91 results on '"Gerlach O."'
Search Results
2. Comparative effectiveness and cost-effectiveness of natalizumab and fingolimod in rapidly evolving severe relapsing-remitting multiple sclerosis in the United Kingdom
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Spelman, T, primary, Herring, WL, additional, Acosta, C, additional, Hyde, R, additional, Jokubaitis, VG, additional, Pucci, E, additional, Lugaresi, A, additional, Laureys, G, additional, Havrdova, EK, additional, Horakova, D, additional, Izquierdo, G, additional, Eichau, S, additional, Ozakbas, S, additional, Alroughani, R, additional, Kalincik, T, additional, Duquette, P, additional, Girard, M, additional, Petersen, T, additional, Patti, F, additional, Csepany, T, additional, Granella, F, additional, Grand’Maison, F, additional, Ferraro, D, additional, Karabudak, R, additional, Jose Sa, M, additional, Trojano, M, additional, van Pesch, V, additional, Van Wijmeersch, B, additional, Cartechini, E, additional, McCombe, P, additional, Gerlach, O, additional, Spitaleri, D, additional, Rozsa, C, additional, Hodgkinson, S, additional, Bergamaschi, R, additional, Gouider, R, additional, Soysal, A, additional, Castillo-Triviño, T, additional, Prevost, J, additional, Garber, J, additional, de Gans, K, additional, Ampapa, R, additional, Simo, M, additional, Sanchez-Menoyo, JL, additional, Iuliano, G, additional, Sas, A, additional, van der Walt, A, additional, John, N, additional, Gray, O, additional, Hughes, S, additional, De Luca, G, additional, Onofrj, M, additional, Buzzard, K, additional, Skibina, O, additional, Terzi, M, additional, Slee, M, additional, Solaro, C, additional, Oreja-Guevara, C, additional, Ramo-Tello, C, additional, Fragoso, Y, additional, Shaygannejad, V, additional, Moore, F, additional, Rajda, C, additional, Aguera Morales, E, additional, and Butzkueven, H, additional
- Published
- 2023
- Full Text
- View/download PDF
3. Green Synthesis of Gold Nanoparticles Obtained from Algae Sargassum cymosum: Optimization, Characterization and Stability
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Costa, L. H., Hemmer, J.V., Wanderlind, E. H., Gerlach, O. M. S., Santos, A. L. H., Tamanaha, M. S., Bella-Cruz, A., Corrêa, R., Bazani, H. A. G., Radetski, C. M., and Almerindo, G. I.
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- 2020
- Full Text
- View/download PDF
4. Comparative effectiveness in multiple sclerosis: A methodological comparison
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Roos, I, Diouf, I, Sharmin, S, Horakova, D, Havrdova, EK, Patti, F, Shaygannejad, V, Ozakbas, S, Izquierdo, G, Eichau, S, Onofrj, M, Lugaresi, A, Alroughani, R, Prat, A, Girard, M, Duquette, P, Terzi, M, Boz, C, Grand'Maison, F, Sola, P, Ferraro, D, Grammond, P, Turkoglu, R, Buzzard, K, Skibina, O, Yamou, B, Altintas, A, Gerlach, O, van Pesch, V, Blanco, Y, Maimone, D, Lechner-Scott, J, Bergamaschi, R, Karabudak, R, McGuigan, C, Cartechini, E, Barnett, M, Hughes, S, Sa, MJ, Solaro, C, Ramo-Tello, C, Hodgkinson, S, Spitaleri, D, Soysal, A, Petersen, T, Granella, F, de Gans, K, McCombe, P, Ampapa, R, Van Wijmeersch, B, van der Walt, A, Butzkueven, H, Prevost, J, Sanchez-Menoyo, JL, Laureys, G, Gouider, R, Castillo-Trivino, T, Gray, O, Aguera-Morales, E, Al-Asmi, A, Shaw, C, Deri, N, Al-Harbi, T, Fragoso, Y, Csepany, T, Sempere, AP, Trevino-Frenk, I, Schepel, J, Moore, F, Malpas, C, Kalincik, T, Roos, I, Diouf, I, Sharmin, S, Horakova, D, Havrdova, EK, Patti, F, Shaygannejad, V, Ozakbas, S, Izquierdo, G, Eichau, S, Onofrj, M, Lugaresi, A, Alroughani, R, Prat, A, Girard, M, Duquette, P, Terzi, M, Boz, C, Grand'Maison, F, Sola, P, Ferraro, D, Grammond, P, Turkoglu, R, Buzzard, K, Skibina, O, Yamou, B, Altintas, A, Gerlach, O, van Pesch, V, Blanco, Y, Maimone, D, Lechner-Scott, J, Bergamaschi, R, Karabudak, R, McGuigan, C, Cartechini, E, Barnett, M, Hughes, S, Sa, MJ, Solaro, C, Ramo-Tello, C, Hodgkinson, S, Spitaleri, D, Soysal, A, Petersen, T, Granella, F, de Gans, K, McCombe, P, Ampapa, R, Van Wijmeersch, B, van der Walt, A, Butzkueven, H, Prevost, J, Sanchez-Menoyo, JL, Laureys, G, Gouider, R, Castillo-Trivino, T, Gray, O, Aguera-Morales, E, Al-Asmi, A, Shaw, C, Deri, N, Al-Harbi, T, Fragoso, Y, Csepany, T, Sempere, AP, Trevino-Frenk, I, Schepel, J, Moore, F, Malpas, C, and Kalincik, T
- Abstract
BACKGROUND: In the absence of evidence from randomised controlled trials, observational data can be used to emulate clinical trials and guide clinical decisions. Observational studies are, however, susceptible to confounding and bias. Among the used techniques to reduce indication bias are propensity score matching and marginal structural models. OBJECTIVE: To use the comparative effectiveness of fingolimod vs natalizumab to compare the results obtained with propensity score matching and marginal structural models. METHODS: Patients with clinically isolated syndrome or relapsing remitting MS who were treated with either fingolimod or natalizumab were identified in the MSBase registry. Patients were propensity score matched, and inverse probability of treatment weighted at six monthly intervals, using the following variables: age, sex, disability, MS duration, MS course, prior relapses, and prior therapies. Studied outcomes were cumulative hazard of relapse, disability accumulation, and disability improvement. RESULTS: 4608 patients (1659 natalizumab, 2949 fingolimod) fulfilled inclusion criteria, and were propensity score matched or repeatedly reweighed with marginal structural models. Natalizumab treatment was associated with a lower probability of relapse (PS matching: HR 0.67 [95% CI 0.62-0.80]; marginal structural model: 0.71 [0.62-0.80]), and higher probability of disability improvement (PS matching: 1.21 [1.02 -1.43]; marginal structural model 1.43 1.19 -1.72]). There was no evidence of a difference in the magnitude of effect between the two methods. CONCLUSIONS: The relative effectiveness of two therapies can be efficiently compared by either marginal structural models or propensity score matching when applied in clearly defined clinical contexts and in sufficiently powered cohorts.
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- 2023
5. Early non-disabling relapses are important predictors of disability accumulation in people with relapsing-remitting multiple sclerosis
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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.
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- 2023
6. Early non-disabling relapses are important predictors of disability accumulation in people with relapsing-remitting multiple sclerosis
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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.
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- 2023
7. Early non-disabling relapses are associated with a higher risk of disability accumulation in people with relapsing-remitting multiple sclerosis
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Coles, A., Daruwalla, C., Shaygannejad, V., Ozakbas, S., Havrdova, E. K., Alroughani, R., Patti, F., Onofrj, M., Eichau, S., Girard, M., Grand'Maison, F., Yamout, B., Sajedi, S. A., Amato, M. P., Altintas, A., Skibina, O., Grammond, P., Butzkueven, H., Maimone, D., Lechner-Scott, J., Soysal, A., John, N., Gerlach, O., Iuliano, G., Foschi, M., Van Pesch, V., Cartechini, E., Kuhle, J., Sa, M. J., Kermode, A., Gouider, R., Hodgkinson, S., McCombe, P., Sanchez-Menoyo, J. L., Singhal, B., Blanco, Y., Hughes, S., McGuigan, C., Taylor, B., Habek, M., Al-Asmi, A., Mihaela, S., Castillo Trivino, T., Al-Harbi, T., Rojas, J. I., Gray, O., Khurana, D., Van Wijmeersch, B., Kalincik, T., and Brown, J. W. L.
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- 2022
8. The risk of secondary progressive multiple sclerosis is geographically determined but modifiable
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Butler, E., Van Pesch, V., Shalaby, N., Kermode, A., Maimone, D., Blanco, Y., Altintas, A., Turkoglu, R., Butzkueven, H., Van der Walt, A., Skibina, O., Buzzard, K., Lechner-Scott, J., Grammond, P., Khoury, S. J., Yamout, B., Grand'Maison, F., Karabudak, R., Amato, M. P., Terzi, M., Duquette, P., Girard, M., Prat, A., Weinstock-Guttman, B., Lugaresi, A., Onofrj, M., Zakaria, M., Boz, C., Eichau, S., Izquierdo, G., Shaygannejad, V., Alroughani, R., Patti, F., Havrdova, E. K., Horakova, D., Ozakbas, S., Sanchez, M. Martinez, Malpas, C., Simpson-Yap, S., Roos, I., Sharmin, S., Sidhom, Y., Gouider, R., Gerlach, O., Soysal, A., Barnett, M., Kuhle, J., Hughes, S., Sa, M. Jose, and Kalincik, T.
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- 2022
9. Efficacy and persistence between dimethyl fumarate, fingolimod, and ocrelizumab after natalizumab cessation
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Macdonell, R., Zhu, C., Kalincik, T., Horakova, D., Zhen, Z., Buzzard, K., Skibina, O., Alroughani, R., Izquierdo, G., Eichau, S., Kuhle, J., Patti, F., Grand'Maison, F., Hodgkinson, S., Grammond, P., Lechner-Scott, J., Butler, E., Prat, A., Girard, M., Butzkueven, H., Van der Walt, A., Merlo, D., Monif, M., Jokubaitis, V., Khoury, S. J., Yamout, B., Garber, J., Kermode, A., Van Hijfte, L., Laureys, G., Boz, C., Terzi, M., Prevost, J., Gerlach, O., Van Wijmeersch, B., Barnett, M., Van Pesch, V., Sa, M. Jose, Slee, M., Ozakbas, S., Weinstock-Guttman, B., and Duquette, P.
