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One- and two-year visual outcomes from the Moorfields age-related macular degeneration database: a retrospective cohort study and an open science resource

22 Jun 2019


To analyse treatment outcomes and share clinical data from a large, single-centre, well-curated database (8174 eyes/6664 patients with 120 756 single entries) of patients with neovascular age-related macular degeneration (AMD) treated with anti-vascular endothelial growth factor (VEGF). By making our depersonalised raw data openly available, we aim to stimulate further research in AMD, as well as set a precedent for future work in this area.


Retrospective, comparative, non-randomised electronic medical record (EMR) database cohort study of the UK Moorfields AMD database with data extracted between 2008 and 2018.


Including one eye per patient, 3357 eyes/patients (61% female). Extraction criteria were ≥1 ranibizumab or aflibercept injection, entry of ‘AMD’ in the diagnosis field of the EMR and a minimum of 1 year of follow-up. Exclusion criteria were unknown date of first injection and treatment outside of routine clinical care at Moorfields before the first recorded injection in the database.

Main outcome measures

Primary outcome measure was change in VA at 1 and 2 years from baseline as measured in Early Treatment Diabetic Retinopathy Study letters. Secondary outcomes were the number of injections and predictive factors for VA gain.


Mean VA gain at 1 year and 2 years were +5.5 (95% CI 5.0 to 6.0) and +4.9 (95% CI 4.2 to 5.6) letters, respectively. Fifty-four per cent of eyes gained ≥5 letters at 2 years, 63% had stable VA (±≤14 letters), 44% of eyes maintained good VA (≥70 letters). Patients received a mean of 7.7 (95% CI 7.6 to 7.8) injections during year 1 and 13.0 (95% CI 12.8 to 13.2) injections over 2 years. Younger age, lower baseline VA and more injections were associated with higher VA gain at 2 years.


This study benchmarks high quality EMR study results of real life AMD treatment and promotes open science in clinical AMD research by making the underlying data publicly available.

Click here to view the full article which appeared in BMJ Open