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Fu Y, Li H, Xu A, Yang Z, Zhang P, Wang W. Cost-effectiveness analysis of sequential two-step screening versus direct colonoscopy screening for colorectal cancer: a large-scale survey in Eastern China. Front Oncol 2025; 15:1524172. [PMID: 40027136 PMCID: PMC11867945 DOI: 10.3389/fonc.2025.1524172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2024] [Accepted: 01/27/2025] [Indexed: 03/05/2025] Open
Abstract
Objectives Despite the implementation of colorectal cancer (CRC) screening programs in many regions worldwide over the past few decades, the cost-effectiveness of these programs has been questioned owing to their acceptance rates. In this study, we evaluated the cost-effectiveness of screening strategies, quantified the impact of colonoscopy acceptance rates, and analyzed the underlying factors driving individual preferences. Methods The cost-effectiveness of three strategies-no screening, sequential two-step screening (fecal immunochemical test and risk assessment, followed by colonoscopy), and colonoscopy screening-was evaluated from a societal perspective. This assessment was conducted using a decision-tree Markov model with the incremental cost-effectiveness ratio as the primary evaluation criterion. Results Sequential screening was more cost-effective than colonoscopy screening (19,335 vs. 27,379 United States dollars per quality-adjusted life year). Ideal sequential screening could prevent 32.2%(691/2147) CRC deaths, whereas colonoscopy screening at the same colonoscopy acceptance rate (20.3%) could prevent 17.6%(377/2147) CRC deaths. When the acceptance rate of direct colonoscopy surpasses the threshold of 37.2%, the resulting health benefits likely outweigh those achieved using a the sequential two-step screening approach. Conclusions Sequential screening is recommended for individuals in areas with constrained screening resources or during the early stages of regional screening program implementation. However, once screening habits are established, transitioning to direct colonoscopy screening becomes more favorable. Notably, reducing colonoscopy costs is the principal factor for enhancing an individual's willingness to undergo the procedure.
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Affiliation(s)
- Yun Fu
- Huzhou Center for Disease Control and Prevention, Huzhou, Zhejiang, China
| | - Hao Li
- Zhongshan Hospital Affiliated to Fudan University, Shanghai, China
| | - Ao Xu
- School of Public Health, Fudan University, Shanghai, China
| | - Zhongrong Yang
- Huzhou Center for Disease Control and Prevention, Huzhou, Zhejiang, China
| | - Peng Zhang
- Huzhou Center for Disease Control and Prevention, Huzhou, Zhejiang, China
| | - Weibing Wang
- School of Public Health, Fudan University, Shanghai, China
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Jia X, Shen Y, Yang J, Song R, Zhang W, Meng MQH, Liao JC, Xing L. PolypMixNet: Enhancing semi-supervised polyp segmentation with polyp-aware augmentation. Comput Biol Med 2024; 170:108006. [PMID: 38325216 DOI: 10.1016/j.compbiomed.2024.108006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 12/29/2023] [Accepted: 01/13/2024] [Indexed: 02/09/2024]
Abstract
BACKGROUND AI-assisted polyp segmentation in colonoscopy plays a crucial role in enabling prompt diagnosis and treatment of colorectal cancer. However, the lack of sufficient annotated data poses a significant challenge for supervised learning approaches. Existing semi-supervised learning methods also suffer from performance degradation, mainly due to task-specific characteristics, such as class imbalance in polyp segmentation. PURPOSE The purpose of this work is to develop an effective semi-supervised learning framework for accurate polyp segmentation in colonoscopy, addressing limited annotated data and class imbalance challenges. METHODS We proposed PolypMixNet, a semi-supervised framework, for colorectal polyp segmentation, utilizing novel augmentation techniques and a Mean Teacher architecture to improve model performance. PolypMixNet introduces the polyp-aware mixup (PolypMix) algorithm and incorporates dual-level consistency regularization. PolypMix addresses the class imbalance in colonoscopy datasets and enhances the diversity of training data. By performing a polyp-aware mixup on unlabeled samples, it generates mixed images with polyp context along with their artificial labels. A polyp-directed soft pseudo-labeling (PDSPL) mechanism was proposed to generate high-quality pseudo labels and eliminate the dilution of lesion features caused by mixup operations. To ensure consistency in the training phase, we introduce the PolypMix prediction consistency (PMPC) loss and PolypMix attention consistency (PMAC) loss, enforcing consistency at both image and feature levels. Code is available at https://github.com/YChienHung/PolypMix. RESULTS PolypMixNet was evaluated on four public colonoscopy datasets, achieving 88.97% Dice and 88.85% mIoU on the benchmark dataset of Kvasir-SEG. In scenarios where the labeled training data is limited to 15%, PolypMixNet outperforms the state-of-the-art semi-supervised approaches with a 2.88-point improvement in Dice. It also shows the ability to reach performance comparable to the fully supervised counterpart. Additionally, we conducted extensive ablation studies to validate the effectiveness of each module and highlight the superiority of our proposed approach. CONCLUSION PolypMixNet effectively addresses the challenges posed by limited annotated data and unbalanced class distributions in polyp segmentation. By leveraging unlabeled data and incorporating novel augmentation and consistency regularization techniques, our method achieves state-of-the-art performance. We believe that the insights and contributions presented in this work will pave the way for further advancements in semi-supervised polyp segmentation and inspire future research in the medical imaging domain.