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- 2022
10. Real-World Comparative Effectiveness and Persistence of Cladribine Tablets and Other Oral Disease-Modifying Treatments for Multiple Sclerosis from GLIMPSE: Results from the MSBase Registry
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Spitaleri, D., Kuhle, J., Ozakbas, SERKAN, Patti, F., Ampapa, R., Horakova, D., Soysal, A., Butzkueven, H., Spelman, T., Lechner-Scott, J., Yamout, B., Alroughani, R., Terzi, M., Hodgkinson, S., Sanchez-Menoyo, J., Blanco, Y., Van Pesch, V., Van der Walt, A., Kalincik, T., Laureys, G., Wong, S., Tundia, N., Altintas, A., Oh, J., Gerlach, O., Al-Asmi, A., and Macdonell, R.
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- 2022
11. Association of Latitude and Exposure to Ultraviolet B Radiation With Severity of Multiple Sclerosis: An International Registry Study.
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Vitkova M., Diouf I., Malpas C., Horakova D., Havrdova E.K., Patti F., Ozakbas S., Izquierdo G., Eichau S., Shaygannejad V., Onofrj M., Lugaresi A., Alroughani R., Prat A., Larochelle C., Girard M., Duquette P., Terzi M., Boz C., Grand'Maison F., Sola P., Ferraro D., Grammond P., Butzkueven H., Buzzard K., Skibina O., Yamout B.I., Karabudak R., Gerlach O., Lechner-Scott J., Maimone D., Bergamaschi R., Van Pesch V., Iuliano G., Cartechini E., JosA Sa M., Ampapa R., Barnett M., Hughes S.E., Ramo-Tello C.M., Hodgkinson S., Spitaleri D.L.A., Petersen T., Butler E.G., Slee M., McGuigan C., McCombe P.A., Granella F., Cristiano E., Prevost J., Taylor B.V., Sa Nchez-Menoyo J.L., Laureys G., Van Hijfte L., Vucic S., Macdonell R.A., Gray O., Olascoaga J., Deri N., Fragoso Y.D., Shaw C., Kalincik T., Vitkova M., Diouf I., Malpas C., Horakova D., Havrdova E.K., Patti F., Ozakbas S., Izquierdo G., Eichau S., Shaygannejad V., Onofrj M., Lugaresi A., Alroughani R., Prat A., Larochelle C., Girard M., Duquette P., Terzi M., Boz C., Grand'Maison F., Sola P., Ferraro D., Grammond P., Butzkueven H., Buzzard K., Skibina O., Yamout B.I., Karabudak R., Gerlach O., Lechner-Scott J., Maimone D., Bergamaschi R., Van Pesch V., Iuliano G., Cartechini E., JosA Sa M., Ampapa R., Barnett M., Hughes S.E., Ramo-Tello C.M., Hodgkinson S., Spitaleri D.L.A., Petersen T., Butler E.G., Slee M., McGuigan C., McCombe P.A., Granella F., Cristiano E., Prevost J., Taylor B.V., Sa Nchez-Menoyo J.L., Laureys G., Van Hijfte L., Vucic S., Macdonell R.A., Gray O., Olascoaga J., Deri N., Fragoso Y.D., Shaw C., and Kalincik T.
- Abstract
BACKGROUND AND OBJECTIVES: The severity of multiple sclerosis (MS) varies widely among individuals. Understanding the determinants of this heterogeneity will help clinicians optimize the management of MS. The aim of this study was to investigate the association between latitude of residence, ultraviolet B radiation exposure (UVB) and the severity of MS. METHOD(S): This observational study used the MSBase registry data. The included patients met the 2005 or 2010 McDonald diagnostic criteria for MS and had a minimum dataset recorded in the registry (date of birth, sex, clinic location, date of MS symptom onset, disease phenotype at baseline and censoring, and >=1 EDSS [Expanded Disability Status Scale] score recorded). The latitude of each study center and cumulative annualized UVB dose at study center (calculated from NASA's Total Ozone Mapping Spectrometer) at ages 6 and 18 and the year of disability assessment were calculated. Disease severity was quantified with MS Severity Score (MSSS). Quadratic regression was used to model the associations between latitude, UVB and MSSS. RESULT(S): 46,128 patients contributing 453,208 visits and a cumulative follow-up of 351,196 patient-years (70% women, mean age 39.2+/-12, resident between latitudes 19degree35' and 56degree16') were included in this study. Latitude showed a non-linear association with MS severity. In latitudes greater than 40degree, more severe disease was associated with higher latitudes (beta=0.08, 95%CI: 0.04 to 0.12). For example, this translates into a mean difference of 1.3 points of MSSS between patients living in Madrid and Copenhagen. No such association was observed in latitudes <40degree (beta=-0.02, 95% CI:-0.06 to 0.03). The overall disability accrual was faster in those with a lower level of estimated UVB exposure before the age of 6 (beta=- 0.5, 95% CI: -0.6 to 0.4) and 18 years (beta=- 0.6, 95%CI:-0.7 to 0.4), as well as with lower life-time UVB exposure at the time of disability assessment (be
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- 2022
12. Confirmed disability progression as a marker of permanent disability in multiple sclerosis.
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Sharmin S., Bovis F., Malpas C., Horakova D., Havrdova E., Izquierdo G., Eichau S., Trojano M., Prat A., Girard M., Duquette P., Onofrj M., Lugaresi A., Grand'Maison F., Grammond P., Sola P., Ferraro D., Terzi M., Gerlach O., Alroughani R., Boz C., Shaygannejad V., van Pesch V., Cartechini E., Kappos L., Lechner-Scott J., Bergamaschi R., Turkoglu R., Solaro C., Iuliano G., Granella F., Van Wijmeersch B., Spitaleri D., Slee M., McCombe P., Prevost J., Ampapa R., Ozakbas S., Sanchez-Menoyo J., Soysal A., Vucic S., Petersen T., de Gans K., Butler E., Hodgkinson S., Sidhom Y., Gouider R., Cristiano E., Castillo-Trivino T., Saladino M., Barnett M., Moore F., Rozsa C., Yamout B., Skibina O., van der Walt A., Buzzard K., Gray O., Hughes S., Sempere A.P., Singhal B., Fragoso Y., Shaw C., Kermode A., Taylor B., Simo M., Shuey N., Al-Harbi T., Macdonell R., Dominguez J.A., Csepany T., Sirbu C., Sormani M.P., Butzkueven H., Kalincik T., Sharmin S., Bovis F., Malpas C., Horakova D., Havrdova E., Izquierdo G., Eichau S., Trojano M., Prat A., Girard M., Duquette P., Onofrj M., Lugaresi A., Grand'Maison F., Grammond P., Sola P., Ferraro D., Terzi M., Gerlach O., Alroughani R., Boz C., Shaygannejad V., van Pesch V., Cartechini E., Kappos L., Lechner-Scott J., Bergamaschi R., Turkoglu R., Solaro C., Iuliano G., Granella F., Van Wijmeersch B., Spitaleri D., Slee M., McCombe P., Prevost J., Ampapa R., Ozakbas S., Sanchez-Menoyo J., Soysal A., Vucic S., Petersen T., de Gans K., Butler E., Hodgkinson S., Sidhom Y., Gouider R., Cristiano E., Castillo-Trivino T., Saladino M., Barnett M., Moore F., Rozsa C., Yamout B., Skibina O., van der Walt A., Buzzard K., Gray O., Hughes S., Sempere A.P., Singhal B., Fragoso Y., Shaw C., Kermode A., Taylor B., Simo M., Shuey N., Al-Harbi T., Macdonell R., Dominguez J.A., Csepany T., Sirbu C., Sormani M.P., Butzkueven H., and Kalincik T.
- Abstract
Background and purpose: The prevention of disability over the long term is the main treatment goal in multiple sclerosis (MS); however, randomized clinical trials evaluate only short-term treatment effects on disability. This study aimed to define criteria for 6-month confirmed disability progression events of MS with a high probability of resulting in sustained long-term disability worsening. Method(s): In total, 14,802 6-month confirmed disability progression events were identified in 8741 patients from the global MSBase registry. For each 6-month confirmed progression event (13,321 in the development and 1481 in the validation cohort), a sustained progression score was calculated based on the demographic and clinical characteristics at the time of progression that were predictive of long-term disability worsening. The score was externally validated in the Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) trial. Result(s): The score was based on age, sex, MS phenotype, relapse activity, disability score and its change from baseline, number of affected functional system domains and worsening in six of the domains. In the internal validation cohort, a 61% lower chance of improvement was estimated with each unit increase in the score (hazard ratio 0.39, 95% confidence interval 0.29-0.52; discriminatory index 0.89). The proportions of progression events sustained at 5 years stratified by the score were 1: 72%; 2: 88%; 3: 94%; 4: 100%. The results of the CLARITY trial were confirmed for reduction of disability progression that was >88% likely to be sustained (events with score >1.5). Conclusion(s): Clinicodemographic characteristics of 6-month confirmed disability progression events identify those at high risk of sustained long-term disability. This knowledge will allow future trials to better assess the effect of therapy on long-term disability accrual.Copyright © 2022 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behal
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- 2022
13. Disease Reactivation After Cessation of Disease-Modifying Therapy in Patients With Relapsing-Remitting Multiple Sclerosis.
