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3 results on '"Inshasi, J"'

1. Predictors of treatment switching in the Big Multiple Sclerosis Data Network.

Author

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, Forsberg, L, Sellebjerg, F, Glaser, A, Pontieri, L, Joensen, H, Rasmussen, PV, Sejbaek, T, Poulsen, MB, Christensen, JR, Kant, M, Stilund, M, Mathiesen, H, Hillert, J, 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, 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, Forsberg, L, Sellebjerg, F, Glaser, A, Pontieri, L, Joensen, H, Rasmussen, PV, Sejbaek, T, Poulsen, MB, Christensen, JR, Kant, M, Stilund, M, Mathiesen, H, Hillert, J, 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

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 1

Published
2023

2. Early non-disabling relapses are important predictors of disability accumulation in people with relapsing-remitting multiple sclerosis

Author

Daruwalla, C, Shaygannejad, V, Ozakbas, S, Havrdova, EK, Horakova, D, Alroughani, R, Boz, C, Patti, F, Onofrj, M, Lugaresi, A, Eichau, S, Girard, M, Prat, A, Duquette, P, Yamout, B, Khoury, SJ, Sajedi, SA, Turkoglu, R, Altintas, A, Skibina, O, Buzzard, K, Grammond, P, Karabudak, R, van der Walt, A, Butzkueven, H, Maimone, D, Lechner-Scott, J, Soysal, A, John, N, Prevost, J, Spitaleri, D, Ramo-Tello, C, Gerlach, O, Iuliano, G, Foschi, M, Ampapa, R, van Pesch, V, Barnett, M, Shalaby, N, D'hooghe, M, Kuhle, J, Sa, MJ, Fabis-Pedrini, M, Kermode, A, Mrabet, S, Gouider, R, Hodgkinson, S, Laureys, G, Van Hijfte, L, Macdonell, R, Oreja-Guevara, C, Cristiano, E, McCombe, P, Sanchez-Menoyo, JL, Singhal, B, Blanco, Y, Hughes, S, Garber, J, Solaro, C, McGuigan, C, Taylor, B, de Gans, K, Habek, M, Al-Asmi, A, Mihaela, S, Castillo Trivino, T, Al-Harbi, T, Rojas, JI, Gray, O, Khurana, D, Van Wijmeersch, B, Grigoriadis, N, Inshasi, J, Oh, J, Aguera-Morales, E, Fragoso, Y, Moore, F, Shaw, C, Baghbanian, SM, Shuey, N, Willekens, B, Hardy, TA, Decoo, D, Sempere, AP, Field, D, Wynford-Thomas, R, Cunniffe, NG, Roos, I, Malpas, CB, Coles, AJ, Kalincik, T, Brown, JWL, MSBase, SG, Daruwalla, C, Shaygannejad, V, Ozakbas, S, Havrdova, EK, Horakova, D, Alroughani, R, Boz, C, Patti, F, Onofrj, M, Lugaresi, A, Eichau, S, Girard, M, Prat, A, Duquette, P, Yamout, B, Khoury, SJ, Sajedi, SA, Turkoglu, R, Altintas, A, Skibina, O, Buzzard, K, Grammond, P, Karabudak, R, van der Walt, A, Butzkueven, H, Maimone, D, Lechner-Scott, J, Soysal, A, John, N, Prevost, J, Spitaleri, D, Ramo-Tello, C, Gerlach, O, Iuliano, G, Foschi, M, Ampapa, R, van Pesch, V, Barnett, M, Shalaby, N, D'hooghe, M, Kuhle, J, Sa, MJ, Fabis-Pedrini, M, Kermode, A, Mrabet, S, Gouider, R, Hodgkinson, S, Laureys, G, Van Hijfte, L, Macdonell, R, Oreja-Guevara, C, Cristiano, E, McCombe, P, Sanchez-Menoyo, JL, Singhal, B, Blanco, Y, Hughes, S, Garber, J, Solaro, C, McGuigan, C, Taylor, B, de Gans, K, Habek, M, Al-Asmi, A, Mihaela, S, Castillo Trivino, T, Al-Harbi, T, Rojas, JI, Gray, O, Khurana, D, Van Wijmeersch, B, Grigoriadis, N, Inshasi, J, Oh, J, Aguera-Morales, E, Fragoso, Y, Moore, F, Shaw, C, Baghbanian, SM, Shuey, N, Willekens, B, Hardy, TA, Decoo, D, Sempere, AP, Field, D, Wynford-Thomas, R, Cunniffe, NG, Roos, I, Malpas, CB, Coles, AJ, Kalincik, T, Brown, JWL, and MSBase, SG

