Background/aims To evaluate the cost-effectiveness of non-invasive monitoring tests to detect the onset of neovascular age-related macular degeneration (nAMD) in the unaffected second eye of patients receiving treatment for unilateral nAMD in a UK National Health Service (NHS) hospital outpatient setting.
Methods A patient-level state transition model was constructed to simulate the onset, detection, and treatment of nAMD in the second eye. Five index tests were compared: self-reported change in visual function, Amsler test, clinic measured change in visual acuity from baseline, fundus assessment by clinical examination or colour photography, and spectral domain optical coherence tomography (SD-OCT). Diagnosis of nAMD was confirmed by fundus fluorescein angiography (FFA) before prompt initiation of antivascular endothelial growth factor treatment. Quality-adjusted life-years (QALYs) and costs of health and social care were modelled over a 25-year time horizon.
Results SD-OCT generated more QALYs (SD-OCT, 5.830; fundus assessment, 5.787; Amsler grid, 5.736, patient’s subjective assessment, 5.630; and visual acuity, 5.600) and lower health and social care costs (SD-OCT, £19 406; fundus assessment, £19 649; Amsler grid, £19 751; patient’s subjective assessment, £20 198 and visual acuity, £20 444) per patient compared with other individual monitoring tests. Probabilistic sensitivity analysis indicated a high probability (97%–99%) of SD-OCT being the preferred test across a range of cost-effectiveness thresholds (£13 000–£30 000) applied in the UK NHS.
Conclusions Early treatment of the second eye following FFA confirmation of SD-OCT positive findings is expected to maintain better visual acuity and health-related quality of life and may reduce costs of health and social care over the lifetime of patients.
- diagnostic tests/investigation
Data availability statement
Data are available on reasonable request. Requests for data from the EDNA study can be made via the corresponding author.
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Contributors RH (Research Fellow, Health Economics) developed the model and conducted the economic analysis. CK conducted the costing survey and analyses of postconversion visual acuity data to inform key model inputs. KB (Research Fellow, Trial Management) contributed to the conception and design of the study and was responsible for its day-to-day conduct and management. BG (Research Fellow, Statistics) conducted the statistical analyses which informed the time to conversion and diagnostic accuracy inputs for the economic model. JK (Associate Professor, Statistics) contributed to the conception and design of the study and was responsible for the statistical analysis of time to conversion and diagnostic accuracy. SS (Consultant, Ophthalmology), RH (Senior Lecturer, Vision Science). AA-B (Consultant, Ophthalmology), and HH (Consultant, Ophthalmology) all contributed to the conception and design of the study and provided clinical expertise and insights to inform key modelling assumptions. MD contributed to the development of the economic model. RG (Consultant, Ophthalmology), Chief investigator of the parallel FASBAT study, provided clinical expertise and data to inform key model inputs and assumptions. MP (Trial Manager for the FASBAT study) was responsible for the collection of post conversion visual acuity and treatment data for EDNA participants who subsequently converted and enrolled in the FASTBAT study (used to inform key modelling inputs). CRR (Professor, Health Care Evaluation), Co-Chief Investigator of EDNA, contributed to the conception and design of the study and was methodological lead for the study. UC (Consultant, Ophthalmology), Chief Investigator of EDNA, led the conception and design of the study and the recruitment and follow-up of participants. GSS (Reader, Health Economics) contributed to the conception and design of the study, was responsible for the health economic objectives, and led the writing of this manuscript.
Funding The project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment Programme (grant number: 12/142/07) and will be published in full in Health Technology Assessment. The funder was not involved in the study design; in the collection, analysis and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication. The Health Services Research Unit (HSRU) and the Health Economics Research Unit (HERU) are core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorate (HSRU/2021–2024, HERU/2021–2024).
Disclaimer The views expressed are those of the authors and not necessarily those of the NIHR or Chief Scientist Office of the Scottish Government Health and Social Care Directorate
Competing interests Grant funding for the study from the NIHR HTA programme (grant number: 12/142/07). SS reports grants and personal fees from Novartis, grants from Allergan, grants and personal fees from Roche, grants and personal fees from Boehringer Ingleheim, personal fees from Apellis, personal fees from Oxurion, personal fees from Heidelberg Engineering, personal fees from Optos, grants and personal fees from Bayer, outside the submitted work. RG reports grants and personal fees from Novartis, grants and personal fees from Bayer, personal fees from Roche, and personal fees from Almeria / allergan, outside the submitted work. CRR is a member of NIHR HTA General Board. UC reports personal fees from Roche, outside the submitted work. GSS reports non-financial support from Merck KGaA, outside the submitted work.
Provenance and peer review Not commissioned; externally peer reviewed.
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