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Roos I., Malpas C., Leray E., Casey R., Horakova D., Havrdova E.K., Debouverie M., Patti F., De Seze J., Izquierdo G., Eichau S., Edan G., Prat A., Girard M., Ozakbas S., Grammond P., Zephir H., Ciron J., Maillart E., Moreau T., Amato M.P., Labauge P., Alroughani R., Buzzard K., Skibina O., Terzi M., Laplaud D.A., Berger E., Grand'Maison F., Lebrun-Frenay C., Cartechini E., Boz C., Lechner-Scott J., Clavelou P., Stankoff B., Prevost J., Kappos L., Pelletier J., Shaygannejad V., Yamout B.I., Khoury S.J., Gerlach O., Spitaleri D.L.A., Van Pesch V., Gout O., Turkoglu R., Heinzlef O., Thouvenot E., McCombe P.A., Soysal A., Bourre B., Slee M., Castillo-Trivino T., Bakchine S., Ampapa R., Butler E.G., Wahab A., Macdonell R.A., Aguera-Morales E., Cabre P., Ben N.H., Van der Walt A., Laureys G., Van Hijfte L., Ramo-Tello C.M., Maubeuge N., Hodgkinson S., Sanchez-Menoyo J.L., Barnett M.H., Labeyrie C., Vucic S., Sidhom Y., Gouider R., Csepany T., Sotoca J., de Gans K., Al-Asmi A., Fragoso Y.D., Vukusic S., Butzkueven H., Kalincik T., Roos I., Malpas C., Leray E., Casey R., Horakova D., Havrdova E.K., Debouverie M., Patti F., De Seze J., Izquierdo G., Eichau S., Edan G., Prat A., Girard M., Ozakbas S., Grammond P., Zephir H., Ciron J., Maillart E., Moreau T., Amato M.P., Labauge P., Alroughani R., Buzzard K., Skibina O., Terzi M., Laplaud D.A., Berger E., Grand'Maison F., Lebrun-Frenay C., Cartechini E., Boz C., Lechner-Scott J., Clavelou P., Stankoff B., Prevost J., Kappos L., Pelletier J., Shaygannejad V., Yamout B.I., Khoury S.J., Gerlach O., Spitaleri D.L.A., Van Pesch V., Gout O., Turkoglu R., Heinzlef O., Thouvenot E., McCombe P.A., Soysal A., Bourre B., Slee M., Castillo-Trivino T., Bakchine S., Ampapa R., Butler E.G., Wahab A., Macdonell R.A., Aguera-Morales E., Cabre P., Ben N.H., Van der Walt A., Laureys G., Van Hijfte L., Ramo-Tello C.M., Maubeuge N., Hodgkinson S., Sanchez-Menoyo J.L., Barnett M.H., Labeyrie C., Vucic S., Sidhom Y., Gouider R., Csepany T., Sotoca J., de Gans K., Al-Asmi A., Fragoso Y.D., Vukusic S., Butzkueven H., and Kalincik T.
- Abstract
OBJECTIVES: To evaluate the rate of return of disease activity after cessation of multiple sclerosis (MS) disease-modifying therapy. METHOD(S): This was a retrospective cohort study from two large observational MS registries: MSBase and OFSEP. Patients with relapsing-remitting MS who had ceased a disease-modifying therapy and were followed up for the subsequent 12-months were included in the analysis. The primary study outcome was annualised relapse rate in the 12 months after disease-modifying therapy discontinuation stratified by patients who did, and did not, commence a subsequent therapy. The secondary endpoint was the predictors of first relapse and disability accumulation after treatment discontinuation. RESULT(S): 14,213 patients, with 18,029 eligible treatment discontinuation epochs, were identified for seven therapies. Annualised rates of relapse (ARR) started to increase 2-months after natalizumab cessation (month 2-4 ARR, 95% confidence interval): 0.47, 0.43-0.51). Commencement of a subsequent therapy within 2-4 months reduced the magnitude of disease reactivation (mean ARR difference: 0.15, 0.08-0.22). After discontinuation of fingolimod, rates of relapse increased overall (month 1-2 ARR: 0.80, 0.70-0.89), and stabilised faster in patients who started a new therapy within 1-2 months (mean ARR difference: 0.14, -0.01-0.29). Magnitude of disease reactivation for other therapies was low, but reduced further by commencement of another treatment 1-10 months after treatment discontinuation. Predictors of relapse were higher relapse rate in the year before cessation, female sex, younger age and higher EDSS. Commencement of a subsequent therapy reduced both the risk of relapse (HR 0.76, 95%CI 0.72-0.81) and disability accumulation (0.73, 0.65-0.80). CONCLUSION(S): The rate of disease reactivation after treatment cessation differs among MS treatments, with the peaks of relapse activity ranging from 1 to 10 months in untreated cohorts that discontinued different t
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- 2022
14. Confirmed disability progression as a marker of permanent disability in multiple sclerosis
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Sharmin, S., Bovis, F., Malpas, C., Horakova, D., Havrdova, E.K., Izquierdo, G., Eichau, S., Trojano, M., Prat, A., Girard, M., Duquette, P., Onofrj, M., Lugaresi, A., Grand'Maison, F., Grammond, P., Sola, P., Ferraro, D., Terzi, M., Gerlach, O., Alroughani, R., Boz, C., Shaygannejad, V., van Pesch, V., Cartechini, E., Kappos, L., Lechner‐Scott, J., Bergamaschi, R., Turkoglu, R., Solaro, C., Iuliano, G., Granella, F., Van Wijmeersch, B., Spitaleri, D., Slee, M., McCombe, P., Prevost, J., Ampapa, R., Ozakbas, S., Sanchez‐Menoyo, J.L., Soysal, A., Vucic, S., Petersen, T., de Gans, K., Butler, E., Hodgkinson, S., Sidhom, Y., Gouider, R., Cristiano, E., Castillo‐Triviño, T., Saladino, M.L., Barnett, M., Moore, F., Rozsa, C., Yamout, B., Skibina, O., van der Walt, A., Buzzard, K., Gray, O., Hughes, S., Sempere, A.P., Singhal, B., Fragoso, Y., Shaw, C., Kermode, A., Taylor, B., Simo, M., Shuey, N., Al‐Harbi, T., Macdonell, R., Dominguez, J.A., Csepany, T., Sirbu, C.A., Sormani, M.P., Butzkueven, H., Kalincik, T., Sharmin, S., Bovis, F., Malpas, C., Horakova, D., Havrdova, E.K., Izquierdo, G., Eichau, S., Trojano, M., Prat, A., Girard, M., Duquette, P., Onofrj, M., Lugaresi, A., Grand'Maison, F., Grammond, P., Sola, P., Ferraro, D., Terzi, M., Gerlach, O., Alroughani, R., Boz, C., Shaygannejad, V., van Pesch, V., Cartechini, E., Kappos, L., Lechner‐Scott, J., Bergamaschi, R., Turkoglu, R., Solaro, C., Iuliano, G., Granella, F., Van Wijmeersch, B., Spitaleri, D., Slee, M., McCombe, P., Prevost, J., Ampapa, R., Ozakbas, S., Sanchez‐Menoyo, J.L., Soysal, A., Vucic, S., Petersen, T., de Gans, K., Butler, E., Hodgkinson, S., Sidhom, Y., Gouider, R., Cristiano, E., Castillo‐Triviño, T., Saladino, M.L., Barnett, M., Moore, F., Rozsa, C., Yamout, B., Skibina, O., van der Walt, A., Buzzard, K., Gray, O., Hughes, S., Sempere, A.P., Singhal, B., Fragoso, Y., Shaw, C., Kermode, A., Taylor, B., Simo, M., Shuey, N., Al‐Harbi, T., Macdonell, R., Dominguez, J.A., Csepany, T., Sirbu, C.A., Sormani, M.P., Butzkueven, H., and Kalincik, T.
- Abstract
Background and purpose The prevention of disability over the long term is the main treatment goal in multiple sclerosis (MS); however, randomized clinical trials evaluate only short-term treatment effects on disability. This study aimed to define criteria for 6-month confirmed disability progression events of MS with a high probability of resulting in sustained long-term disability worsening. Methods In total, 14,802 6-month confirmed disability progression events were identified in 8741 patients from the global MSBase registry. For each 6-month confirmed progression event (13,321 in the development and 1481 in the validation cohort), a sustained progression score was calculated based on the demographic and clinical characteristics at the time of progression that were predictive of long-term disability worsening. The score was externally validated in the Cladribine Tablets Treating Multiple Sclerosis Orally (CLARITY) trial. Results The score was based on age, sex, MS phenotype, relapse activity, disability score and its change from baseline, number of affected functional system domains and worsening in six of the domains. In the internal validation cohort, a 61% lower chance of improvement was estimated with each unit increase in the score (hazard ratio 0.39, 95% confidence interval 0.29–0.52; discriminatory index 0.89). The proportions of progression events sustained at 5 years stratified by the score were 1: 72%; 2: 88%; 3: 94%; 4: 100%. The results of the CLARITY trial were confirmed for reduction of disability progression that was >88% likely to be sustained (events with score ˃1.5). Conclusions Clinicodemographic characteristics of 6-month confirmed disability progression events identify those at high risk of sustained long-term disability. This knowledge will allow future trials to better assess the effect of therapy on long-term disability accrual.
