Skip to main content

Advertisement

SpringerLink
Log in

First measured retinal nerve fiber layer thickness in RRMS can be used as a biomarker for the course of the disease: threshold value discussions

  • Original Communication
  • Published:
Journal of Neurology Aims and scope Submit manuscript

Abstract

Background

Peripapillary retinal nerve fiber layer thickness correlates with radiological and clinical parameters in patients with MS.

Objective

The aim of this study is to investigate the use of the first measured pRNFL thickness as a predictor of disease course in patients with RRMS.

Methods

One hundred and thirty seven RRMS patients were enrolled in the study within the first 5 years of illness. Patients were followed for 34.1 months and the EDSS was used to assess disability status to determine whether the first measured pRNFL thickness, using proportional hazards models, predicts the risk of disability worsening.

Results

The mean disease duration was 26.1 months. Disability worsening was detected in 36 patients. In tertile-based groups formed according to pRNFL thickness, the group with the lowest pRNFL thickness had a 2.8-fold increase in the risk of disability worsening compared to the group with the highest. The risk was higher in the first 2 years of the study (HR = 3.48; p = 0.008).

Conclusion

The first measured pRNFL thickness in RRMS patients can predict the risk of disability worsening, and the risk of disability worsening in the early period was higher in the group with the lowest pRNFL value.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Availability of data and materials

The dataset used and analyzed during the current study is available from the corresponding author on reasonable request.

References

  1. Balk LJ, Cruz-Herranz A, Albrecht P, Arnow S, Gelfand JM, Tewarie P, Killestein J, Uitdehaag BMJ, Petzold A, Green AJ (2016) Timing of retinal neuronal and axonal loss in MS: a longitudinal OCT study. J Neurol 263:1323–1331

    Article  Google Scholar 

  2. Bsteh G, Hegen H, Teuchner B, Amprosi M, Berek K, Ladstätter F, Wurth S, Auer M, Di Pauli F, Deisenhammer F, Berger T (2019) Peripapillary retinal nerve fibre layer as measured by optical coherence tomography is a prognostic biomarker not only for physical but also for cognitive disability progression in multiple sclerosis. Mult Scler 25:196–203

    Article  Google Scholar 

  3. Cilingir V, Batur M (2020) Axonal degeneration independent of inflammatory activity: is it more intense in the early stages of relapsing-remitting multiple sclerosis disease? Eur Neurol 83:508–516

    Article  Google Scholar 

  4. Cilingir V, Batur M, Bulut MD, Milanlioglu A, Yilgor A, Batur A, Yasar T, Tombul T (2017) The association between retinal nerve fibre layer thickness and corpus callosum index in different clinical subtypes of multiple sclerosis. Neurol Sci 38:1223–1232

    Article  Google Scholar 

  5. Costello F, Hodge W, Pan YI, Freedman M, DeMeulemeester C (2009) Differences in retinal nerve fiber layer atrophy between multiple sclerosis subtypes. J Neurol Sci 281:74–79

    Article  Google Scholar 

  6. Davion JB, Lopes R, Drumez É, Labreuche J, Hadhoum N, Lannoy J, Vermersch P, Pruvo JP, Leclerc X, Zéphir H, Outteryck O (2020) Asymptomatic optic nerve lesions: an underestimated cause of silent retinal atrophy in MS. Neurology 94:e2468–e2478

    Article  CAS  Google Scholar 

  7. Freedman MS, Abdoli M (2015) Evaluating response to disease-modifying therapy in relapsing multiple sclerosis. Expert Rev Neurother 15:407–423

    Article  CAS  Google Scholar 

  8. Gabilondo I, Martínez-Lapiscina EH, Martínez-Heras E, Fraga-Pumar E, Llufriu S, Ortiz S, Bullich S, Sepulveda M, Falcon C, Berenguer J, Saiz A, Sanchez-Dalmau B, Villoslada P (2014) Trans-synaptic axonal degeneration in the visual pathway in multiple sclerosis. Ann Neurol 75:98–107

