학술논문
Predictors of treatment switching in the Big Multiple Sclerosis Data Network
Document Type
article
Author
Tim Spelman; Melinda Magyari; Helmut Butzkueven; Anneke Van Der Walt; Sandra Vukusic; Maria Trojano; Pietro Iaffaldano; Dana Horáková; Jirí Drahota; Fabio Pellegrini; Robert Hyde; Pierre Duquette; Jeannette Lechner-Scott; Seyed Aidin Sajedi; Patrice Lalive; Vahid Shaygannejad; Serkan Ozakbas; Sara Eichau; Raed Alroughani; Murat Terzi; Marc Girard; Tomas Kalincik; Francois Grand'Maison; Olga Skibina; Samia J. Khoury; Bassem Yamout; Maria Jose Sa; Oliver Gerlach; Yolanda Blanco; Rana Karabudak; Celia Oreja-Guevara; Ayse Altintas; Stella Hughes; Pamela McCombe; Radek Ampapa; Koen de Gans; Chris McGuigan; Aysun Soysal; Julie Prevost; Nevin John; Jihad Inshasi; Leszek Stawiarz; Ali Manouchehrinia; Lars Forsberg; Finn Sellebjerg; Anna Glaser; Luigi Pontieri; Hanna Joensen; Peter Vestergaard Rasmussen; Tobias Sejbaek; Mai Bang Poulsen; Jeppe Romme Christensen; Matthias Kant; Morten Stilund; Henrik Mathiesen; Jan Hillert; The Big MS Data Network: a collaboration of the Czech MS Registry, the Danish MS Registry, Italian MS Registry, Swedish MS Registry, MSBase Study Group, and OFSEP
Source
Frontiers in Neurology, Vol 14 (2023)
Subject
Language
English
ISSN
1664-2295
Abstract
BackgroundTreatment switching is a common challenge and opportunity in real-world clinical practice. Increasing diversity in disease-modifying treatments (DMTs) has generated interest in the identification of reliable and robust predictors of treatment switching across different countries, DMTs, and time periods.ObjectiveThe objective of this retrospective, observational study was to identify independent predictors of treatment switching in a population of relapsing-remitting MS (RRMS) patients in the Big Multiple Sclerosis Data Network of national clinical registries, including the Italian MS registry, the OFSEP of France, the Danish MS registry, the Swedish national MS registry, and the international MSBase Registry.MethodsIn this cohort study, we merged information on 269,822 treatment episodes in 110,326 patients from 1997 to 2018 from five clinical registries. Patients were included in the final pooled analysis set if they had initiated at least one DMT during the relapsing-remitting MS (RRMS) stage. Patients not diagnosed with RRMS or RRMS patients not initiating DMT therapy during the RRMS phase were excluded from the analysis. The primary study outcome was treatment switching. A multilevel mixed-effects shared frailty time-to-event model was used to identify independent predictors of treatment switching. The contributing MS registry was included in the pooled analysis as a random effect.ResultsEvery one-point increase in the Expanded Disability Status Scale (EDSS) score at treatment start was associated with 1.08 times the rate of subsequent switching, adjusting for age, sex, and calendar year (adjusted hazard ratio [aHR] 1.08; 95% CI 1.07–1.08). Women were associated with 1.11 times the rate of switching relative to men (95% CI 1.08–1.14), whilst older age was also associated with an increased rate of treatment switching. DMTs started between 2007 and 2012 were associated with 2.48 times the rate of switching relative to DMTs that began between 1996 and 2006 (aHR 2.48; 95% CI 2.48–2.56). DMTs started from 2013 onwards were more likely to switch relative to the earlier treatment epoch (aHR 8.09; 95% CI 7.79–8.41; reference = 1996–2006).ConclusionSwitching between DMTs is associated with female sex, age, and disability at baseline and has increased in frequency considerably in recent years as more treatment options have become available. Consideration of a patient's individual risk and tolerance profile needs to be taken into account when selecting the most appropriate switch therapy from an expanding array of treatment choices.