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- 2022
15. Disease Reactivation After Cessation of Disease-Modifying Therapy in Patients With Relapsing-Remitting Multiple Sclerosis
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Roos, I, Malpas, C, Leray, E, Casey, R, Horakova, D, Havrdova, EK, Debouverie, M, Patti, F, De Seze, J, Izquierdo, G, Eichau, S, Edan, G, Prat, A, Girard, M, Ozakbas, S, Grammond, P, Zephir, H, Ciron, J, Maillart, E, Moreau, T, Amato, MP, Labauge, P, Alroughani, R, Buzzard, K, Skibina, O, Terzi, M, Laplaud, DA, Berger, E, Grand'Maison, F, Lebrun-Frenay, C, Cartechini, E, Boz, C, Lechner-Scott, J, Clavelou, P, Stankoff, B, Prevost, J, Kappos, L, Pelletier, J, Shaygannejad, V, Yamout, B, Khoury, SJ, Gerlach, O, Spitaleri, DLA, Van Pesch, V, Gout, O, Turkoglu, R, Heinzlef, O, Thouvenot, E, McCombe, PA, Soysal, A, Bourre, B, Slee, M, Castillo-Trivino, T, Bakchine, S, Ampapa, R, Butler, EG, Wahab, A, Macdonell, RA, Aguera-Morales, E, Cabre, P, Ben, NH, Van der Walt, A, Laureys, G, Van Hijfte, L, Ramo-Tello, CM, Maubeuge, N, Hodgkinson, S, Sanchez-Menoyo, JL, Barnett, MH, Labeyrie, C, Vucic, S, Sidhom, Y, Gouider, R, Csepany, T, Sotoca, J, de Gans, K, Al-Asmi, A, Fragoso, YD, Vukusic, S, Butzkueven, H, Kalincik, T, Roos, I, Malpas, C, Leray, E, Casey, R, Horakova, D, Havrdova, EK, Debouverie, M, Patti, F, De Seze, J, Izquierdo, G, Eichau, S, Edan, G, Prat, A, Girard, M, Ozakbas, S, Grammond, P, Zephir, H, Ciron, J, Maillart, E, Moreau, T, Amato, MP, Labauge, P, Alroughani, R, Buzzard, K, Skibina, O, Terzi, M, Laplaud, DA, Berger, E, Grand'Maison, F, Lebrun-Frenay, C, Cartechini, E, Boz, C, Lechner-Scott, J, Clavelou, P, Stankoff, B, Prevost, J, Kappos, L, Pelletier, J, Shaygannejad, V, Yamout, B, Khoury, SJ, Gerlach, O, Spitaleri, DLA, Van Pesch, V, Gout, O, Turkoglu, R, Heinzlef, O, Thouvenot, E, McCombe, PA, Soysal, A, Bourre, B, Slee, M, Castillo-Trivino, T, Bakchine, S, Ampapa, R, Butler, EG, Wahab, A, Macdonell, RA, Aguera-Morales, E, Cabre, P, Ben, NH, Van der Walt, A, Laureys, G, Van Hijfte, L, Ramo-Tello, CM, Maubeuge, N, Hodgkinson, S, Sanchez-Menoyo, JL, Barnett, MH, Labeyrie, C, Vucic, S, Sidhom, Y, Gouider, R, Csepany, T, Sotoca, J, de Gans, K, Al-Asmi, A, Fragoso, YD, Vukusic, S, Butzkueven, H, and Kalincik, T
- Abstract
BACKGROUND AND OBJECTIVES: To evaluate the rate of return of disease activity after cessation of multiple sclerosis (MS) disease-modifying therapy. METHODS: This was a retrospective cohort study from 2 large observational MS registries: MSBase and OFSEP. Patients with relapsing-remitting MS who had ceased a disease-modifying therapy and were followed up for the subsequent 12 months were included in the analysis. The primary study outcome was annualized relapse rate in the 12 months after disease-modifying therapy discontinuation stratified by patients who did, and did not, commence a subsequent therapy. The secondary endpoint was the predictors of first relapse and disability accumulation after treatment discontinuation. RESULTS: A total of 14,213 patients, with 18,029 eligible treatment discontinuation epochs, were identified for 7 therapies. Annualized rates of relapse (ARRs) started to increase 2 months after natalizumab cessation (month 2-4 ARR 0.47, 95% CI 0.43-0.51). Commencement of a subsequent therapy within 2-4 months reduced the magnitude of disease reactivation (mean ARR difference: 0.15, 0.08-0.22). After discontinuation of fingolimod, rates of relapse increased overall (month 1-2 ARR: 0.80, 0.70-0.89) and stabilized faster in patients who started a new therapy within 1-2 months (mean ARR difference: 0.14, -0.01 to 0.29). The magnitude of disease reactivation for other therapies was low but reduced further by commencement of another treatment 1-10 months after treatment discontinuation. Predictors of relapse were a higher relapse rate in the year before cessation, female sex, younger age, and higher EDSS score. Commencement of a subsequent therapy reduced both the risk of relapse (HR 0.76, 95% CI 0.72-0.81) and disability accumulation (0.73, 0.65-0.80). DISCUSSION: The rate of disease reactivation after treatment cessation differs among MS treatments, with the peaks of relapse activity ranging from 1 to 10 months in untreated cohorts that discontinued di
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- 2022
16. Multiple Sclerosis Severity Score (MSSS) improves the accuracy of individualized prediction in MS
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Kalincik, T, Kister, I, Bacon, TE, Malpas, CB, Sharmin, S, Horakova, D, Kubala-Havrdova, E, Patti, F, Izquierdo, G, Eichau, S, Ozakbas, S, Onofrj, M, Lugaresi, A, Prat, A, Girard, M, Duquette, P, Grammond, P, Sola, P, Ferraro, D, Alroughani, R, Terzi, M, Boz, C, Grand'Maison, F, Bergamaschi, R, Gerlach, O, Sa, MJ, Kappos, L, Cartechini, E, Lechner-Scott, J, van Pesch, V, Shaygannejad, V, Granella, F, Spitaleri, D, Iuliano, G, Maimone, D, Prevost, J, Soysal, A, Turkoglu, R, Ampapa, R, Butzkueven, H, Cutter, G, Kalincik, T, Kister, I, Bacon, TE, Malpas, CB, Sharmin, S, Horakova, D, Kubala-Havrdova, E, Patti, F, Izquierdo, G, Eichau, S, Ozakbas, S, Onofrj, M, Lugaresi, A, Prat, A, Girard, M, Duquette, P, Grammond, P, Sola, P, Ferraro, D, Alroughani, R, Terzi, M, Boz, C, Grand'Maison, F, Bergamaschi, R, Gerlach, O, Sa, MJ, Kappos, L, Cartechini, E, Lechner-Scott, J, van Pesch, V, Shaygannejad, V, Granella, F, Spitaleri, D, Iuliano, G, Maimone, D, Prevost, J, Soysal, A, Turkoglu, R, Ampapa, R, Butzkueven, H, and Cutter, G
- Abstract
BACKGROUND: The MSBase prediction model of treatment response leverages multiple demographic and clinical characteristics to estimate hazards of relapses, confirmed disability accumulation (CDA), and confirmed disability improvement (CDI). The model did not include Multiple Sclerosis Severity Score (MSSS), a disease duration-adjusted ranked score of disability. OBJECTIVE: To incorporate MSSS into the MSBase prediction model and compare model accuracy with and without MSSS. METHODS: The associations between MSSS and relapse, CDA, and CDI were evaluated with marginal proportional hazards models adjusted for three principal components representative of patients' demographic and clinical characteristics. The model fit with and without MSSS was assessed with penalized r2 and Harrell C. RESULTS: A total of 5866 MS patients were started on disease-modifying therapy during prospective follow-up (age 38.4 ± 10.6 years; 72% female; disease duration 8.5 ± 7.7 years). Including MSSS into the model improved the accuracy of individual prediction of relapses by 31%, of CDA by 23%, and of CDI by 24% (Harrell C) and increased the amount of variance explained for relapses by 49%, for CDI by 11%, and for CDA by 10% as compared with the original model. CONCLUSION: Addition of a single, readily available metric, MSSS, to the comprehensive MSBase prediction model considerably improved the individual accuracy of prognostics in MS.
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- 2022
17. Comparative effectiveness of cladribine tablets versus other oral disease-modifying treatments for multiple sclerosis: Results from MSBase registry
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Spelman, T, Ozakbas, S, Alroughani, R, Terzi, M, Hodgkinson, S, Laureys, G, Kalincik, T, Van der Walt, A, Yamout, B, Lechner-Scott, J, Soysal, A, Kuhle, J, Sanchez-Menoyo, JL, Morgado, YB, La Spitaleri, D, van Pesch, V, Horakova, D, Ampapa, R, Patti, F, Macdonell, R, Al-Asmi, A, Gerlach, O, Oh, J, Altintas, A, Tundia, N, Wong, SL, Butzkueven, H, Spelman, T, Ozakbas, S, Alroughani, R, Terzi, M, Hodgkinson, S, Laureys, G, Kalincik, T, Van der Walt, A, Yamout, B, Lechner-Scott, J, Soysal, A, Kuhle, J, Sanchez-Menoyo, JL, Morgado, YB, La Spitaleri, D, van Pesch, V, Horakova, D, Ampapa, R, Patti, F, Macdonell, R, Al-Asmi, A, Gerlach, O, Oh, J, Altintas, A, Tundia, N, Wong, SL, and Butzkueven, H
- Abstract
BACKGROUND: Effectiveness of cladribine tablets, an oral disease-modifying treatment (DMT) for multiple sclerosis (MS), was established in clinical trials and confirmed with real-world experience. OBJECTIVES: Use real-world data to compare treatment patterns and clinical outcomes in people with MS (pwMS) treated with cladribine tablets versus other oral DMTs. METHODS: Retrospective treatment comparisons were based on data from the international MSBase registry. Eligible pwMS started treatment with cladribine, fingolimod, dimethyl fumarate, or teriflunomide tablets from 2018 to mid-2021 and were censored at treatment discontinuation/switch, death, loss to follow-up, pregnancy, or study period end. Treatment persistence was evaluated as time to discontinuation/switch; relapse outcomes included time to first relapse and annualized relapse rate (ARR). RESULTS: Cohorts included 633 pwMS receiving cladribine tablets, 1195 receiving fingolimod, 912 receiving dimethyl fumarate, and 735 receiving teriflunomide. Individuals treated with fingolimod, dimethyl fumarate, or teriflunomide switched treatment significantly more quickly than matched cladribine tablet cohorts (adjusted hazard ratio (95% confidence interval): 4.00 (2.54-6.32), 7.04 (4.16-11.93), and 6.52 (3.79-11.22), respectively). Cladribine tablet cohorts had significantly longer time-to-treatment discontinuation, time to first relapse, and lower ARR, compared with other oral DMT cohorts. CONCLUSION: Cladribine tablets were associated with a significantly greater real-world treatment persistence and more favorable relapse outcomes than all oral DMT comparators.
