifetime GA deaths per 1000 individuals with GIM, respectively. Among surveilled individuals, simulated lifetime GA incidence (per 1000) decreased with shorter surveillance intervals (10-year to 1-year, 11.2-6.1) as did GA mortality (7.4-3.6). Compared with no surveillance, all modeled surveillance intervals yielded greater life expectancy (87-190 undiscounted life-years gained per 1000); 5-year surveillance provided the greatest number of life-years gained per EGD performed and was the cost-effective strategy ($40,706/QALY). In individuals with risk factors of family history of GA or anatomically extensive, incomplete-type GIM intensified 3-year surveillance was cost-effective (incremental cost-effectiveness ratio $28,156/QALY and $87,020/QALY, respectively). CONCLUSIONS Using microsimulation modeling, surveillance of incidentally detected GIM every 5 years is associated with reduced GA incidence/mortality and is cost-effective from a health care sector perspective. Real-world studies evaluating the impact of GIM surveillance on GA incidence and mortality in the United States are needed.
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Affiliation(s)
- Nikhil R Thiruvengadam
- Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California.
| | - Shashank Gupta
- Department of Medicine, Loma Linda University Health, Loma Linda, California
| | - Seth Buller
- Loma Linda University School of Medicine, Loma Linda, California
| | - Imad Awad
- Department of Medicine, Loma Linda University Health, Loma Linda, California
| | - Devika Gandhi
- Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Allison Ibarra
- Division of Gastroenterology, University of California San Diego, San Diego, California
| | - Gonzalo Latorre
- Department of Gastroenterology, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Arnoldo Riquelme
- Department of Gastroenterology, Faculty of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile; Centro para la Prevención y el Control del Cáncer (CECAN), Santiago, Chile
| | - Michael L Kochman
- Division of Gastroenterology and Hepatology, Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Gregory Cote
- Division of Gastroenterology and Hepatology, Oregon Health & Science University, Portland, Oregon
| | - Shailja C Shah
- Division of Gastroenterology, University of California San Diego, San Diego, California; Gastroenterology Section, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Monica Saumoy
- Center for Digestive Health, Penn Medicine Princeton Medical Center, Plainsboro, New Jersey
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Li H, Zhang S, Zhou J, Tong F, Gong J, Zha Z, Li N, Xia C, Li J, Zheng L, Luo P, Han R, Ma H, Lv Y, Zeng H, Zheng R, Cao M, Yang F, Yan X, Sun D, He S, Zhang S, Chen W, He J. Endoscopic Surveillance for Premalignant Esophageal Lesions: A Community-Based Multicenter, Prospective Cohort Study. Clin Gastroenterol Hepatol 2023; 21:653-662.e8. [PMID: 35623589 DOI: 10.1016/j.cgh.2022.04.039] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 04/19/2022] [Accepted: 04/21/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Mild and moderate dysplasia are major premalignant lesions of esophageal squamous cell carcinoma (ESCC); however, evidence of the progression risk in patients with these conditions is extremely limited. We aimed to assess the incidence and risk factors for advanced neoplasia in patients with mild-moderate dysplasia. METHODS This prospective cohort study included patients with mild-moderate dysplasia from 9 regions in rural China. These patients were identified from a community-based ESCC screening program conducted between 2010 and 2016 and were offered endoscopic surveillance until December 2021. We estimated the incidence of advanced esophageal neoplasia, including severe dysplasia, carcinoma in situ, or ESCC, and identified potential risk factors using the Cox regression model. RESULTS The 1183 patients with mild-moderate dysplasia were followed up over a period of 6.95 years. During follow-up evaluation, 88 patients progressed to advanced neoplasia (7.44%), with an incidence rate of 10.44 per 1000 person-years. The median interval from the progression of mild-moderate dysplasia to advanced neoplasia was 2.39 years (interquartile range, 1.58-4.32 y). A total of 74.47% of patients with mild-moderate dysplasia experienced regression to nondysplasia, and 18.09% showed no lesion progression. Patients with mild-moderate dysplasia who had a family history of esophageal cancer and were age 55 years and older showed 97% higher advanced neoplasia yields than all patients with mild-moderate dysplasia. CONCLUSIONS In a country with a high incidence of ESCC, patients with mild-moderate dysplasia showed an overall risk of advanced neoplasia progression of 1.04% per year. Patients with mild-moderate dysplasia would be recommended for endoscopic surveillance during the first 2 to 3 years.
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Affiliation(s)
- He Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China
| | - Jinyi Zhou
- Department for Chronic Non-communicable Diseases Control, Jiangsu Provincial Center for Disease Control and Prevention (Public Health Research Institute of Jiangsu Province), Nanjing, China
| | - Feng Tong
- Department of Preventive Management, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Jiyong Gong
- Department of Preventive Management, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Zhenqiu Zha
- Institute of Chronic Non-communicable Diseases Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Changfa Xia
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Jiang Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Liyang Zheng
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Henan Engineering Research Center of Cancer Prevention and Control, Henan International Joint Laboratory of Cancer Prevention, Zhengzhou, China
| | - Pengfei Luo
- Department for Chronic Non-communicable Diseases Control, Jiangsu Provincial Center for Disease Control and Prevention (Public Health Research Institute of Jiangsu Province), Nanjing, China
| | - Renqing Han
- Department for Chronic Non-communicable Diseases Control, Jiangsu Provincial Center for Disease Control and Prevention (Public Health Research Institute of Jiangsu Province), Nanjing, China
| | - Hengmin Ma
- Department of Preventive Management, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Yili Lv
- Institute of Chronic Non-communicable Diseases Prevention and Control, Anhui Provincial Center for Disease Control and Prevention, Hefei, China
| | - Hongmei Zeng
- Office of Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Rongshou Zheng
- Office of Cancer Registry, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
| | - Maomao Cao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Fan Yang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Xinxin Yan
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Dianqin Sun
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Siyi He
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Shaoli Zhang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China
| | - Wanqing Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College/Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Beijing, China.
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
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