Predictors of treatment switching in the Big Multiple Sclerosis Data Network
Authors: Spelman Tim , Magyari Melinda , Butzkueven Helmut , Van Der Walt Anneke , Vukusic Sandra , Trojano Maria , Iaffaldano Pietro , Horáková Dana , Drahota Jirí , Pellegrini Fabio , Hyde Robert , Duquette Pierre , Lechner-Scott Jeannette , Sajedi Seyed Aidin , Lalive Patrice , Shaygannejad Vahid , Ozakbas Serkan , Eichau Sara , Alroughani Raed , Terzi Murat , Girard Marc , Kalincik Tomas , Grand'Maison Francois , Skibina Olga , Khoury Samia J. , Yamout Bassem , Sa Maria Jose , Gerlach Oliver , Blanco Yolanda , Karabudak Rana , Oreja-Guevara Celia , Altintas Ayse , Hughes Stella , McCombe Pamela , Ampapa Radek , de Gans Koen , McGuigan Chris , Soysal Aysun , Prevost Julie , John Nevin , Inshasi Jihad , Stawiarz Leszek , Manouchehrinia Ali , Forsberg Lars , Sellebjerg Finn , Glaser Anna , Pontieri Luigi , Joensen Hanna , Rasmussen Peter Vestergaard , Sejbaek Tobias , Poulsen Mai Bang , Christensen Jeppe Romme , Kant Matthias , Stilund Morten , Mathiesen Henrik , Hillert Jan ,   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
Published: December 2023

Background

Treatment 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.

Objective

The 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.

Methods

In 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.

Results

Every 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).

Conclusion

Switching 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.