Predictors of treatment switching in the Big Multiple Sclerosis Data Network

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; Finn Sellebjerg; Luigi Pontieri; Hanna Joensen; Peter Vestergaard Rasmussen; Mai Bang Poulsen; Jeppe Romme Christensen; Henrik Mathiesen; 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

doi:10.3389/fneur.2023.1274194

Predictors of treatment switching in the Big Multiple Sclerosis Data Network

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 TerziMarc 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, Finn Sellebjerg, Luigi Pontieri, Hanna Joensen, Peter Vestergaard Rasmussen, Mai Bang Poulsen, Jeppe Romme Christensen, Henrik Mathiesen, 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

^*Corresponding author for this work

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.

Original language	English
Article number	1274194
Journal	Frontiers in Neurology
Volume	14
ISSN	1664-2295
DOIs	https://doi.org/10.3389/fneur.2023.1274194
Publication status	Published - 2023

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Spelman, T., Magyari, M., Butzkueven, H., Van Der Walt, A., Vukusic, S., Trojano, M., Iaffaldano, P., Horáková, D., Drahota, J., Pellegrini, F., Hyde, R., Duquette, P., Lechner-Scott, J., Sajedi, S. A., Lalive, P., Shaygannejad, V., Ozakbas, S., Eichau, S., Alroughani, R., ... 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 (2023). Predictors of treatment switching in the Big Multiple Sclerosis Data Network. Frontiers in Neurology, 14, Article 1274194. https://doi.org/10.3389/fneur.2023.1274194

Spelman, T, Magyari, M, Butzkueven, H, Van Der Walt, A, Vukusic, S, Trojano, M, Iaffaldano, P, Horáková, D, Drahota, J, Pellegrini, F, Hyde, R, Duquette, P, Lechner-Scott, J, Sajedi, SA, Lalive, P, Shaygannejad, V, Ozakbas, S, Eichau, S, Alroughani, R, Terzi, M, Girard, M, Kalincik, T, Grand'Maison, F, Skibina, O, Khoury, SJ, Yamout, B, Sa, MJ, Gerlach, O, Blanco, Y, Karabudak, R, Oreja-Guevara, C, Altintas, A, Hughes, S, McCombe, P, Ampapa, R, de Gans, K, McGuigan, C, Soysal, A, Prevost, J, John, N, Inshasi, J, Stawiarz, L, Manouchehrinia, A, Sellebjerg, F , Pontieri, L, Joensen, H, Rasmussen, PV, Poulsen, MB , Christensen, JR, Mathiesen, H & 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 2023, 'Predictors of treatment switching in the Big Multiple Sclerosis Data Network', Frontiers in Neurology, vol. 14, 1274194. https://doi.org/10.3389/fneur.2023.1274194

@article{c65dedb1776b456fb1c66d0c2347f72a,

title = "Predictors of treatment switching in the Big Multiple Sclerosis Data Network",

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.",

author = "Tim Spelman and Melinda Magyari and Helmut Butzkueven and {Van Der Walt}, Anneke and Sandra Vukusic and Maria Trojano and Pietro Iaffaldano and Dana Hor{\'a}kov{\'a} and Jir{\'i} Drahota and Fabio Pellegrini and Robert Hyde and Pierre Duquette and Jeannette Lechner-Scott and Sajedi, {Seyed Aidin} and Patrice Lalive and Vahid Shaygannejad and Serkan Ozakbas and Sara Eichau and Raed Alroughani and Murat Terzi and Marc Girard and Tomas Kalincik and Francois Grand'Maison and Olga Skibina and Khoury, {Samia J} and Bassem Yamout and Sa, {Maria Jose} and Oliver Gerlach and Yolanda Blanco and Rana Karabudak and Celia Oreja-Guevara and Ayse Altintas and Stella Hughes and Pamela McCombe and Radek Ampapa and {de Gans}, Koen and Chris McGuigan and Aysun Soysal and Julie Prevost and Nevin John and Jihad Inshasi and Leszek Stawiarz and Ali Manouchehrinia and Finn Sellebjerg and Luigi Pontieri and Hanna Joensen and Rasmussen, {Peter Vestergaard} and Poulsen, {Mai Bang} and Christensen, {Jeppe Romme} and Henrik Mathiesen and {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}",

note = "Copyright {\textcopyright} 2023 Spelman, Magyari, Butzkueven, Van Der Walt, Vukusic, Trojano, Iaffaldano, Hor{\'a}kov{\'a}, 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.",

year = "2023",

doi = "10.3389/fneur.2023.1274194",

language = "English",

volume = "14",

journal = "Frontiers in Neurology",

issn = "1664-2295",

publisher = "Frontiers Research Foundation",

}

TY - JOUR

T1 - Predictors of treatment switching in the Big Multiple Sclerosis Data Network

AU - Spelman, Tim

AU - Magyari, Melinda

AU - Butzkueven, Helmut

AU - Van Der Walt, Anneke

AU - Vukusic, Sandra

AU - Trojano, Maria

AU - Iaffaldano, Pietro

AU - Horáková, Dana

AU - Drahota, Jirí

AU - Pellegrini, Fabio

AU - Hyde, Robert

AU - Duquette, Pierre

AU - Lechner-Scott, Jeannette

AU - Sajedi, Seyed Aidin

AU - Lalive, Patrice

AU - Shaygannejad, Vahid

AU - Ozakbas, Serkan

AU - Eichau, Sara

AU - Alroughani, Raed

AU - Terzi, Murat

AU - Girard, Marc

AU - Kalincik, Tomas

AU - Grand'Maison, Francois

AU - Skibina, Olga

AU - Khoury, Samia J

AU - Yamout, Bassem

AU - Sa, Maria Jose

AU - Gerlach, Oliver

AU - Blanco, Yolanda

AU - Karabudak, Rana

AU - Oreja-Guevara, Celia

AU - Altintas, Ayse

AU - Hughes, Stella

AU - McCombe, Pamela

AU - Ampapa, Radek

AU - de Gans, Koen

AU - McGuigan, Chris

AU - Soysal, Aysun

AU - Prevost, Julie

AU - John, Nevin

AU - Inshasi, Jihad

AU - Stawiarz, Leszek

AU - Manouchehrinia, Ali

AU - Sellebjerg, Finn

AU - Pontieri, Luigi

AU - Joensen, Hanna

AU - Rasmussen, Peter Vestergaard

AU - Poulsen, Mai Bang

AU - Christensen, Jeppe Romme

AU - Mathiesen, Henrik

AU - 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

N1 - Copyright © 2023 Spelman, Magyari, Butzkueven, Van Der Walt, Vukusic, Trojano, Iaffaldano, Horáková, 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.

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85181709240&partnerID=8YFLogxK

U2 - 10.3389/fneur.2023.1274194

DO - 10.3389/fneur.2023.1274194

M3 - Journal article

C2 - 38187157

SN - 1664-2295

VL - 14

JO - Frontiers in Neurology

JF - Frontiers in Neurology

M1 - 1274194

ER -

Predictors of treatment switching in the Big Multiple Sclerosis Data Network

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