Visually Evoked Potential as Prognostic Biomarker for Neuroaxonal Damage in Multiple Sclerosis From a Multicenter Longitudinal Cohort
Open accessAbstract
Background and Objectives With the increasing use of visually evoked potentials (VEPs) as quantitative outcome parameters for myelin in clinical trials, an in-depth understanding of longitudinal VEP latency changes and their prognostic potential for subsequent neuronal loss will be required. In this longitudinal multicenter study, we evaluated the association and prognostic potential of VEP latency for retinal neurodegeneration, measured by optical coherence tomography (OCT), in relapsing-remitting MS (RRMS). Methods We included 293 eyes of 147 patients with RRMS (age [years, median ± SD] 36 ± 10, male sex 35%, F/U [years, median {IQR} 2.1 {1.5–3.9}]): 41 eyes had a history of optic neuritis (ON) ≥6 months before baseline (CHRONIC-ON), and 252 eyes had no history of ON (CHRONIC-NON). P100 latency (VEP), macular combined ganglion cell and inner plexiform layer volume (GCIPL), and peripapillary retinal nerve fiber layer thickness (pRNFL) (OCT) were quantified. Results P100 latency change over the first year predicted subsequent GCIPL loss (36 months) across the entire chronic cohort (p = 0.001) and in (and driven by) the CHRONIC-NON subset (p = 0.019) but not in the CHRONIC-ON subset (p = 0.680). P100 latency and pRNFL were correlated at baseline (CHRONIC-NON p = 0.004, CHRONIC-ON p < 0.001), but change in P100 latency and pRNFL were not correlated. P100 latency did not differ longitudinally between protocols or centers. Discussion VEP in non-ON eyes seems to be a promising marker of demyelination in RRMS and of potential prognostic value for subsequent retinal ganglion cell loss. This study also provides evidence that VEP may be a useful and reliable biomarker for multicenter studies.
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OCT is emerging as a robust prognostic biomarker in MS and was also suggested to be applicable for treatment decisions and differential diagnosis.
“Further, OCT is emerging as a robust prognostic biomarker in MS and was also suggested to be applicable for treatment decisions and differential diagnosis.”
From Applying the 2024-revised McDonald criteria for multiple sclerosis using conventional diagnostic tools: a single-centre prospective cohort study in Germany (2026) · cites this paper as [38]
The Background and Objectives and Methods sections describe OCT as a measure of retinal neurodegeneration, while the Discussion evaluates VEP latency—not OCT—as a prognostic marker. Searches for OCT prognosis, treatment decisions, and differential diagnosis found no passage in our copy addressing those claimed uses of OCT. Page numbers were not available. (LLM, conf=0.75)
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- Authors
- Oertel, F. C., Krämer, J., Motamedi, S., Keihani, A., Zimmermann, H. G., Dimitriou, N. G., Condor-Montes, S., Bereuter, C., Cordano, C., Abdelhak, A., Trip, A., Aktas, O., Meuth, S. G., Wiendl, H., Ruprecht, K., Bellmann-Strobl, J., Paul, F., Petzold, A., Brandt, A. U., Albrecht, P., & Green, A. J.
- Affiliations
- University of California, San Francisco (US)
- From the Weill Institute for Neurosciences (F.C.C.O., A.K., S.C.-M., C.C., A.A., A.J.G.), Department of Neurology, University of California San Francisco (UCSF); Experimental and Clinical Research Center (F.C.C.O., S.M., H.G.Z., C.B., J.B.-S., F.P., A.U.B.), Max Delbrück Center for Molecular Medicine and Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Germany; Department of Neurology with Institute of Translational Neurology (J.K.,...
- Corresponding author
- Green, Ari J.
- ORCID
- Oertel, Frederike Cosima
- Krämer, Julia
- Motamedi, Seyedamirhosein
- Keihani, Azeen
- Zimmermann, Hanna G.
- Condor-Montes, Shivany
- Bereuter, Charlotte
- Cordano, Christian
- Abdelhak, Ahmed
- Aktas, Orhan
- Meuth, Sven G.
- Wiendl, Heinz
- Ruprecht, Klemens
- Bellmann-Strobl, Judith
- Paul, Friedemann
- Petzold, Axel
- Brandt, Alexander U.
- Albrecht, Philipp
- Green, Ari J.
- Venue
- Neurology Neuroimmunology & Neuroinflammation
- Published
- 2023-05
- Volume
- 10
- Issue
- 3
- ISSN
- 2332-7812 (ISSN-L)
- PMC
- PMC10026703
- OpenAlex
- W4323348742
- Cited by
- 33
- References
- 41
- Citations by year
- 2026: 12 · 2025: 11 · 2024: 6 · 2023: 4
- FWCI
- 6.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Neurology Neuroimmunology & Neuroinflammation (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, cc-by)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- CINECA IRIS Institutial Research Information System (University of Genoa) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- National Eye Institute (P30EY002162)
- Topics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Ophthalmology › Glaucoma and retinal disorders
- Health Sciences › Medicine › Ophthalmology › Drug-Induced Ocular Toxicity
- Keywords
- visual evoked potentials, P100 latency, multiple sclerosis, relapsing-remitting multiple sclerosis, retinal neurodegeneration, optic neuritis, peripapillary retinal nerve fiber layer, prognostic factors, demyelination, neuroaxonal damage, longitudinal cohort
- MeSH terms
- Adult, Evoked Potentials, Female, Humans, Male, Middle Aged, Multiple Sclerosis, Optic Neuritis, Prognosis, Retina, Retinal Ganglion Cells
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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