Open access

Short Communication

4 December 2020

A Delphi panel on treatment of high disease activity relapsing remitting multiple sclerosis in the Netherlands

Authors: Renée E Michels https://orcid.org/0000-0002-1799-9653 [email protected], Michel L Peters, Krijn MH Schiffers, Paul A Bouma, Gerald ID Hengstman, Caspar EP van Munster, Esther Zeinstra, Gert De Voer, and Marieke KrolAuthor Info & Affiliations

Publication: Journal of Comparative Effectiveness Research

Volume 10, Number 2

https://doi.org/10.2217/cer-2020-0140

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Abstract

Aim: To gain insight into current treatment and barriers to optimal treatment for high disease activity relapsing remitting multiple sclerosis (MS) in the Netherlands. Materials & methods: A two-round Delphi panel using an online questionnaire was conducted. Seven MS neurologists from diverse locations in the Netherlands were invited to participate. Result: Out of the seven MS neurologists, five completed both questionnaire rounds. Conclusion: Effectiveness and side effects along with patient’s lesion load were the most important factors for choosing a disease modifying therapy (DMTs). Respondents felt restricted to optimally treat their patients due to reimbursement restrictions for certain disease modifying therapies, although agreed that satisfactory treatment options are currently available. The answers show consensus between the participating MS neurologists with high certainty of answers.

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References

Papers of special note have been highlighted as: • of interest

1.

Franciotta D, Salvetti M, Lolli F, Serafini B, Aloisi F. B cells and multiple sclerosis. Lancet Neurol. 7(9), 852–858 (2008).

2.

Kleinschnitz C, Meuth SG, Kieseier BC, Wiendl H. Immunotherapeutic approaches in MS: update on pathophysiology and emerging agents or strategies 2006. Endocr. Metab. Immune Disord. Drug Targets 7(1), 35–63 (2007).

3.

Chitnis T. The role of CD4 T cells in the pathogenesis of multiple sclerosis. Int. Rev. Neurobiol. 79, 43–72 (2007).

4.

Lublin FD, Reingold SC, Cohen JA et al. Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology 83(3), 278–286 (2014).

5.

European Medicines Agency. Mavenclad – summary of product characteristics (2017). Last revision of text in 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/mavenclad

6.

Richtlijn Multiple Sclerose. https://richtlijnendatabase.nl/richtlijn/multipele_sclerose/multipele_sclerose_-_startpagina.html

• Dutch guideline for multiple sclerosis.

7.

Zorginstituut Nederland. GVS beoordeling cladribine (mavenclad^®) (2018). https://www.zorginstituutnederland.nl/publicaties/adviezen/2018/01/24/gvs-advies-cladribine-mavenclad

• Dutch Health Technology Assessment (HTA) assessment report for cladribine tablets listing the reimbursement restrictions.

8.

European Medicines Agency. Gilenya – summary of product characteristics (2011). Last revision of text in 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/gilenya

9.

Zorginstituut Nederland. Wijziging bijlage 2 voorwaarde fingolimod (gilenya). (2016). https://www.zorginstituutnederland.nl/publicaties/adviezen/2016/07/12/wijziging-bijlage-2-voorwaarde-fingolimod-gilenya-bij-actieve-relapse-remitting-multiple-sclerose-rrms

• Dutch HTA assessment report for fingolimod listing the reimbursement restrictions.

10.

European Medicines Agency. Tysabri – summary of product characteristics. (2006). Last revision of the text in 2018. https://www.ema.europa.eu/en/medicines/human/EPAR/tysabri

11.

Zorginstituut Nederland. Herbeoordeling en duiding van natalizumab tysabri^®. (2014). https://www.zorginstituutnederland.nl/binaries/zinl/documenten/adviezen/2014/07/14/natalizumab-tysabri-bij-zeer-actieve-relapsing-remitting-multiple-sclerose/Natalizumab+Tysabri+bij+zeer+actieve+relapsing+remitting+multiple+sclerose.pdf

12.

Avella JR. Delphi panels: research design, procedures, advantages, and challenges. J. Doctoral Studies 11, 305–321 (2016).

13.

Akins RB, Tolson H, Cole BR. Stability of response characteristics of a Delphi panel: application of bootstrap data expansion. BMC Med. Res. Methodol. 5, 37 (2005).

14.

Iqbal S, Pipon-Young L. The Delphi method. Psychologist 22(7), 598–601 (2009).

15.

Simoens S. Using the Delphi technique in economic evaluation: time to revisit the oracle? J. Clin. Pharm. Ther. 31(6), 519–522 (2006).

16.

Powell C. The Delphi technique: myths and realities. J. Adv. Nurs. 41(4), 376–382 (2003).

17.

Kremer IEH, Evers S, Jongen PJ, Hiligsmann M. Comparison of preferences of healthcare professionals and MS patients for attributes of disease-modifying drugs: a best-worst scaling. Health Expect. 21(1), 171–180 (2018).

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