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World J Gastroenterol. Nov 21, 2026; 32(43): 122311
Published online Nov 21, 2026. doi: 10.3748/wjg.122311
Modelling the impact of colorectal cancer screening strategies: A systematic review and meta-analysis
Yi-Ke Yan, Yue-Lun Zhang, Bin Lu, Zhi-Liang He, Xin-Ran Cheng, Kai Song, Yu-Qing Chen, Jing-Jing Han, Hong-Da Chen, Min Dai
Yi-Ke Yan, Yue-Lun Zhang, Bin Lu, Zhi-Liang He, Xin-Ran Cheng, Yu-Qing Chen, Hong-Da Chen, Center for Prevention and Early Intervention, National Infrastructures for Translational Medicine, Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
Yi-Ke Yan, Bin Lu, Zhi-Liang He, Min Dai, Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, China
Bin Lu, Center for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 101118, China
Kai Song, Department of Gastroenterology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100730, China
Jing-Jing Han, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
Co-first authors: Yi-Ke Yan and Yue-Lun Zhang.
Co-corresponding authors: Hong-Da Chen and Min Dai.
Author contributions: Dai M and Chen HD contributed equally to this work as co-corresponding authors; they supervised the study, contributed to the interpretation of findings, critically revised the manuscript, and approved the final version. Yan YK, Zhang YL, Lu B and He ZL contributed equally to this work as co-first authors; they made substantial intellectual contributions to the conception and design of the study, data extraction, data analysis and interpretation, and manuscript preparation. Specifically, Yan YK, Lu B and He ZL conducted data extraction; Yan YK performed data analysis and drafted the initial manuscript; Zhang YL and Lu B provided methodological support and contributed to manuscript revision; Cheng XR, Song K, Chen YQ and Han JJ verified the data. All authors reviewed and approved the final version of the manuscript.
AI contribution statement: ASReview, an open-source machine learning tool, was used during title and abstract screening solely to prioritize records by predicted relevance; all eligibility decisions were made by the authors. During manuscript preparation, GPT-5 (OpenAI, San Francisco, CA, United States) was used solely for linguistic refinement, grammar correction, formatting assistance, and improvement of clarity and readability. No AI tool was involved in the generation of research data, interpretation of results, or formulation of conclusions. All AI-generated outputs were critically reviewed and revised by the authors.
Supported by Capital’s Funds for Health Improvement and Research (CFH), No. 2026-2G-4026; PUMCH Talent Development and Support Program (Category B), No. UGG06641; National Key Research and Development Project of China, No. 2024YFA0918501; the National Natural Science Foundation of China, No. 82273726 and No. 82473705; Beijing Research Ward Excellence Program, No. BRWEP2024W034010101; the Fundamental Research Funds for the Central Universities, Peking Union Medical College, No. 3332025126; and the Science and Technology Planning Project of Tibet Autonomous Region, No. XZ202501JD0021.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Corresponding author: Hong-Da Chen, Professor, Center for Prevention and Early Intervention, National Infrastructures for Translational Medicine, Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing 100730, China.
chenhongda@pumch.cn
Received: April 16, 2026
Revised: May 13, 2026
Accepted: June 26, 2026
Published online: November 21, 2026
Processing time: 164 Days and 4.8 Hours
BACKGROUND
Long-term trial evidence on the benefits of colorectal cancer (CRC) screening, particularly for novel or hybrid strategies, remains scarce. Simulation models have been developed to address questions unfeasible for trials.
AIM
To synthesize model-based evidence on the long-term impact of CRC screening strategies.
METHODS
We systematically searched PubMed, EMBASE, and Web of Science for studies published between January 1, 2014, and March 3, 2025. Eligible studies were modelling studies evaluating CRC screening strategies in average-risk populations, focusing on CRC incidence, CRC-specific mortality, and all-cause mortality; screening-related harms and colonoscopy resource requirements were beyond the scope of the quantitative synthesis. Pooled risk ratios (RRs) were estimated using random-effects models, with subgroup analyses by model structure, natural history, and country. Cost-effectiveness evidence was synthesized qualitatively.
RESULTS
We included 102 eligible studies, assessing seven common strategies, ten emerging test-based strategies, and four hybrid strategies. All common strategies significantly reduced CRC burden compared to no screening, with 10-yearly colonoscopy achieving the greatest reductions (RR, 0.23; 95%CI: 0.19-0.28 for incidence; RR, 0.17; 95%CI: 0.14-0.21 for mortality) under perfect adherence. Emerging strategies, such as artificial intelligence-assisted colonoscopy, showed promising reductions in CRC burden in limited model-based analyses. Four hybrid screening strategies also demonstrated high efficacy. Adherence significantly influenced outcomes and specific model contributed to heterogeneity. Most common screening strategies were reported as cost-effective compared to no screening, while certain novel screening strategies were not cost-effective at current prices.
CONCLUSION
Novel and hybrid strategies may have the potential to reduce CRC burden. Real-world participation and model choice influence projected outcomes and should be considered in policy and practice.
Core Tip: This meta-analysis of modeling studies shows that colorectal cancer screening substantially reduces incidence and mortality, with 10-yearly colonoscopy being most effective under perfect adherence. Emerging and hybrid strategies appear promising but with uncertain cost-effectiveness. Outcomes are strongly influenced by adherence and modelling assumptions, highlighting the need to balance effectiveness, real-world implementation, and economic considerations in screening policy decisions.
