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Survey of Ophthalmology 2024There is a need to identify accurately prognostic factors that determine the progression of intermediate to late-stage age-related macular degeneration (AMD). Currently,... (Meta-Analysis)
Meta-Analysis Review
There is a need to identify accurately prognostic factors that determine the progression of intermediate to late-stage age-related macular degeneration (AMD). Currently, clinicians cannot provide individualised prognoses of disease progression. Moreover, enriching clinical trials with rapid progressors may facilitate delivery of shorter intervention trials aimed at delaying or preventing progression to late AMD. Thus, we performed a systematic review to outline and assess the accuracy of reporting prognostic factors for the progression of intermediate to late AMD. A meta-analysis was originally planned. Synonyms of AMD and disease progression were used to search Medline and EMBASE for articles investigating AMD progression published between 1991 and 2021. Initial search results included 3229 articles. Predetermined eligibility criteria were employed to systematically screen papers by two reviewers working independently and in duplicate. Quality appraisal and data extraction were performed by a team of reviewers. Only 6 studies met the eligibility criteria. Based on these articles, exploratory prognostic factors for progression of intermediate to late AMD included phenotypic features (e.g. location and size of drusen), age, smoking status, ocular and systemic co-morbidities, race, and genotype. Overall, study heterogeneity precluded reporting by forest plots and meta-analysis. The most commonly reported prognostic factors were baseline drusen volume/size, which was associated with progression to neovascular AMD, and outer retinal thinning linked to progression to geographic atrophy. In conclusion, poor methodological quality of included studies warrants cautious interpretation of our findings. Rigorous studies are warranted to provide robust evidence in the future.
Topics: Humans; Prognosis; Angiogenesis Inhibitors; Disease Progression; Visual Acuity; Vascular Endothelial Growth Factor A; Wet Macular Degeneration; Retinal Drusen
PubMed: 37890677
DOI: 10.1016/j.survophthal.2023.10.010 -
Eye (London, England) Aug 2023The aim of this systematic literature review is twofold, (1) detail the impact of retinal biomarkers identifiable via optical coherence tomography (OCT) on disease... (Review)
Review
UNLABELLED
The aim of this systematic literature review is twofold, (1) detail the impact of retinal biomarkers identifiable via optical coherence tomography (OCT) on disease progression and response to treatment in neovascular age-related macular degeneration (nAMD) and (2) establish which biomarkers are currently identifiable by artificial intelligence (AI) models and the utilisation of this technology. Following the PRISMA guidelines, PubMed was searched for peer-reviewed publications dated between January 2016 and January 2022.
POPULATION
Patients diagnosed with nAMD with OCT imaging.
SETTINGS
Comparable settings to NHS hospitals.
STUDY DESIGNS
Randomised controlled trials, prospective/retrospective cohort studies and review articles. From 228 articles, 130 were full-text reviewed, 50 were removed for falling outside the scope of this review with 10 added from the author's inventory, resulting in the inclusion of 90 articles. From 9 biomarkers identified; intraretinal fluid (IRF), subretinal fluid, pigment epithelial detachment, subretinal hyperreflective material (SHRM), retinal pigmental epithelial (RPE) atrophy, drusen, outer retinal tabulation (ORT), hyperreflective foci (HF) and retinal thickness, 5 are considered pertinent to nAMD disease progression; IRF, SHRM, drusen, ORT and HF. A number of these biomarkers can be classified using current AI models. Significant retinal biomarkers pertinent to disease activity and progression in nAMD are identifiable via OCT; IRF being the most important in terms of the significant impact on visual outcome. Incorporating AI into ophthalmology practice is a promising advancement towards automated and reproducible analyses of OCT data with the ability to diagnose disease and predict future disease conversion.
SYSTEMATIC REVIEW REGISTRATION
This review has been registered with PROSPERO (registration ID: CRD42021233200).
Topics: Humans; Tomography, Optical Coherence; Artificial Intelligence; Retrospective Studies; Prospective Studies; Fluorescein Angiography; Biomarkers; Macular Degeneration; Disease Progression; Wet Macular Degeneration; Angiogenesis Inhibitors
PubMed: 36526863
DOI: 10.1038/s41433-022-02360-4