Olivia Adair, Felicity Lamrock, James F O'Mahony, Mark Lawler, Ethna McFerran
{"title":"A Comparison of International Modeling Methods for Evaluating Health Economics of Colorectal Cancer Screening: A Systematic Review.","authors":"Olivia Adair, Felicity Lamrock, James F O'Mahony, Mark Lawler, Ethna McFerran","doi":"10.1016/j.jval.2025.01.007","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Cost-effectiveness analysis (CEA) is an accepted approach to evaluate cancer screening programs. CEA estimates partially depend on modeling methods and assumptions used. Understanding common practice when modeling cancer relies on complete, accessible descriptions of prior work. This review's objective is to comprehensively examine published CEA modeling methods used to evaluate colorectal cancer (CRC) screening from an aspiring modeler's perspective. It compares existing models, highlighting the importance of precise modeling method descriptions and essential factors when modeling CRC progression.</p><p><strong>Methods: </strong>MEDLINE, EMBASE, Web of Science, and Scopus electronic databases were used. The Consolidated Health Economic Evaluation Reporting Standards statement and data items from previous systematic reviews formed a template to extract relevant data. Specific focus included model type, natural history, appropriate data sources, and survival analysis.</p><p><strong>Results: </strong>Seventy-eight studies, with 52 unique models were found. Twelve previously published models were reported in 39 studies, with 39 newly developed models. CRC progression from the onset was commonly modeled, with only 6 models not including it as a model component.</p><p><strong>Conclusions: </strong>Modeling methods needed to simulate CRC progression depend on the natural history structure and research requirements. For aspiring modelers, accompanying models with clear overviews and extensive modeling assumption descriptions are beneficial. Open-source modeling would also allow model replicability and result in appropriate decisions suggested for CRC screening programs.</p>","PeriodicalId":23508,"journal":{"name":"Value in Health","volume":" ","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Value in Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jval.2025.01.007","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
A Comparison of International Modeling Methods for Evaluating Health Economics of Colorectal Cancer Screening: A Systematic Review.
Objectives: Cost-effectiveness analysis (CEA) is an accepted approach to evaluate cancer screening programs. CEA estimates partially depend on modeling methods and assumptions used. Understanding common practice when modeling cancer relies on complete, accessible descriptions of prior work. This review's objective is to comprehensively examine published CEA modeling methods used to evaluate colorectal cancer (CRC) screening from an aspiring modeler's perspective. It compares existing models, highlighting the importance of precise modeling method descriptions and essential factors when modeling CRC progression.
Methods: MEDLINE, EMBASE, Web of Science, and Scopus electronic databases were used. The Consolidated Health Economic Evaluation Reporting Standards statement and data items from previous systematic reviews formed a template to extract relevant data. Specific focus included model type, natural history, appropriate data sources, and survival analysis.
Results: Seventy-eight studies, with 52 unique models were found. Twelve previously published models were reported in 39 studies, with 39 newly developed models. CRC progression from the onset was commonly modeled, with only 6 models not including it as a model component.
Conclusions: Modeling methods needed to simulate CRC progression depend on the natural history structure and research requirements. For aspiring modelers, accompanying models with clear overviews and extensive modeling assumption descriptions are beneficial. Open-source modeling would also allow model replicability and result in appropriate decisions suggested for CRC screening programs.
期刊介绍:
Value in Health contains original research articles for pharmacoeconomics, health economics, and outcomes research (clinical, economic, and patient-reported outcomes/preference-based research), as well as conceptual and health policy articles that provide valuable information for health care decision-makers as well as the research community. As the official journal of ISPOR, Value in Health provides a forum for researchers, as well as health care decision-makers to translate outcomes research into health care decisions.