Abstract

BACKGROUND: The prognostic significance of non-disabling relapses in people with relapsing-remitting multiple sclerosis (RRMS) is unclear. OBJECTIVE: To determine whether early non-disabling relapses predict disability accumulation in RRMS. METHODS: We redefined mild relapses in MSBase as 'non-disabling', and moderate or severe relapses as 'disabling'. We used mixed-effects Cox models to compare 90-day confirmed disability accumulation events in people with exclusively non-disabling relapses within 2 years of RRMS diagnosis to those with no early relapses; and any early disabling relapses. Analyses were stratified by disease-modifying therapy (DMT) efficacy during follow-up. RESULTS: People who experienced non-disabling relapses within 2 years of RRMS diagnosis accumulated more disability than those with no early relapses if they were untreated (n = 285 vs 4717; hazard ratio (HR) = 1.29, 95% confidence interval (CI) = 1.00-1.68) or given platform DMTs (n = 1074 vs 7262; HR = 1.33, 95% CI = 1.15-1.54), but not if given high-efficacy DMTs (n = 572 vs 3534; HR = 0.90, 95% CI = 0.71-1.13) during follow-up. Differences in disability accumulation between those with early non-disabling relapses and those with early disabling relapses were not confirmed statistically. CONCLUSION: This study suggests that early non-disabling relapses are associated with a higher risk of disability accumulation than no early relapses in RRMS. This risk may be mitigated by high-efficacy DMTs. Therefore, non-disabling relapses should be considered when making treatment decisions.

Published
2023

3. Early non-disabling relapses are important predictors of disability accumulation in people with relapsing-remitting multiple sclerosis

Author

Altıntaş, Ayşe (ORCID 0000-0002-8524-5087 & YÖK ID 11611), Daruwalla, C.; Shaygannejad, V.; Ozakbas, S.; Havrdova, EK.; Horakova, D.; Alroughani, R.; Boz, C.; Patti, F.; Onofrj, M.; Lugaresi, A.; Eichau, S.; Girard, M.; Prat, A.; Duquette, P.; Yamout, B.; Khoury, S.J.; Sajedi, S.A.; Turkoglu, R.; Skibina, O.; Buzzard, K.; Grammond, P.; Karabudak, R.; van der Walt, A.; Butzkueven, H.; Maimone, D.; Lechner-Scott, J.; Soysal, A.; John, N.; Prevost, J.; Spitaleri, D.; Ramo-Tello, C.; Gerlach, O.; Iuliano, G.; Foschi, M.; Ampapa, R.; van Pesch, V.; Barnett, M.; Shalaby, N.; D'hooghe, M.; Kuhle, J.; Sa, M.J.; Fabis-Pedrini, M.; Kermode, A.; Mrabet, S.; Gouider, R.; Hodgkinson, S.; Laureys, G.; Van Hijfte, L.; Macdonell, R.; Oreja-Guevara, C.; Cristiano, E.; McCombe, P.; Sanchez-Menoyo, J.L.; Singhal, B.; Blanco, Y.; Hughes, S.; Garber, J.; Solaro, C.; McGuigan, C.; Taylor, B.; de Gans, K.; Habek, M.; Al-Asmi, A.; Mihaela, S.; Castillo Triviño, T.; Al-Harbi, T.; Rojas, J.I.; Gray, O.; Khuran,a D.; Van Wijmeersch, B.; Grigoriadis, N.; Inshasi, J.; Oh, J.; Aguera-Morales, E.; Fragoso, Y.; Moore, F.; Shaw, C.; Baghbanian, S.M.; Shuey, N.; Willekens, B.; Hardy, T.A.; Decoo, D.; Sempere, A.P.; Field, D.; Wynford-Thomas, R.; Cunniffe, NG.; Roos, I.; Malpas, C.B.; Coles, A.J.; Kalincik, T.; Brown, J.W.L., Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM), School of Medicine, Altıntaş, Ayşe (ORCID 0000-0002-8524-5087 & YÖK ID 11611), Daruwalla, C.; Shaygannejad, V.; Ozakbas, S.; Havrdova, EK.; Horakova, D.; Alroughani, R.; Boz, C.; Patti, F.; Onofrj, M.; Lugaresi, A.; Eichau, S.; Girard, M.; Prat, A.; Duquette, P.; Yamout, B.; Khoury, S.J.; Sajedi, S.A.; Turkoglu, R.; Skibina, O.; Buzzard, K.; Grammond, P.; Karabudak, R.; van der Walt, A.; Butzkueven, H.; Maimone, D.; Lechner-Scott, J.; Soysal, A.; John, N.; Prevost, J.; Spitaleri, D.; Ramo-Tello, C.; Gerlach, O.; Iuliano, G.; Foschi, M.; Ampapa, R.; van Pesch, V.; Barnett, M.; Shalaby, N.; D'hooghe, M.; Kuhle, J.; Sa, M.J.; Fabis-Pedrini, M.; Kermode, A.; Mrabet, S.; Gouider, R.; Hodgkinson, S.; Laureys, G.; Van Hijfte, L.; Macdonell, R.; Oreja-Guevara, C.; Cristiano, E.; McCombe, P.; Sanchez-Menoyo, J.L.; Singhal, B.; Blanco, Y.; Hughes, S.; Garber, J.; Solaro, C.; McGuigan, C.; Taylor, B.; de Gans, K.; Habek, M.; Al-Asmi, A.; Mihaela, S.; Castillo Triviño, T.; Al-Harbi, T.; Rojas, J.I.; Gray, O.; Khuran,a D.; Van Wijmeersch, B.; Grigoriadis, N.; Inshasi, J.; Oh, J.; Aguera-Morales, E.; Fragoso, Y.; Moore, F.; Shaw, C.; Baghbanian, S.M.; Shuey, N.; Willekens, B.; Hardy, T.A.; Decoo, D.; Sempere, A.P.; Field, D.; Wynford-Thomas, R.; Cunniffe, NG.; Roos, I.; Malpas, C.B.; Coles, A.J.; Kalincik, T.; Brown, J.W.L., Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM), and School of Medicine

