Evidence map›Paper›PMID 42347990›Full record

ReviewGraefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie2026

Review of emerging imaging findings to reveal a broader spectrum of lesions in AMD.

Enrico Borrelli, Giovanni Neri, Alessandro Berni, Chiara Olivieri, Jay Chhablani, Giulia Corradetti, Rosa Dolz-Marco, Gregor S Reiter, Dinah Zur, Francesco Bandello and 1 more

Abstract readReview
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In one paragraph

Review in Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Enrico BorrelliDepartment of Surgical Sciences, University of Turin, Turin, Italy. borrelli.enrico@yahoo.com.ORCID http://orcid.org/0000-0003-2815-5031
Giovanni NeriDepartment of Surgical Sciences, University of Turin, Turin, Italy.
Alessandro BerniIRCCS San Raffaele Scientific Institute, Milan, Italy.
Chiara OlivieriDepartment of Surgical Sciences, University of Turin, Turin, Italy.
Jay ChhablaniDepartment of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Giulia CorradettiDepartment of Ophthalmology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Rosa Dolz-MarcoUnit of Macula, Oftalvist Clinic, Valencia, 46004, Spain.
Gregor S ReiterDepartment of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Dinah ZurFaculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, Israel.
Francesco BandelloIRCCS San Raffaele Scientific Institute, Milan, Italy.
Michele ReibaldiDepartment of Surgical Sciences, University of Turin, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Age-related macular degeneration (AMD) is the leading cause of irreversible vision loss in developed countries, with prevalence expected to reach nearly 288 million by 2040. Accurate classification of AMD is critical for patient care and clinical research, guiding prognosis, therapeutic strategies, and the design of clinical trials. A widely adopted framework, the Beckman classification, stratifies AMD based primarily on color fundus photography (CFP) findings, defining stages from early to late disease. While simple and clinically applicable, such systems do not account for several key phenotypes revealed by advances in multimodal imaging. Such novel phenotypes include reticular pseudodrusen (RPD), acquired vitelliform lesions (AVL), non-exudative macular neovascularization (MNV), incomplete retinal pigment epithelium and outer retina atrophy (iRORA), and non-neovascular exudative fluid. Recent imaging modalities-including optical coherence tomography (OCT), fundus autofluorescence (FAF), and OCT angiography (OCTA)-have uncovered features with important prognostic implications that are currently misclassified with respect to AMD. For example, eyes with RPD or AVL in the absence of drusen are currently misclassified as "early AMD" or excluded altogether, despite their high risk of progression. Similarly, the ambiguous status of non-exudative MNV, which carries both protective and harmful potential, highlights the need for greater granularity. The Classification of Atrophy Meetings (CAM) group has also introduced refined OCT-based definitions such as iRORA and cRORA, underscoring early degenerative changes that precede geographic atrophy. Moreover, novel entities like non-neovascular intraretinal or subretinal fluid challenge the assumption that exudation is synonymous with neovascular AMD. This review synthesizes recent evidence highlighting the limitations of current classification systems in light of these advances. Furthermore, we emphasize that intermediate AMD, currently treated as a uniform category, actually encompasses highly heterogeneous phenotypes with distinct risks and trajectories. A more nuanced, imaging-integrated classification system is urgently needed to improve disease staging, identify high-risk eyes, and ensure appropriate patient selection for emerging therapies. Such a framework would not only better reflect the complex natural history of AMD but also facilitate the regulatory shift toward continuous, quantitative endpoints in clinical trials.

Indexed as

Age-related macular degenerationClassificationGeographic atrophyImaging biomarkersIntermediate AMDMacular neovascularization

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.