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- 2022
18. Comparative effectiveness of cladribine tablets versus other oral disease-modifying treatments for multiple sclerosis: results from MSBase registry
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Altıntaş, Ayşe (ORCID 0000-0002-8524-5087 & YÖK ID 11611), Spelman, T.; Ozakbas, S.; Alroughani, R.; Terzi, M.; Hodgkinson, S.; Laureys, G.; Kalincik, T.; Van Der Walt, A.; Yamout, B.; Lechner-Scott, J.; Soysal, A.; Kuhle, J.; Sanchez-Menoyo, J.L.; Blanco Morgado, Y.; Spitaleri, D.; van Pesch, V.; Horakova, D.; Ampapa, R.; Patti, F.; Macdonell, R.; Al-Asmi, A.; Gerlach, O.; Oh, J.; Tundia, N.; Wong, S.L.; Butzkueven, H., 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), Spelman, T.; Ozakbas, S.; Alroughani, R.; Terzi, M.; Hodgkinson, S.; Laureys, G.; Kalincik, T.; Van Der Walt, A.; Yamout, B.; Lechner-Scott, J.; Soysal, A.; Kuhle, J.; Sanchez-Menoyo, J.L.; Blanco Morgado, Y.; Spitaleri, D.; van Pesch, V.; Horakova, D.; Ampapa, R.; Patti, F.; Macdonell, R.; Al-Asmi, A.; Gerlach, O.; Oh, J.; Tundia, N.; Wong, S.L.; Butzkueven, H., Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM), and School of Medicine
- Abstract
Background: effectiveness of cladribine tablets, an oral disease-modifying treatment (DMT) for multiple sclerosis (MS), was established in clinical trials and confirmed with real-world experience. Objectives: use real-world data to compare treatment patterns and clinical outcomes in people with MS (pwMS) treated with cladribine tablets versus other oral DMTs. Methods: retrospective treatment comparisons were based on data from the international MSBase registry. Eligible pwMS started treatment with cladribine, fingolimod, dimethyl fumarate, or teriflunomide tablets from 2018 to mid-2021 and were censored at treatment discontinuation/switch, death, loss to follow-up, pregnancy, or study period end. Treatment persistence was evaluated as time to discontinuation/switch; relapse outcomes included time to first relapse and annualized relapse rate (ARR). Results: cohorts included 633 pwMS receiving cladribine tablets, 1195 receiving fingolimod, 912 receiving dimethyl fumarate, and 735 receiving teriflunomide. Individuals treated with fingolimod, dimethyl fumarate, or teriflunomide switched treatment significantly more quickly than matched cladribine tablet cohorts (adjusted hazard ratio (95% confidence interval): 4.00 (2.54-6.32), 7.04 (4.16-11.93), and 6.52 (3.79-11.22), respectively). Cladribine tablet cohorts had significantly longer time-to-treatment discontinuation, time to first relapse, and lower ARR, compared with other oral DMT cohorts. Conclusion: cladribine tablets were associated with a significantly greater real-world treatment persistence and more favorable relapse outcomes than all oral DMT comparators., Financial support for this study was provided entirely by a contract with EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA (CrossRef Funder ID: 10.13039/100004755). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The following authors are employed by the sponsor: NT and SLW.
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- 2022
19. Personality traits are not associated with changes in employment status over 3 years in persons with multiple sclerosis
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Van Der Hiele, K, Van Egmond, Eea, Van Gorp, Dam, Jongen, Pj, Reneman, Mf, van der Klink, J., Beenakker, Eac, Van Eijk, Jjj, Frequin, Stfm, Hoitsma, E, Gerlach, O., Mostert, Jp, Verhagen, Wim, Heerings, Map, Middelkoop, Ham, Visser, Lh, Van Der Hiele, K, Van Egmond, Eea, Van Gorp, Dam, Jongen, Pj, Reneman, Mf, van der Klink, J., Beenakker, Eac, Van Eijk, Jjj, Frequin, Stfm, Hoitsma, E, Gerlach, O., Mostert, Jp, Verhagen, Wim, Heerings, Map, Middelkoop, Ham, and Visser, Lh
- Abstract
Previous research discovered a protective effect of higher conscientiousness against a 3-year deterioration in employment status in persons with multiple sclerosis (pwMS). To replicate these findings, we used data from a multicentre prospective cohort study where 145 employed pwMS completed questionnaires, neurological and neuropsychological examinations at baseline and after 3 years. A 3-year deterioration in employment status was reported in 31.0%. We observed no differences in personality, demographics or clinical characteristics between pwMS with deteriorated or stable employment status. These null findings may be partly explained by the classification of deteriorated employment status, which does not reflect Dutch labour conditions.
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- 2022
20. Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression (vol 208, 106180, 2021)
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De Brouwer, E, Becker, T, Moreau, Y, Havrdova, EK, Trojano, M, Eichau, S, Ozakbas, S, Onofrj, M, Grammond, P, Kuhle, J, Kappos, L, Sola, P, Cartechini, E, Lechner-Scott, J, Alroughani, R, Gerlach, O, Kalincik, T, Granella, F, Grand'Maison, F, Bergamaschi, R, Sa, MJ, Van Wijmeersch, B, Soysal, A, Sanchez-Menoyo, JL, Solaro, C, Boz, C, Iuliano, G, Buzzard, K, Aguera-Morales, E, Terzi, M, Trivio, TC, Spitaleri, D, Van Pesch, V, Shaygannejad, V, Moore, F, Oreja-Guevara, C, Maimone, D, Gouider, R, Csepany, T, Ramo-Tello, C, and Peeters, L
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- 2022
21. Work difficulties in people with multiple sclerosis: the role of depression, anxiety and coping
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van Egmond, E., van der Hiele, K., van Gorp, D., Jongen, S., van der Klink, J., Reneman, M., Beenakker, M., van Eijk, J., Frequin, S., de Gans, K., van Geel, B., Gerlach, O., Hengstman, G., Mostert, J., Verhagen, W., Middelkoop, H., Visser, L., and Extremities Pain and Disability (EXPAND)
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- 2021
22. Personality traits are not associated with changes in employment status over 3 years in persons with multiple sclerosis.
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van der Hiele, K., van Egmond, E. E. A., van Gorp, D. A. M., Jongen, P. J., Reneman, M. F., van der Klink, J. J. L., Beenakker, E. A. C., van Eijk, J. J. J., Frequin, S. T. F. M., Hoitsma, E., Gerlach, O. H. H., Mostert, J. P., Verhagen, W. I. M., Heerings, M. A. P., Middelkoop, H. A. M., and Visser, L. H.
- Abstract
Previous research discovered a protective effect of higher conscientiousness against a 3-year deterioration in employment status in persons with multiple sclerosis (pwMS). To replicate these findings, we used data from a multicentre prospective cohort study where 145 employed pwMS completed questionnaires, neurological and neuropsychological examinations at baseline and after 3 years. A 3-year deterioration in employment status was reported in 31.0%. We observed no differences in personality, demographics or clinical characteristics between pwMS with deteriorated or stable employment status. These null findings may be partly explained by the classification of deteriorated employment status, which does not reflect Dutch labour conditions. [ABSTRACT FROM AUTHOR]
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- 2022
- Full Text
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23. Disability accrual in primary-progressive & secondaryprogressive multiple sclerosis.
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Boz C., Diouf I., Malpas C., Nguyen A.-L., Moradi N., Horakova D., Kubala Havrdova E., Patti F., Izquierdo G., Eichau S., Prat A., Girard M., Duquette P., Onofrj M., Lugaresi A., Grand'Maison F., Weinstock-Guttman B., Amato M.P., Grammond P., Gerlach O., Ozakbas S., Sola P., Ferraro D., Butzkueven H., Lechner-Scott J., Alroughani R., Van Pesch V., Cartechini E., Terzi M., Maimone D., Ramo-Tello C., Spitaleri D., Kappos L., Yamout B., Sa M., Slee M., Blanco Y., Bergamaschi R., Butler E., Iuliano G., Granella F., Sidhom Y., Gouider R., Ampapa R., Van Wijmeersch B., Karabudak R., Prevost J., Sanchez-Menoyo J.L., Verheul F., Mccombe P., Castillo-Trivino T., Macdonell R., Altintas A., Laureys G., Van Hijfte L., Van Der Walt A., Vucic S., Turkoglu R., Barnett M., Cristiano E., Zakaria M., Shaygannejad V., Hodgkinson S., Soysal A., Kalincik T., Harding-Forrester S., Roos I., Sharmin S., Boz C., Diouf I., Malpas C., Nguyen A.-L., Moradi N., Horakova D., Kubala Havrdova E., Patti F., Izquierdo G., Eichau S., Prat A., Girard M., Duquette P., Onofrj M., Lugaresi A., Grand'Maison F., Weinstock-Guttman B., Amato M.P., Grammond P., Gerlach O., Ozakbas S., Sola P., Ferraro D., Butzkueven H., Lechner-Scott J., Alroughani R., Van Pesch V., Cartechini E., Terzi M., Maimone D., Ramo-Tello C., Spitaleri D., Kappos L., Yamout B., Sa M., Slee M., Blanco Y., Bergamaschi R., Butler E., Iuliano G., Granella F., Sidhom Y., Gouider R., Ampapa R., Van Wijmeersch B., Karabudak R., Prevost J., Sanchez-Menoyo J.L., Verheul F., Mccombe P., Castillo-Trivino T., Macdonell R., Altintas A., Laureys G., Van Hijfte L., Van Der Walt A., Vucic S., Turkoglu R., Barnett M., Cristiano E., Zakaria M., Shaygannejad V., Hodgkinson S., Soysal A., Kalincik T., Harding-Forrester S., Roos I., and Sharmin S.
