Evidence map›Paper›PMID 40156473›Full record

ArticleActa ophthalmologica2025

Artificial intelligence-quantified schisis volume as a structural endpoint for gene therapy clinical trials in X-linked retinoschisis.

Tien-En Tan, Peilun Dai, Jonathan Hensman, Peter Kiraly, Beau J Fenner, Yong Liu, Rick S M Goh, Ian C Han, Daniel S W Ting, Camiel J F Boon and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Acta ophthalmologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Article
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.

Tien-En TanSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.ORCID https://orcid.org/0000-0002-9869-5159
Peilun DaiInstitute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.ORCID https://orcid.org/0000-0002-1680-0526
Jonathan HensmanDepartment of Ophthalmology, Amsterdam University Medical Center, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-2925-8940
Peter KiralyOxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Beau J FennerSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Yong LiuInstitute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Rick S M GohInstitute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Ian C HanThe University of Iowa Institute for Vision Research, The University of Iowa, Iowa City, Iowa, USA.
Daniel S W TingSingapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore.
Camiel J F BoonDepartment of Ophthalmology, Amsterdam University Medical Center, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0002-6737-7932
M Dominik FischerOxford Eye Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.

Funding

Agency for Science, Technology and Research A20H4g2141Agency for Science, Technology and Research H20C6a0032Duke-NUS Medical School 05/FY2020/EX/15-A58Duke-NUS Medical School 05/FY2022/EX/66-A128Duke-NUS Medical School Duke-NUS/RSF/2021/0018National Medical Research Council MOH-000655-00National Medical Research Council MOH001014-00
6 · The paper itself

Abstract

purposeTo use artificial intelligence (AI) for quantifying schisis volume (ASV) in X-linked retinoschisis (XLRS) for use as a structural endpoint in gene therapy clinical trials.

methodsWe used data from Singapore, the United Kingdom, the Netherlands, and the United States. The AI model was developed on 250 optical coherence tomography (OCT) slices, with human annotation of schisis cavities (Dataset 1). ASV was quantified on Dataset 2 - 16 OCT scans from 8 eyes with XLRS at two time points, and Dataset 4 - 62 OCT scans from 31 eyes at two time points before and after carbonic anhydrase inhibitor (CAI) treatment. A clinical trial was simulated comparing CAI treatment against control. Changes in ASV, central subfield thickness (CST) and central foveal thickness (CFT) were compared. Effect size (Cohen's d) of the three structural endpoints was determined and used in sample size calculations for a future XLRS gene therapy clinical trial, at a 0.05 significance level and 80% power.

resultsIn the simulated clinical trial, all structural metrics showed greater reductions with intervention than with control, but only change in ASV reached statistical significance (p = 0.004). Cohen's d for ASV, CST and CFT were 0.972, 0.685 and 0.521, respectively. For the future gene therapy clinical trial, sample sizes required in each arm for ASV, CST and CFT were 18, 35 and 59 participants, respectively.

conclusionsASV measurements can track changes in schisis volume in response to treatment. As an endpoint, ASV has a greater statistical effect size than CST/CFT, which reduces sample size requirements for future XLRS gene therapy clinical trials.

Indexed as

Artificial IntelligenceGenetic TherapyRetinoschisisTomography, Optical CoherenceAdultCarbonic Anhydrase InhibitorsChildFemaleHumansMaleMiddle AgedVisual AcuityYoung AdultCarbonic Anhydrase InhibitorsAIclinical trial endpointsgene therapyinherited retinal diseaseRS1XLRS

Identifiers

PMID40156473
PMCPMC12340173

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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.