Title |
Determinants of therapeutic lag in multiple sclerosis
|
---|---|
Published in |
Multiple Sclerosis Journal, January 2021
|
DOI | 10.1177/1352458520981300 |
Pubmed ID | |
Authors |
Izanne Roos, Emmanuelle Leray, Federico Frascoli, Romain Casey, J William L Brown, Dana Horakova, Eva Kubala Havrdova, Marc Debouverie, Maria Trojano, Francesco Patti, Guillermo Izquierdo, Sara Eichau, Gilles Edan, Alexandre Prat, Marc Girard, Pierre Duquette, Marco Onofrj, Alessandra Lugaresi, Pierre Grammond, Jonathan Ciron, Aurélie Ruet, Serkan Ozakbas, Jérôme De Seze, Céline Louapre, Hélène Zephir, Maria José Sá, Patrizia Sola, Diana Ferraro, Pierre Labauge, Gilles Defer, Roberto Bergamaschi, Christine Lebrun-Frenay, Cavit Boz, Elisabetta Cartechini, Thibault Moreau, David Laplaud, Jeannette Lechner-Scott, Francois Grand’Maison, Oliver Gerlach, Murat Terzi, Franco Granella, Raed Alroughani, Gerardo Iuliano, Vincent Van Pesch, Bart Van Wijmeersch, Daniele LA Spitaleri, Aysun Soysal, Eric Berger, Julie Prevost, Eduardo Aguera-Morales, Pamela McCombe, Tamara Castillo Triviño, Pierre Clavelou, Jean Pelletier, Recai Turkoglu, Bruno Stankoff, Olivier Gout, Eric Thouvenot, Olivier Heinzlef, Youssef Sidhom, Riadh Gouider, Tunde Csepany, Bertrand Bourre, Abdullatif Al Khedr, Olivier Casez, Philippe Cabre, Alexis Montcuquet, Abir Wahab, Jean-Philippe Camdessanche, Aude Maurousset, Ivania Patry, Karolina Hankiewicz, Corinne Pottier, Nicolas Maubeuge, Céline Labeyrie, Chantal Nifle, Alasdair Coles, Charles B Malpas, Sandra Vukusic, Helmut Butzkueven, Tomas Kalincik |
Abstract |
A delayed onset of treatment effect, termed therapeutic lag, may influence the assessment of treatment response in some patient subgroups. The objective of this study is to explore the associations of patient and disease characteristics with therapeutic lag on relapses and disability accumulation. Data from MSBase, a multinational multiple sclerosis (MS) registry, and OFSEP, the French MS registry, were used. Patients diagnosed with MS, minimum 1 year of exposure to MS treatment and 3 years of pre-treatment follow-up, were included in the analysis. Studied outcomes were incidence of relapses and disability accumulation. Therapeutic lag was calculated using an objective, validated method in subgroups stratified by patient and disease characteristics. Therapeutic lag under specific circumstances was then estimated in subgroups defined by combinations of clinical and demographic determinants. High baseline disability scores, annualised relapse rate (ARR) ⩾ 1 and male sex were associated with longer therapeutic lag on disability progression in sufficiently populated groups: females with expanded disability status scale (EDSS) < 6 and ARR < 1 had mean lag of 26.6 weeks (95% CI = 18.2-34.9), males with EDSS < 6 and ARR < 1 31.0 weeks (95% CI = 25.3-36.8), females with EDSS < 6 and ARR ⩾ 1 44.8 weeks (95% CI = 24.5-65.1), and females with EDSS ⩾ 6 and ARR < 1 54.3 weeks (95% CI = 47.2-61.5). Pre-treatment EDSS and ARR are the most important determinants of therapeutic lag. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 29% |
France | 1 | 14% |
Australia | 1 | 14% |
United States | 1 | 14% |
Unknown | 2 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 71% |
Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Science communicators (journalists, bloggers, editors) | 1 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 24 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 4 | 17% |
Student > Master | 3 | 13% |
Student > Doctoral Student | 2 | 8% |
Researcher | 2 | 8% |
Professor > Associate Professor | 1 | 4% |
Other | 0 | 0% |
Unknown | 12 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 29% |
Biochemistry, Genetics and Molecular Biology | 1 | 4% |
Social Sciences | 1 | 4% |
Immunology and Microbiology | 1 | 4% |
Neuroscience | 1 | 4% |
Other | 1 | 4% |
Unknown | 12 | 50% |