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Affiliation(s)
- Xiao Jia
- School of Control Science and Engineering, Shandong University, Jinan, China.
| | - Yutian Shen
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China.
| | - Jianhong Yang
- School of Control Science and Engineering, Shandong University, Jinan, China.
| | - Ran Song
- School of Control Science and Engineering, Shandong University, Jinan, China.
| | - Wei Zhang
- School of Control Science and Engineering, Shandong University, Jinan, China.
| | - Max Q-H Meng
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China.
| | - Joseph C Liao
- Department of Urology, Stanford University, Stanford, 94305, CA, USA; VA Palo Alto Health Care System, Palo Alto, 94304, CA, USA.
| | - Lei Xing
- Department of Radiation Oncology, Stanford University, Stanford, 94305, CA, USA.
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Monahan KJ, Davies MM, Abulafi M, Banerjea A, Nicholson BD, Arasaradnam R, Barker N, Benton S, Booth R, Burling D, Carten RV, D'Souza N, East JE, Kleijnen J, Machesney M, Pettman M, Pipe J, Saker L, Sharp L, Stephenson J, Steele RJ. Faecal immunochemical testing (FIT) in patients with signs or symptoms of suspected colorectal cancer (CRC): a joint guideline from the Association of Coloproctology of Great Britain and Ireland (ACPGBI) and the British Society of Gastroenterology (BSG). Gut 2022; 71:gutjnl-2022-327985. [PMID: 35820780 PMCID: PMC9484376 DOI: 10.1136/gutjnl-2022-327985] [Citation(s) in RCA: 68] [Impact Index Per Article: 22.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 07/01/2022] [Indexed: 12/12/2022]
Abstract
Faecal immunochemical testing (FIT) has a high sensitivity for the detection of colorectal cancer (CRC). In a symptomatic population FIT may identify those patients who require colorectal investigation with the highest priority. FIT offers considerable advantages over the use of symptoms alone, as an objective measure of risk with a vastly superior positive predictive value for CRC, while conversely identifying a truly low risk cohort of patients. The aim of this guideline was to provide a clear strategy for the use of FIT in the diagnostic pathway of people with signs or symptoms of a suspected diagnosis of CRC. The guideline was jointly developed by the Association of Coloproctology of Great Britain and Ireland/British Society of Gastroenterology, specifically by a 21-member multidisciplinary guideline development group (GDG). A systematic review of 13 535 publications was undertaken to develop 23 evidence and expert opinion-based recommendations for the triage of people with symptoms of a suspected CRC diagnosis in primary care. In order to achieve consensus among a broad group of key stakeholders, we completed an extended Delphi of the GDG, and also 61 other individuals across the UK and Ireland, including by members of the public, charities and primary and secondary care. Seventeen research recommendations were also prioritised to inform clinical management.
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Affiliation(s)
- Kevin J Monahan
- The Wolfson Endoscopy Unit, Gastroenterology Department, St Mark's Hospital and Academic Institute, Harrow, London, UK
- Faculty of Medicine, Department of Surgery & Cancer, Imperial College, London, UK
| | - Michael M Davies
- Department of Colorectal Surgery, University Hospital of Wales, Cardiff, UK
| | - Muti Abulafi
- Colorectal Surgery, Croydon Health Services NHS Trust, Croydon, Greater London, UK
| | - Ayan Banerjea
- Nottingham Colorectal Service, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Brian D Nicholson
- Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Ramesh Arasaradnam
- University of Warwick, Clinical Sciences Research Institute, Coventry, UK
- Gastroenterology Department, University Hospital Coventry, Coventry, UK
| | | | - Sally Benton
- Hub Director, NHS Bowel Cancer Screening South of England Hub, Royal Surrey County Hospital NHS Foundation Trust, Guildford, Surrey, UK
| | - Richard Booth
- Colorectal Surgery, Croydon University Hospital, Croydon, UK
| | - David Burling
- Radiology, St Mark's Hospital and Academic Institute, Harrow, London, UK
| | | | | | - James Edward East
- Translational Gastroenterology Unit, Univerity of Oxford Nuffield Department of Medicine, Oxford, UK
- Gastroenterology, Mayo Clinic Healthcare, London, UK
| | - Jos Kleijnen
- Kleijnen Systematic Reviews Ltd, York, North Yorkshire, UK
| | - Michael Machesney
- Colorectal Surgery, Whipps Cross Hospital, Barts Health NHS Trust, London, UK
| | - Maria Pettman
- Colorectal Surgery, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | | | - Lance Saker
- General Practice, Oak Lodge Medical Centre, London, UK
| | - Linda Sharp
- Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK
| | | | - Robert Jc Steele
- Surgery and Oncology Department, University of Dundee, Dundee, UK
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