- Abstract
Background: Some cohort studies have reported similar onset age and disability accrual in primary and secondary progressive MS (PPMS, SPMS); others have reported later onset and faster disability accrual in SPMS. Comparisons are complicated by differences in baseline disability and exposure to disease-modifying therapies (DMT), and by lack of a standardized definition of SPMS. Objective(s): We compared hazards of disability accrual in PPMS and SPMS patients from the MSBase cohort using multivariable Cox models, applying validated diagnostic criteria for SPMS (Lorscheider et al., Brain 2016). Method(s): Inclusion required adult-onset progressive MS; >= 3 recorded Expanded Disability Status Scale (EDSS) scores; and, for SPMS, initial records with EDSS <= 3 to allow objective identification of SPMS conversion. Phenotypes were subgrouped as active (PPMS-A, SPMS-A) if >= 1 progressive-phase relapse was recorded, and inactive (PPMS-N, SPMS-N) otherwise. Disability accrual was defined by sustained EDSS increases confirmed over >= 6 months. Hazard ratios (HR) for disability accrual were obtained using Andersen-Gill Cox models, adjusted for sex and time-varying age, disability, visit frequency, and proportion of time on DMT or immunosuppressive therapy. Sensitivity analyses were performed using (1) PPMS and SPMS diagnosed since 1995, and (2) physician-diagnosed SPMS. Cumulative probability of reaching EDSS >= 7 (wheelchair required) was assessed (Kaplan-Meier). Result(s): 5461 patients were included (1257 PPMS-N; 1308 PPMS-A; 1731 SPMS-N; 1165 SPMS-A). Age at progression onset was older in SPMS than PPMS (47.2 +/- 10.2, vs. 41.5 +/- 10.7 [mean +/- SD]), and in the inactive subgroups of each phenotype. Hazard of disability accrual was decreased in SPMS relative to PPMS (HR 0.85; 95% CI 0.78-0.92); decreased by proportion of time on DMT (HR 0.99 per 10% increment; 0.98-0.99); and higher in males (1.18; 1.12-1.25). Relative to PPMS-N, hazard was decreased in SPMS-A (0.79; 0.71
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- 2021
24. Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression
- Author
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De Brouwer, E, Becker, T, Moreau, Y, Havrdova, EK, Trojano, M, Eichau, S, Ozakbas, S, Onofrj, M, Grammond, P, Kuhle, J, Kappos, L, Sola, P, Cartechini, E, Lechner-Scott, J, Alroughani, R, Gerlach, O, Kalincik, T, Granella, F, Grand'Maison, F, Bergamaschi, R, Sa, MJ, Van Wijmeersch, B, Soysal, A, Luis Sanchez-Menoyo, J, Solaro, C, Boz, C, Iuliano, G, Buzzard, K, Aguera-Morales, E, Terzi, M, Castillo Trivio, T, Spitaleri, D, Van Pesch, V, Shaygannejad, V, Moore, F, Oreja-Guevara, C, Maimone, D, Gouider, R, Csepany, T, Ramo-Tello, C, Peeters, L, De Brouwer, E, Becker, T, Moreau, Y, Havrdova, EK, Trojano, M, Eichau, S, Ozakbas, S, Onofrj, M, Grammond, P, Kuhle, J, Kappos, L, Sola, P, Cartechini, E, Lechner-Scott, J, Alroughani, R, Gerlach, O, Kalincik, T, Granella, F, Grand'Maison, F, Bergamaschi, R, Sa, MJ, Van Wijmeersch, B, Soysal, A, Luis Sanchez-Menoyo, J, Solaro, C, Boz, C, Iuliano, G, Buzzard, K, Aguera-Morales, E, Terzi, M, Castillo Trivio, T, Spitaleri, D, Van Pesch, V, Shaygannejad, V, Moore, F, Oreja-Guevara, C, Maimone, D, Gouider, R, Csepany, T, Ramo-Tello, C, and Peeters, L
- Abstract
BACKGROUND AND OBJECTIVES: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem. METHODS: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used. RESULTS: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features. CONCLUSIONS: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS.
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- 2021
25. Prognostic value of natural killer cell/T cell ratios for disease activity in multiple sclerosis
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Mimpen, M, Muris, AH, Rolf, L, Gerlach, O, Kuhle, J, Hupperts, R, Smolders, Joost, Damoiseaux, J, Mimpen, M, Muris, AH, Rolf, L, Gerlach, O, Kuhle, J, Hupperts, R, Smolders, Joost, and Damoiseaux, J
- Abstract
Background and purpose: Natural killer (NK) cells may play a role in multiple sclerosis (MS). Ratios of NK cells to CD4+ T cells have been proposed as a biomarker for the therapeutic effect of stem cell transplantation in MS. The objectives here were to explore the relevance of this ratio in MS patients by analysing NK and T cell subsets, as well as their prognostic value for disease activity. Methods: Baseline peripheral blood mononuclear cells of 50 relapsing–remitting MS patients, participating in our vitamin D supplementation study (SOLARIUM), were analysed with flow cytometry. Disease activity was measured as new magnetic resonance imaging lesions, relapses and mean plasma neurofilament light chain levels after 48 weeks of follow-up. Results: The proportion of NK cells correlated negatively with CD4+ T cells (R = −0.335, p = 0.001) and interleukin 17A (IL-17A+) CD4+ T cells (R = −0.203, p = 0.043). Participants with magnetic resonance imaging activity or relapses displayed lower NK/IL-17A+CD4+ T cell ratios (p =0.025 and p = 0.006, respectively). The NK/IL-17A+CD4+ T cell ratio correlated negatively with neurofilament light chain levels (R = −0.320, p = 0.050). Vitamin D supplementation did not affect these ratios. Conclusions: Our data suggest a protective role of an expanded NK cell compartment compared to the CD4+ T cell subset fractions in relapsing–remitting MS patients. NK/CD4+ T cell ratios may be a prognostic biomarker for disease activity in MS.
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- 2021
26. Synthesis of nanostructured lean-NO x catalysts by direct laser deposition of monometallic Pt-, Rh- and bimetallic PtRh-nanoparticles on SiO2 support
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Savastenko, N., Volpp, H.-R., Gerlach, O., and Strehlau, W.
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- 2008
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27. Prognostic value of natural killer cell/T cell ratios for disease activity in multiple sclerosis
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Mimpen, M. (Max), Muris, A.-H. (Anne-Hilde), Rolf, L. (Linda), Gerlach, O. (Oliver), Kuhle, J. (Jens), Hupperts, R. (Raymond), Smolders, J. (Joost), Damoiseaux, J., Mimpen, M. (Max), Muris, A.-H. (Anne-Hilde), Rolf, L. (Linda), Gerlach, O. (Oliver), Kuhle, J. (Jens), Hupperts, R. (Raymond), Smolders, J. (Joost), and Damoiseaux, J.
- Abstract
Background and purpose: Natural killer (NK) cells may play a role in multiple sclerosis (MS). Ratios of NK cells to CD4+ T cells have been proposed as a biomarker for the therapeutic effect of stem cell transplantation in MS. The objectives here were to explore the relevance of this ratio in MS patients by analysing NK and T cell subsets, as well as their prognostic value for disease activity. Methods: Baseline peripheral bloo
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- 2020
- Full Text
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28. Measurement of the controlled variable during heating of Ti6Al4V for thixoforging
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Gerlach, O, primary, Lechler, A, additional, and Verl, A, additional
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- 2018
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29. Funktionale Programmiersprachen zur Entwicklung numerischer Steuerungen*/Use of functional programming languages for developing computerized numerical controls - Analysis of their potential and fields of application
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Gerlach, O., primary, Csiszar, A., additional, Lechler, A., additional, and Verl, A. Prof., additional
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- 2017
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30. Semi-solid Formgebung von AMC-Werkstoffen
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Seyboldt, C., Liewald, M., Schubert, T., Weißgärber, T., Gerlach, O., Lechler, A., and Publica
- Abstract
Hinsichtlich der Verarbeitung von partikelverstärkten Aluminiummatrix-Verbundwerkstoffen (AMC) zu komplexen Bauteilen mit hoher Endkonturnähe, Maßhaltigkeit und hervorragenden mechanischen Eigenschaften bietet die Formgebung im teilflüssigen Zustand aussichtsreiche Perspektiven. In diesem Zusammenhang beschreibt der Fachbeitrag eine neuentwickelte Prozessroute zur Herstellung von Hochleistungskomponenten aus solchen AMC-Werkstoffen und zeigt deren Potentiale auf.
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- 2015
31. Semi-solid Formgebung von AMC-Werkstoffen*/Semi-solid forming of AMC materials - Potential of a new process flow for high performance components
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Seyboldt, C., primary, Schubert, T., additional, Gerlach, O., additional, Liewald, M., additional, Weißgärber, T., additional, and Lechler, A., additional
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- 2015
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32. Time constant measurement for control of induction heating processes for thixoforming
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Gerlach, O, primary, Lechler, A, additional, and Verl, A, additional
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- 2014
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33. Von der nachholenden zur nachhaltigen Entwicklung - und wieder zurück. Vom Schicksal der Naturverhältnisse in der Entwicklungsdiskussion
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Gerlach, O., Kalmring, S., Kumitz, D., Nowak, A., Görg, Christoph, Gerlach, O., Kalmring, S., Kumitz, D., Nowak, A., and Görg, Christoph
- Published
- 2004
34. Die Wirkung von »Entspannungsmusik« auf Patienten, Ärzte und Pflegepersonal einer internistischen Intensivstation
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Neuhof, H., primary, Klapp, B. F., additional, Gerlach, O., additional, Koch, H. U., additional, Hundhausen, T., additional, and Lasch, H. G., additional
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- 2008
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35. Synthesis of nanostructured lean-NO x catalysts by direct laser deposition of monometallic Pt-, Rh- and bimetallic PtRh-nanoparticles on SiO2 support
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Savastenko, N., primary, Volpp, H.-R., additional, Gerlach, O., additional, and Strehlau, W., additional
- Published
- 2007
- Full Text
- View/download PDF
36. GABAB receptors at glutamatergic synapses in the rat striatum
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Lacey, C.J., primary, Boyes, J., additional, Gerlach, O., additional, Chen, L., additional, Magill, P.J., additional, and Bolam, J.P., additional
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- 2005
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37. Developments in mathematical models of human pilot behaviour
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Gerlach, O. H., primary
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- 1977
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38. Simulation research: role of university, government and industry in the Netherlands
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Gerlach, O. H., primary
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- 1980
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39. GABAB receptors at glutamatergic synapses in the rat striatum
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Lacey, C.J., Boyes, J., Gerlach, O., Chen, L., Magill, P.J., and Bolam, J.P.
