Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/33494
Title: Delay from treatment start to full effect of immunotherapies for multiple sclerosis
Authors: Roos, Izanne
Leray, Emmanuelle
Frascoli, Federico
Casey, Romain
Brown, J. William L.
Horakova, Dana
Havrdova, Eva K.
Trojano, Maria
Patti, Francesco
Izquierdo, Guillermo
Eichau, Sara
Onofrj, Marco
Lugaresi, Alessandra
Prat, Alexandre
Girard, Marc
Grammond, Pierre
Sola, Patrizia
Ferraro, Diana
Ozakbas, Serkan
Bergamaschi, Roberto
Sa, Maria Jose
Cartechini, Elisabetta
Boz, Cavit
Granella, Franco
Hupperts, Raymond
Terzi, Murat
Lechner-Scott, Jeannette
Spitaleri, Daniele
Van Pesch, Vincent
Soysal, Aysun
Olascoaga, Javier
Prevost, Julie
Aguera-Morales, Eduardo
Slee, Mark
Csepany, Tunde
Turkoglu, Recai
Sidhom, Youssef
Gouider, Riadh
VAN WIJMEERSCH, Bart 
McCombe, Pamela
Macdonell, Richard
Coles, Alasdair
Malpas, Charles B.
Butzkueven, Helmut
Vukusic, Sandra
Kalincik, Tomas
Issue Date: 2020
Publisher: OXFORD UNIV PRESS
Source: BRAIN, 143 (9) , p. 2742 -2756
Abstract: In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments ('therapeutic lag') on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag.
Notes: Kalincik, T (corresponding author), Univ Melbourne, Dept Med, CORe, 300 Grattan St, Melbourne, Vic 3050, Australia.
tomas.kalincik@unimelb.edu.au
Other: Kalincik, T (corresponding author), Univ Melbourne, Dept Med, CORe, 300 Grattan St, Melbourne, Vic 3050, Australia. tomas.kalincik@unimelb.edu.au
Keywords: multiple sclerosis;therapeutic lag
Document URI: http://hdl.handle.net/1942/33494
ISSN: 0006-8950
e-ISSN: 1460-2156
DOI: 10.1093/brain/awaa231
ISI #: WOS:000607095300025
Category: A1
Type: Journal Contribution
Validations: ecoom 2022
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
awaa231.pdfPublished version885.99 kBAdobe PDFView/Open
Show full item record

WEB OF SCIENCETM
Citations

23
checked on Apr 30, 2024

Page view(s)

24
checked on Jun 21, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.