    Article  CAS  Google Scholar 

  9. Garcia-Martin E, Ara JR, Martin J, Almarcegui C, Dolz I, Vilades E, Gil-Arribas L, Fernandez FJ, Polo V, Larrosa JM, Pablo LE, Satue M (2017) Retinal and optic nerve degeneration in patients with multiple sclerosis followed up for 5 years. Ophthalmology 124:688–696

    Article  Google Scholar 

  10. Gil-Perotin S, Castillo-Villalba J, Cubas-Nuñez L, Gasque R, Hervas D, Gomez-Mateu J, Alcala C, Perez-Miralles F, Gascon F, Dominguez JA, Casanova B (2019) Combined cerebrospinal fluid neurofilament light chain protein and chitinase-3 like-1 levels in defining disease course and prognosis in multiple sclerosis. Front Neurol 10:1008

    Article  Google Scholar 

  11. Havas J, Leray E, Rollot F, Casey R, Michel L, Lejeune F, Wiertlewski S, Laplaud D, Foucher Y (2020) Predictive medicine in multiple sclerosis: a systematic review. Mult Scler Relat Disord 40:101928

    Article  Google Scholar 

  12. Kalincik T, Manouchehrinia A, Sobisek L, Jokubaitis V, Spelman T, Horakova D, Havrdova E, Trojano M, Izquierdo G, Lugaresi A, Girard M, Prat A, Duquette P, Grammond P, Sola P, Hupperts R, Grand’Maison F, Pucci E, Boz C, Alroughani R, Van Pesch V, Lechner-Scott J, Terzi M, Bergamaschi R, Iuliano G, Granella F, Spitaleri D, Shaygannejad V, Oreja-Guevara C, Slee M, Ampapa R, Verheul F, McCombe P, Olascoaga J, Amato MP, Vucic S, Hodgkinson S, Ramo-Tello C, Flechter S, Cristiano E, Rozsa C, Moore F, Luis Sanchez-Menoyo J, Laura Saladino M, Barnett M, Hillert J, Butzkueven H (2017) Towards personalized therapy for multiple sclerosis: prediction of individual treatment response. Brain 140:2426–2443

    Article  Google Scholar 

  13. Lange AP, Zhu F, Sayao A-L, Sadjadi R, Alkabie S, Traboulsee AL, Costello F, Tremlett H (2013) Retinal nerve fiber layer thickness in benign multiple sclerosis. Mult Scler 19:1275–1281

    Article  Google Scholar 

  14. Lassmann H (2018) Multiple sclerosis pathology. Cold Spring Harb Perspect Med 8:a028936

    Article  Google Scholar 

  15. Martinez-Lapiscina EH, Arnow S, Wilson JA, Saidha S, Preiningerova JL, Oberwahrenbrock T, Brandt AU, Pablo LE, Guerrieri S, Gonzalez I, Outteryck O, Mueller AK, Albrecht P, Chan W, Lukas S, Balk LJ, Fraser C, Frederiksen JL, Resto J, Frohman T, Cordano C, Zubizarreta I, Andorra M, Sanchez-Dalmau B, Saiz A, Bermel R, Klistorner A, Petzold A, Schippling S, Costello F, Aktas O, Vermersch P, Oreja-Guevara C, Comi G, Leocani L, Garcia-Martin E, Paul F, Havrdova E, Frohman E, Balcer LJ, Green AJ, Calabresi PA, Villoslada P (2016) Retinal thickness measured with optical coherence tomography and risk of disability worsening in multiple sclerosis: a cohort study. Lancet Neurol 15:574–584

    Article  Google Scholar 

  16. Nolan RC, Galetta SL, Frohman TC, Frohman EM, Calabresi PA, Castrillo-Viguera C, Cadavid D, Balcer LJ (2018) Optimal intereye difference thresholds in retinal nerve fiber layer thickness for predicting a unilateral optic nerve lesion in multiple sclerosis. J Neuroophthalmol 38:451–458