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- *
GABA , *NEURAL transmission , *NEURAL circuitry , *IMMUNOGLOBULINS , *CELL membranes - Abstract
Abstract: Although multiple effects of GABAB receptor activation on synaptic transmission in the striatum have been described, the precise locations of the receptors mediating these effects have not been determined. To address this issue, we carried out pre-embedding immunogold electron microscopy in the rat using antibodies against the GABAB receptor subunits, GABAB1 and GABAB2. In addition, to investigate the relationship between GABAB receptors and glutamatergic striatal afferents, we used antibodies against the vesicular glutamate transporters, vesicular glutamate transporter 1 and vesicular glutamate transporter 2, as markers for glutamatergic terminals. Immunolabeling for GABAB1 and GABAB2 was widely and similarly distributed in the striatum, with immunogold particles localized at both presynaptic and postsynaptic sites. The most commonly labeled structures were dendritic shafts and spines, as well as terminals forming asymmetric and symmetric synapses. In postsynaptic structures, the majority of labeling associated with the plasma membrane was localized at extrasynaptic sites, although immunogold particles were also found at the postsynaptic specialization of some symmetric, putative GABAergic synapses. Labeling in axon terminals was located within, or at the edge of, the presynaptic active zone, as well as at extrasynaptic sites. Double labeling for GABAB receptor subunits and vesicular glutamate transporters revealed that labeling for both GABAB1 and GABAB2 was localized on glutamatergic axon terminals that expressed either vesicular glutamate transporter 1 or vesicular glutamate transporter 2. The patterns of innervation of striatal neurons by the vesicular glutamate transporter 1- and vesicular glutamate transporter 2-positive terminals suggest that they are selective markers of corticostriatal and thalamostriatal afferents, respectively. These results thus provide evidence that presynaptic GABAB heteroreceptors are in a position to modulate the two major excitatory inputs to striatal spiny projection neurons arising in the cortex and thalamus. In addition, presynaptic GABAB autoreceptors are present on the terminals of spiny projection neurons and/or striatal GABAergic interneurons. Furthermore, the data indicate that GABA may also affect the excitability of striatal neurons via postsynaptic GABAB receptors. [Copyright &y& Elsevier]
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- 2006
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40. Comparative effectiveness of cladribine tablets versus other oral disease-modifying treatments for multiple sclerosis: Results from MSBase registry
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Tim Spelman, Serkan Ozakbas, Raed Alroughani, Murat Terzi, Suzanne Hodgkinson, Guy Laureys, Tomas Kalincik, Anneke Van Der Walt, Bassem Yamout, Jeannette Lechner-Scott, Aysun Soysal, Jens Kuhle, Jose Luis Sanchez-Menoyo, Yolanda Blanco Morgado, Daniele LA Spitaleri, Vincent van Pesch, Dana Horakova, Radek Ampapa, Francesco Patti, Richard Macdonell, Abdullah Al-Asmi, Oliver Gerlach, Jiwon Oh, Ayse Altintas, Namita Tundia, Schiffon L Wong, Helmut Butzkueven, UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire, Altıntaş, Ayşe (ORCID 0000-0002-8524-5087 & YÖK ID 11611), Spelman, T., Ozakbas, S., Alroughani, R., Terzi, M., Hodgkinson, S., Laureys, G., Kalincik, T., Van Der Walt, A., Yamout, B., Lechner-Scott, J., Soysal, A., Kuhle, J., Sanchez-Menoyo, J.L., Blanco Morgado, Y., Spitaleri, D., van Pesch, V., Horakova, D., Ampapa, R., Patti, F., Macdonell, R., Al-Asmi, A., Gerlach, O., Oh, J., Tundia, N., Wong, S.L., Butzkueven, H., Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM), and School of Medicine
- Subjects
relapse ,Multiple Sclerosis ,real-world data ,Fingolimod Hydrochloride ,switching ,Dimethyl Fumarate ,Neurosciences and neurology ,MS ,registry ,Multiple Sclerosis, Relapsing-Remitting ,Disability ,Discontinuation ,Real-world data ,Registry ,Relapse ,Switching ,Neurology ,disability ,Recurrence ,Medicine and Health Sciences ,Humans ,Cladribine ,Neurology (clinical) ,Registries ,Immunosuppressive Agents ,Retrospective Studies ,Tablets ,discontinuation - Abstract
Background: effectiveness of cladribine tablets, an oral disease-modifying treatment (DMT) for multiple sclerosis (MS), was established in clinical trials and confirmed with real-world experience. Objectives: use real-world data to compare treatment patterns and clinical outcomes in people with MS (pwMS) treated with cladribine tablets versus other oral DMTs. Methods: retrospective treatment comparisons were based on data from the international MSBase registry. Eligible pwMS started treatment with cladribine, fingolimod, dimethyl fumarate, or teriflunomide tablets from 2018 to mid-2021 and were censored at treatment discontinuation/switch, death, loss to follow-up, pregnancy, or study period end. Treatment persistence was evaluated as time to discontinuation/switch; relapse outcomes included time to first relapse and annualized relapse rate (ARR). Results: cohorts included 633 pwMS receiving cladribine tablets, 1195 receiving fingolimod, 912 receiving dimethyl fumarate, and 735 receiving teriflunomide. Individuals treated with fingolimod, dimethyl fumarate, or teriflunomide switched treatment significantly more quickly than matched cladribine tablet cohorts (adjusted hazard ratio (95% confidence interval): 4.00 (2.54-6.32), 7.04 (4.16-11.93), and 6.52 (3.79-11.22), respectively). Cladribine tablet cohorts had significantly longer time-to-treatment discontinuation, time to first relapse, and lower ARR, compared with other oral DMT cohorts. Conclusion: cladribine tablets were associated with a significantly greater real-world treatment persistence and more favorable relapse outcomes than all oral DMT comparators., Financial support for this study was provided entirely by a contract with EMD Serono Research & Development Institute, Inc., Billerica, MA, USA, an affiliate of Merck KGaA (CrossRef Funder ID: 10.13039/100004755). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The following authors are employed by the sponsor: NT and SLW.
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- 2023
41. Determinants of therapeutic lag in multiple sclerosis
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Tomas Kalincik, Marc Girard, Corinne Pottier, Murat Terzi, Jean Pelletier, Oliver Gerlach, Julie Prevost, Dana Horakova, Francois Grand'Maison, Raed Alroughani, Guillermo Izquierdo, Francesco Patti, Federico Frascoli, Maria Trojano, Franco Granella, Pamela A. McCombe, Charles B Malpas, Recai Turkoglu, Aurélie Ruet, Jonathan Ciron, Tünde Csépány, Nicolas Maubeuge, Helmut Butzkueven, Pierre Clavelou, Tamara Castillo Trivino, Marco Onofrj, Jean Philippe Camdessanche, Pierre Labauge, Vincent Van Pesch, Pierre Grammond, Abir Wahab, Roberto Bergamaschi, Aysun Soysal, Diana Ferraro, Bertrand Bourre, Olivier Gout, Jeannette Lechner-Scott, Sara Eichau, Emmanuelle Leray, Alexis Montcuquet, Pierre Duquette, Olivier Casez, Youssef Sidhom, Patrizia Sola, Bart Van Wijmeersch, Izanne Roos, Gilles Edan, Serkan Ozakbas, David Laplaud, Sandra Vukusic, Abdullatif Al Khedr, Céline Labeyrie, Philippe Cabre, Eric Thouvenot, Céline Louapre, Romain Casey, Alessandra Lugaresi, Riadh Gouider, Alasdair Coles, Eric Berger, Ivania Patry, Gerardo Iuliano, Elisabetta Cartechini, Cavit Boz, Karolina Hankiewicz, Eva Havrdova, Eduardo Aguera-Morales, J William L Brown, Jérôme De Seze, Bruno Stankoff, Olivier Heinzlef, Gilles Defer, Alexandre Prat, Chantal Nifle, Maria José Sá, Marc Debouverie, Daniele Spitaleri, Aude Maurousset, Thibault Moreau, Christine Lebrun-Frenay, Hélène Zéphir, University of Melbourne, Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École des Hautes Études en Santé Publique [EHESP] (EHESP), École des Hautes Études en Santé Publique [EHESP] (EHESP), Département Méthodes quantitatives en santé publique (METIS), Collectif de recherche handicap, autonomie et société inclusive (CoRHASI), Swinburne University of Technology [Melbourne], Université Claude Bernard Lyon 1 (UCBL), Université de Lyon, Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Hospices Civils de Lyon (HCL), Charles University [Prague], Università degli studi di Catania [Catania], Università degli studi 'G. d'Annunzio' Chieti-Pescara [Chieti-Pescara] (Ud'A), Università degli Studi di Modena e Reggio Emilia (UNIMORE), University of Queensland [Brisbane], Monash University [Clayton], UCL - SSS/IONS/CEMO - Pôle Cellulaire et moléculaire, UCL - (SLuc) Service de biochimie médicale, UCL - (SLuc) Service de neurologie, Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Charles University [Prague] (CU), Adaptation, mesure et évaluation en santé. Approches interdisciplinaires (APEMAC), Université de Lorraine (UL), Service de neurologie [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), University of Bari Aldo Moro (UNIBA), University of Catania [Italy], Hospital Virgen Macarena, Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM), CHU Toulouse [Toulouse], INSERM, Neurocentre Magendie, U1215, Physiopathologie de la Plasticité Neuronale, F-33000 Bordeaux, France, CIC Bordeaux, Université Bordeaux Segalen - Bordeaux 2-Institut National de la Santé et de la Recherche Médicale (INSERM), Dokuz Eylül Üniversitesi = Dokuz Eylül University [Izmir] (DEÜ), CIC Strasbourg (Centre d’Investigation Clinique Plurithématique (CIC - P) ), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Strasbourg (UNISTRA)-Hôpital de Hautepierre [Strasbourg]-Nouvel Hôpital Civil de Strasbourg, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Lille, Fernando Pessoa University, Azienda Ospedaleria Universitaria di Modena, CHU Montpellier, Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Centre Hospitalier Universitaire de Nice (CHU Nice), Karadeniz Technical University (KTU), Università degli Studi di Macerata = University of Macerata (UNIMC), CHU Dijon, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Centre