Evidence map›Paper›PMID 35790835›Full record

ArticleEye (London, England)2023

Personalized treatment supported by automated quantitative fluid analysis in active neovascular age-related macular degeneration (nAMD)-a phase III, prospective, multicentre, randomized study: design and methods.

Leonard M Coulibaly, Stefan Sacu, Philipp Fuchs, Hrvoje Bogunovic, Georg Faustmann, Christian Unterrainer, Gregor S Reiter, Ursula Schmidt-Erfurth

Abstract readClinical Trial Protocol
In one paragraph

Article in Eye (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  12. Analysis of OCT Scanning Parameters in AMD and RVO.Diagnostics (Basel, Switzerland) · 2024
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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

8 authors.

Leonard M CoulibalyVienna Clinical Trial Centre (VTC), Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Stefan SacuVienna Clinical Trial Centre (VTC), Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Philipp FuchsVienna Clinical Trial Centre (VTC), Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Hrvoje BogunovicChristian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-9168-0894
Georg FaustmannChristian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.
Christian UnterrainerRetInSight, Vienna, Austria.
Gregor S ReiterChristian Doppler Laboratory for Ophthalmic Image Analysis, Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-7661-4015
Ursula Schmidt-ErfurthVienna Clinical Trial Centre (VTC), Department of Ophthalmology and Optometry, Medical University of Vienna, Vienna, Austria. ursula.schmidt-erfurth@meduniwien.ac.at.ORCID 0000-0002-7788-7311

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn neovascular age-related macular degeneration (nAMD) the exact amount of fluid and its location on optical coherence tomography (OCT) have been defined as crucial biomarkers for disease activity and therapeutic decisions. Yet in the absence of quantitative evaluation tools, real-world care outcomes are disappointing. Artificial intelligence (AI) offers a practical option for clinicians to enhance point-of-care management by analysing OCT volumes in a short time. In this protocol we present the prospective implementation of an AI-algorithm providing automated real-time fluid quantifications in a clinical real-world setting.

methodsThis is a prospective, multicentre, randomized (1:1) and double masked phase III clinical trial. Two-hundred-ninety patients with active nAMD will be randomized between a study arm using AI-supported fluid quantifications and another arm using conventional qualitative assessments, i.e. state-of-the-art disease management. The primary outcome is defined as the mean number of injections over 1 year. Change in BCVA is defined as a secondary outcome. DISCUSSION: Automated measurement of fluid volumes in all retinal compartments such as intraretinal fluid (IRF), and subretinal fluid (SRF) will serve as an objective tool for clinical investigators on which to base retreatment decisions. Compared to qualitative fluid assessment, retreatment decisions will be plausible and less prone to error or large variability. The underlying hypothesis is that fluid should be treated, while residual persistent or stable amounts of fluid may not benefit from further therapy. Reducing injection numbers without diminishing the visual benefit will increase overall patient safety and relieve the burden for healthcare providers. TRIAL-REGISTRATION: EudraCT-Number: 2019-003133-42.

Indexed as

Macular DegenerationRanibizumabAngiogenesis InhibitorsArtificial IntelligenceClinical Trials, Phase III as TopicHumansIntravitreal InjectionsMulticenter Studies as TopicPrecision MedicineProspective StudiesRandomized Controlled Trials as TopicSubretinal FluidTomography, Optical CoherenceVascular Endothelial Growth Factor AAngiogenesis InhibitorsRanibizumabVascular Endothelial Growth Factor A

Identifiers

PMID35790835
PMCPMC9255834

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Registered trials

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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 OpenQuestion graph.