    Article  Google Scholar 

  17. Oberwahrenbrock T, Ringelstein M, Jentschke S, Deuschle K, Klumbies K, Bellmann-Strobl J, Harmel J, Ruprecht K, Schippling S, Hartung H-P, Aktas O, Brandt AU, Paul F (2013) Retinal ganglion cell and inner plexiform layer thinning in clinically isolated syndrome. Mult Scler 19:1887–1895

    Article  Google Scholar 

  18. Pellegrini F, Copetti M, Bovis F, Cheng D, Hyde R, de Moor C, Kieseier BC, Sormani MP (2020) A proof-of-concept application of a novel scoring approach for personalized medicine in multiple sclerosis. Mult Scler 26:1064–1073

    Article  Google Scholar 

  19. Petzold A, Balcer LJ, Calabresi PA, Costello F, Frohman TC, Frohman EM, Martinez-Lapiscina EH, Green AJ, Kardon R, Outteryck O, Paul F, Schippling S, Vermersch P, Villoslada P, Balk LJ, Ern-Eye I (2017) Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis. Lancet Neurol 16:797–812

    Article  Google Scholar 

  20. Saidha S, Al-Louzi O, Ratchford JN, Bhargava P, Oh J, Newsome SD, Prince JL, Pham D, Roy S, van Zijl P, Balcer LJ, Frohman EM, Reich DS, Crainiceanu C, Calabresi PA (2015) Optical coherence tomography reflects brain atrophy in multiple sclerosis: a four-year study. Ann Neurol 78:801–813

    Article  Google Scholar 

  21. Saidha S, Syc SB, Ibrahim MA, Eckstein C, Warner CV, Farrell SK, Oakley JD, Durbin MK, Meyer SA, Balcer LJ, Frohman EM, Rosenzweig JM, Newsome SD, Ratchford JN, Nguyen QD, Calabresi PA (2011) Primary retinal pathology in multiple sclerosis as detected by optical coherence tomography. Brain 134:518–533

    Article  Google Scholar 

  22. Sormani MP, Rio J, Tintorè M, Signori A, Li D, Cornelisse P, Stubinski B, Stromillo M, Montalban X, De Stefano N (2013) Scoring treatment response in patients with relapsing multiple sclerosis. Mult Scler 19:605–612

    Article  CAS  Google Scholar 

  23. Tewarie P, Balk L, Costello F, Green A, Martin R, Schippling S, Petzold A (2012) The OSCAR-IB consensus criteria for retinal OCT quality assessment. PLoS ONE 7:e34823

    Article  CAS  Google Scholar 

  24. Tintore M, Rovira À, Río J, Otero-Romero S, Arrambide G, Tur C, Comabella M, Nos C, Arévalo MJ, Negrotto L, Galán I, Vidal-Jordana A, Castilló J, Palavra F, Simon E, Mitjana R, Auger C, Sastre-Garriga J, Montalban X (2015) Defining high, medium and low impact prognostic factors for developing multiple sclerosis. Brain 138:1863–1874

    Article  Google Scholar 

Download references

Acknowledgments

The authors want to explicitly thank Demet Kırk who diligently performed OCT scans for this study.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Van Yuzuncu Yil University Faculty of Medicine Neurology Department, Kampus, Tusba, 65300, Van, Turkey

    Vedat Cilingir

  2. Department of Ophthalmology, Van Yuzuncu Yil University, Van, Turkey

    Muhammed Batur

Authors
  1. Vedat Cilingir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Muhammed Batur
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vedat Cilingir.

Ethics declarations

Statement of ethics

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All the subjects provided their written informed consent, and the study protocol was accepted by the local ethics committee of our university.

Conflicts of interest

The authors declare that there is no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cilingir, V., Batur, M. First measured retinal nerve fiber layer thickness in RRMS can be used as a biomarker for the course of the disease: threshold value discussions. J Neurol 268, 2858–2865 (2021). https://doi.org/10.1007/s00415-021-10469-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00415-021-10469-x

Keywords

Search

Navigation