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Predictors of Treatment Switching in the Big Multiple Sclerosis Data Network Publisher



Spelman T1, 2 ; Magyari M3, 4 ; Butzkueven H2, 5 ; Van Der Walt A2, 6 ; Vukusic S7, 8, 9 ; Trojano M10 ; Iaffaldano P11 ; Horakova D12 ; Drahota J12 ; Pellegrini F13, 14 ; Hyde R13 ; Duquette P15 ; Lechnerscott J16, 17 ; Sajedi SA18 Show All Authors
Authors
  1. Spelman T1, 2
  2. Magyari M3, 4
  3. Butzkueven H2, 5
  4. Van Der Walt A2, 6
  5. Vukusic S7, 8, 9
  6. Trojano M10
  7. Iaffaldano P11
  8. Horakova D12
  9. Drahota J12
  10. Pellegrini F13, 14
  11. Hyde R13
  12. Duquette P15
  13. Lechnerscott J16, 17
  14. Sajedi SA18
  15. Lalive P19
  16. Shaygannejad V20
  17. Ozakbas S21
  18. Eichau S22
  19. Alroughani R23
  20. Terzi M24
  21. Girard M15
  22. Kalincik T25
  23. Grandmaison F26
  24. Skibina O5
  25. Khoury SJ27
  26. Yamout B27
  27. Sa MJ28
  28. Gerlach O29
  29. Blanco Y30
  30. Karabudak R31
  31. Orejaguevara C32
  32. Altintas A33
  33. Hughes S34
  34. Mccombe P35
  35. Ampapa R36
  36. De Gans K37
  37. Mcguigan C38
  38. Soysal A39
  39. Prevost J40
  40. John N41
  41. Inshasi J42
  42. Stawiarz L1
  43. Manouchehrinia A1
  44. Forsberg L1
  45. Sellebjerg F4
  46. Glaser A1
  47. Pontieri L3
  48. Joensen H3
  49. Rasmussen PV43
  50. Sejbaek T44
  51. Poulsen MB45
  52. Christensen JR3
  53. Kant M46
  54. Stilund M47, 48
  55. Mathiesen H49
  56. Hillert J1

Source: Frontiers in Neurology Published:2023


Abstract

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. Copyright © 2023 Spelman, Magyari, Butzkueven, Van Der Walt, Vukusic, Trojano, Iaffaldano, Horakova, Drahota, Pellegrini, Hyde, Duquette, Lechner-Scott, Sajedi, Lalive, Shaygannejad, Ozakbas, Eichau, Alroughani, Terzi, Girard, Kalincik, Grand'Maison, Skibina, Khoury, Yamout, Sa, Gerlach, Blanco, Karabudak, Oreja-Guevara, Altintas, Hughes, McCombe, Ampapa, de Gans, McGuigan, Soysal, Prevost, John, Inshasi, Stawiarz, Manouchehrinia, Forsberg, Sellebjerg, Glaser, Pontieri, Joensen, Rasmussen, Sejbaek, Poulsen, Christensen, Kant, Stilund, Mathiesen, Hillert and 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.
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