Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee

Trystan Macdonald¹, Zhivko Zhelev², Xiaoxuan Liu¹, Christopher Hyde², Jiri Fajtl³, Catherine Egan⁴, Adnan Tufail⁴, Alicja R Rudnicka⁵, Bethany Shinkins⁶, Rosalind Given-Wilson⁷, J Kevin Dunbar⁸, Steve Halligan⁹, Peter Scanlon¹⁰, Anne Mackie¹¹, Sian Taylor-Philips¹², Alastair K Denniston¹³

Affiliations

¹ College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHSFT, Birmingham, UK.
² Exeter Test Group, College of Medicine and Health, University of Exeter Medical School, Exeter, UK.
³ School of Computer Science and Mathematics, Kingston University London, London, UK.
⁴ NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Ophthalmology, University College London, London, UK.
⁵ Population Health Research Institute, St George's University of London, London, UK.
⁶ Warwick Medical School, University of Warwick, Coventry, UK.
⁷ St George's University Hospitals NHS Foundation Trust, London, UK.
⁸ Vaccination and Screening Directorate, NHS England, London, UK.
⁹ Centre for Medical Imaging, Division of Medicine, University College London, London, UK.
¹⁰ Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, UK.
¹¹ UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
¹² Warwick Medical School, University of Warwick, Coventry, UK; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
¹³ College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHSFT, Birmingham, UK. Electronic address: a.denniston@bham.ac.uk.

PMID: 40185647
DOI: 10.1016/j.landig.2024.12.004

Free article

Review

Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee

Trystan Macdonald et al. Lancet Digit Health. 2025 May.

Free article

. 2025 May;7(5):100840.

doi: 10.1016/j.landig.2024.12.004. Epub 2025 Apr 3.

Authors

Affiliations

¹ College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHSFT, Birmingham, UK.
² Exeter Test Group, College of Medicine and Health, University of Exeter Medical School, Exeter, UK.
³ School of Computer Science and Mathematics, Kingston University London, London, UK.
⁴ NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Ophthalmology, University College London, London, UK.
⁵ Population Health Research Institute, St George's University of London, London, UK.
⁶ Warwick Medical School, University of Warwick, Coventry, UK.
⁷ St George's University Hospitals NHS Foundation Trust, London, UK.
⁸ Vaccination and Screening Directorate, NHS England, London, UK.
⁹ Centre for Medical Imaging, Division of Medicine, University College London, London, UK.
¹⁰ Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, UK.
¹¹ UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
¹² Warwick Medical School, University of Warwick, Coventry, UK; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
¹³ College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHSFT, Birmingham, UK. Electronic address: a.denniston@bham.ac.uk.

PMID: 40185647
DOI: 10.1016/j.landig.2024.12.004

Abstract

Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts of this process through artificial intelligence, commonly known as automated retinal imaging analysis software (ARIAS). A number of such products are now on the market. In the UK, Scotland has used a rules-based autograder since 2011, but the diabetic eye screening programmes in the rest of the UK rely solely on human graders. With more sophisticated machine learning-based ARIAS now available and greater challenges in terms of human grader capacity, in 2019 the UK's National Screening Committee (NSC) was asked to consider the modification of diabetic eye screening in England with ARIAS. Following up on a review of ARIAS research highlighting the strengths and limitations of existing evidence, the NSC here sets out their considerations for evaluating evidence to support the introduction of ARIAS into the diabetic eye screening programme.

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Conflict of interest statement

Declaration of interests XL reports consulting fees from Hardian Health and Conceivable Life Sciences, and a past role as a Health Scientist at Apple. CH is a member of the UK NSC, which funded the Exeter Test Group at University of Exeter to do evidence review of screening for diabetic retinopathy. CE has received a grant or contract and travel support to attend MacTel international clinical study meetings from the Lowy Medical Research Institute; and consulting fees from Heidelberg Engineering, Inozyme Pharma, and Boehringer Ingelheim. AT has received consulting fees from Annexon, Apellis, Bayer, Genentech, Iveric Bio, Novartis, Oxurion, Roche, Heidelberg Engineering, Ocular Therapeutix, Opthea, Oculogics, and Boehringer Ingelheim; payment or honoraria from Apellis; and sits on the Data Safety Monitoring Board or Advisory Board for the Alvotech AVT06 study and J&J 1887 study. RG-W is a member of the UK NSC and Non-Executive Director at Moorfields Eye Hospital. SH is Chair of the UK NSC Artificial Intelligence Task Group, which received institutional funding from the National Institute for Health and Care Research (NIHR) biomedical research centre; is a member of the UK NSC Adult Reference Group and the NIHR health technology assessment prioritisation board; and is a Clinical Professional Advisor for the National Health Service England diabetic eye screening programme; and reports payment for expert witness work from multiple instructing solicitors. PS reports consulting fees from Boehringer; grants or contracts from Zeiss, Centervue, Optos, and Bayer; speaker fees from Bayer and Topcon; and support for attending meetings from Boehringer and Bayer. ST-P is a member of the UK NSC and Chair of the UK NSC Research and Methodology Group, funded by an NIHR Research Professorship (NIHR302434). All other authors declare no competing interests. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee

Affiliations

Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee

Authors

Affiliations

Abstract

Conflict of interest statement

References

Publication types

MeSH terms

LinkOut - more resources

Full Text Sources

Medical