Abstract

Background: the prognostic significance of non-disabling relapses in people with relapsing-remitting multiple sclerosis (RRMS) is unclear. Objective: to determine whether early non-disabling relapses predict disability accumulation in RRMS. Methods: we redefined mild relapses in MSBase as 'non-disabling', and moderate or severe relapses as 'disabling'. We used mixed-effects Cox models to compare 90-day confirmed disability accumulation events in people with exclusively non-disabling relapses within 2 years of RRMS diagnosis to those with no early relapses; and any early disabling relapses. Analyses were stratified by disease-modifying therapy (DMT) efficacy during follow-up. Results: people who experienced non-disabling relapses within 2 years of RRMS diagnosis accumulated more disability than those with no early relapses if they were untreated (n = 285 vs 4717; hazard ratio (HR) = 1.29, 95% confidence interval (CI) = 1.00-1.68) or given platform DMTs (n = 1074 vs 7262; HR = 1.33, 95% CI = 1.15-1.54), but not if given high-efficacy DMTs (n = 572 vs 3534; HR = 0.90, 95% CI = 0.71-1.13) during follow-up. Differences in disability accumulation between those with early non-disabling relapses and those with early disabling relapses were not confirmed statistically. Conclusion: this study suggests that early non-disabling relapses are associated with a higher risk of disability accumulation than no early relapses in RRMS. This risk may be mitigated by high-efficacy DMTs. Therefore, non-disabling relapses should be considered when making treatment decisions., The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was financially supported by National Health and Medical Research Council of Australia (fellowship nos.1140766 and 1080518, project grant nos. 1129189 and 1083539), the University of Melbourne (Faculty of Medicine, Dentistry and Health Sciences research fellowship), National Institute for Health and Care Research (UK) Advanced Fellowship (grant no. 301728; recipient JWLB) and Academic Clinical Fellowship (grant no. EAN/ACA-006/7488627/C; recipient CD). The MSBase Foundation is a not-for-profit organization that receives support from Roche, Merck, Biogen, Novartis, Bayer Schering, Sanofi Genzyme, and Teva. Role of the Funder/Sponsor: The National Health and Medical Research Council of Australia, the University of Melbourne and the National Institute for Health and Care Research (UK) had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Published
2023

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