Evidence map›Paper›PMID 40775528›Full record

ReviewGene therapy2026

Visualising treatment effects in low-vision settings: proven and potential endpoints for clinical trials of inherited retinal disease therapies.

Arun J Thirunavukarasu, Shabnam Raji, Jasmina Cehajic Kapetanovic

Abstract readReview
In one paragraph

Review in Gene therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
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

3 authors.

Arun J ThirunavukarasuNuffield Laboratory of Ophthalmology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK. enquiries@ndcn.ox.ac.uk.ORCID 0000-0001-8968-4768
Shabnam RajiNuffield Laboratory of Ophthalmology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0009-0003-6779-5194
Jasmina Cehajic KapetanovicNuffield Laboratory of Ophthalmology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0002-9956-6412

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inherited retinal diseases are a devasting and incurable cause of blindness which frequently affect patients at a young age, and developing effective treatments has been an important research priority in recent decades. Treatments must be validated in randomised-control trials, which involve measuring benefit according to prospectively defined endpoints. A wide variety of conventional clinical endpoints and emerging anatomical, physiological, and functional biomarkers may be selected. Different options may be better or worse at capturing clinically significant differences and identifying real differences between experimental groups. This review provides an overview of some proven and potential endpoints for randomised-control trials involving inherited retinal disease patients. Clinical endpoints and biomarkers are discussed, and the work required to validate biomarkers for use in trials is outlined. Unlike in general medicine, ophthalmological clinical endpoints may all be conceptualised as surrogates for maintained vision. Selecting optimal endpoints is essential to ensure that treatments are assessed fairly, such that resources are directed towards interventions that stand to truly benefit patients with inherited retinal diseases.

Indexed as

Genetic TherapyRetinal DiseasesBiomarkersEndpoint DeterminationHumansRandomized Controlled Trials as TopicTreatment OutcomeBiomarkers

Identifiers

PMID40775528
PMCPMC7619018

What OpenQuestion 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 OpenQuestion graph.