hospitalier universitaire de Nantes (CHU Nantes), University of Newcastle [Australia] (UoN), Zuyderland Hospital [Heerlen, The Netherlands], Ondokuz Mayis University, University of Parma = Università degli studi di Parma [Parme, Italie], Amiri hospital, University of Salerno (UNISA), Université Catholique de Louvain = Catholic University of Louvain (UCL), Hasselt University (UHasselt), San Giuseppe Moscati Hospital [Avellino, Italie], Bakirkoy Matern & Childrens State Hosp, Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Universidad de Córdoba [Cordoba], Hospital Donostia, CHU Clermont-Ferrand, Hôpital de la Timone [CHU - APHM] (TIMONE), Fondation Ophtalmologique Adolphe de Rothschild [Paris], Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), CHI Poissy-Saint-Germain, Université de la Manouba [Tunisie] (UMA), University of Debrecen, Hôpital Charles Nicolle [Rouen], CHU Amiens-Picardie, CHU de la Martinique [Fort de France], CHU Limoges, CHU Henri Mondor, Centre Hospitalier Universitaire de Saint-Etienne (CHU de Saint-Etienne), Centre Hospitalier Régional Universitaire de Tours (CHRU TOURS), Centre Hospitalier Sud Francilien, CH Evry-Corbeil, Centre Hospitalier de Saint-Denis [Ile-de-France], Centre Hospitalier René Dubos [Pontoise], This study was supported by the EDMUS Foundation and NHMRC [1140766,1129189, 1157717]. IR is supported by a MSIF-ARSEP McDonald fellowship grantand a Melbourne Research Scholarship. The MSBase Foundation is a not-for-profitorganization that receives support from Biogen, Novartis, Merck, Roche, Teva andSanofi Genzyme. The study was conducted separately and apart from the guidanceof the sponsors. The Observatoire Français de la Sclérose en Plaques (OFSEP) issupported by a grant provided by the French State and handled by the 'AgenceNationale de la Recherche,' within the framework of the 'Investments for the Future'program, under the reference ANR-10-COHO-002, by the Eugène Devic EDMUSFoundation against multiple sclerosis and by the ARSEP Foundation., ANR-10-COHO-0002,OFSEP,Observatoire Français de la Sclérose en Plaques(2010), Centre de recherche en neurosciences de Lyon - Lyon Neuroscience Research Center (CRNL), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Roos I., Leray E., Frascoli F., Casey R., Brown J.W.L., Horakova D., Havrdova E.K., Debouverie M., Trojano M., Patti F., Izquierdo G., Eichau S., Edan G., Prat A., Girard M., Duquette P., Onofrj M., Lugaresi A., Grammond P., Ciron J., Ruet A., Ozakbas S., De Seze J., Louapre C., Zephir H., Sa M.J., Sola P., Ferraro D., Labauge P., Defer G., Bergamaschi R., Lebrun-Frenay C., Boz C., Cartechini E., Moreau T., Laplaud D., Lechner-Scott J., Grand'Maison F., Gerlach O., Terzi M., Granella F., Alroughani R., Iuliano G., Van Pesch V., Van Wijmeersch B., Spitaleri D.L.A., Soysal A., Berger E., Prevost J., Aguera-Morales E., McCombe P., Castillo Trivino T., Clavelou P., Pelletier J., Turkoglu R., Stankoff B., Gout O., Thouvenot E., Heinzlef O., Sidhom Y., Gouider R., Csepany T., Bourre B., Al Khedr A., Casez O., Cabre P., Montcuquet A., Wahab A., Camdessanche J.-P., Maurousset A., Patry I., Hankiewicz K., Pottier C., Maubeuge N., Labeyrie C., Nifle C., Coles A., Malpas C.B., Vukusic S., Butzkueven H., Kalincik T., Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lyon-Université de Lyon-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Università degli studi di Bari Aldo Moro = University of Bari Aldo Moro (UNIBA), Università degli studi di Catania = University of Catania (Unict), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Neurocentre Magendie : Physiopathologie de la Plasticité Neuronale (U1215 Inserm - UB), Université de Bordeaux (UB)-Institut François Magendie-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nouvel Hôpital Civil de Strasbourg-Hôpital de Hautepierre [Strasbourg], Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Modena e Reggio Emilia = University of Modena and Reggio Emilia (UNIMORE), University of Newcastle [Callaghan, Australia] (UoN), Ondokuz Mayis University (OMU), Università degli studi di Parma = University of Parma (UNIPR), Universidad de Córdoba = University of Córdoba [Córdoba], University of Debrecen Egyetem [Debrecen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU), CHU Henri Mondor [Créteil], Centre Hospitalier Universitaire de Saint-Etienne [CHU Saint-Etienne] (CHU ST-E), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
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Registrie ,Male ,medicine.medical_specialty ,Treatment response ,Pediatrics ,Neurology ,Lag ,[SDV]Life Sciences [q-bio] ,Aucun ,multiple sclerosis ,03 medical and health sciences ,Disability Evaluation ,0302 clinical medicine ,Multiple Sclerosis, Relapsing-Remitting ,Recurrence ,medicine ,Humans ,Treatment effect ,Disabled Persons ,Registries ,030304 developmental biology ,0303 health sciences ,business.industry ,Multiple sclerosis ,Delayed onset ,medicine.disease ,3. Good health ,Clinical neurology ,therapeutic lag ,multiple sclerosi ,Disease Progression ,Disabled Person ,Observational study ,Female ,observational study ,Neurology (clinical) ,business ,030217 neurology & neurosurgery ,Human - Abstract
International audience; Objective: To explore the associations of patient and disease characteristics with the duration of therapeutic lag for relapses and disability progression.Background: Therapeutic lag represents the delay from initiation of therapy to attainment of full treatment effect. Understanding the determinants of therapeutic lag provides valuable information for personalised choice of therapy in multiple sclerosis (MS).Design/Methods: Data from MSBase, a multinational MS registry, and OFSEP, the French national registry, were used. Patients diagnosed with MS, minimum 1-year exposure to MS treatment, minimum 3-year pre-treatment follow up and yearly review were included in the analysis. By studying incidence of relapses and 6-month confirmed disability progression, the duration of therapeutic lag was calculated by identifying the first local minimum of the first derivative after treatment start in subgroups stratified by patient and disease characteristics. Pairwise analyses of univariate predictors were performed. Combinations of determinants that consistently drove differences in therapeutic lag in pair by pair analyses were included in the final model.Results: Baseline EDSS, ARR and sex were associated with duration of therapeutic lag on disability progression in univariate and pairwise bivariable analyses. In the final model, therapeutic lag was 27.8 weeks shorter in females with ARR6 compared to those with EDSS>=6 (26.6, 18.2–34.9 vs 54.3, 47.2–61.5). Baseline EDSS, ARR, sex and MS phenotype were associated with duration of therapeutic lag on relapses in univariate analyses. Pairwise bivariable analyses of the pairs of determinants suggested ependently associated with therapeutic lag. In the final model, therapeutic lag was shortest in those with RRMS and EDSS
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- 2021
42. Effectiveness of Disease-Modifying Treatment on Spinal Cord Lesion Formation in Relapse-Onset Multiple Sclerosis: An MSBase Registry Study.
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Kreiter D, Kalincik T, Hupperts R, Patti F, Spitaleri D, Foschi M, Surcinelli A, Maimone D, Yamout B, Khoury SJ, Lechner-Scott J, Ozakbas S, and Gerlach O
- Abstract
Background: Spinal cord lesions in multiple sclerosis (MS) have considerable impact on disability. High-efficacy disease-modifying treatments (hDMTs) are associated with greater reduction of relapses and new brain lesions compared to low-efficacy treatments (lDMTs). Knowledge on the impact of DMTs on cord lesion formation is limited as these outcome measures were not included in MS treatment trials. This study aims to investigate whether hDMTs reduce the formation of cord lesions more effectively than lDMTs., Methods: Patients with relapse-onset MS, a cord magnetic resonance imaging (MRI) within 6 months before/after initiation of their first DMT and ≥1 cord MRI at follow-up (interval > 6 months) were extracted from the MSBase registry (ACTRN12605000455662). Patients treated with hDMTs ≥90% or lDMTs ≥90% of follow-up duration were considered the hDMT and lDMT groups, respectively. Matching was performed using propensity scores. Cox proportional hazards models were used to estimate the hazards of new cord lesions, brain lesions and relapses., Results: Ninety-four and 783 satisfied hDMT and lDMT group criteria, respectively. Seventy-seven hDMT patients were matched to 184 lDMT patients. In the hDMT group there was no evidence of reduction of new cord lesions (hazard ratio [HR] 0.99 [95% CI 0.51, 1.92], p = 0.97), while there were fewer new brain lesions (HR 0.22 [95% CI 0.10, 0.49], p < 0.001) and fewer relapses (HR 0.45 [95% CI 0.28, 0.72], p = 0.004)., Conclusion: A potential discrepancy exists in the effect of hDMTs over lDMTs in preventing spinal cord lesions versus brain lesions and relapses. While hDMTs provided a significant reduction for the latter when compared to lDMTs, there was no significant reduction in new spinal cord lesions., (© 2024. The Author(s).)
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- 2024
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43. Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center study.
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De Brouwer E, Becker T, Werthen-Brabants L, Dewulf P, Iliadis D, Dekeyser C, Laureys G, Van Wijmeersch B, Popescu V, Dhaene T, Deschrijver D, Waegeman W, De Baets B, Stock M, Horakova D, Patti F, Izquierdo G, Eichau S, Girard M, Prat A, Lugaresi A, Grammond P, Kalincik T, Alroughani R, Grand'Maison F, Skibina O, Terzi M, Lechner-Scott J, Gerlach O, Khoury SJ, Cartechini E, Van Pesch V, Sà MJ, Weinstock-Guttman B, Blanco Y, Ampapa R, Spitaleri D, Solaro C, Maimone D, Soysal A, Iuliano G, Gouider R, Castillo-Triviño T, Sánchez-Menoyo JL, Laureys G, van der Walt A, Oh J, Aguera-Morales E, Altintas A, Al-Asmi A, de Gans K, Fragoso Y, Csepany T, Hodgkinson S, Deri N, Al-Harbi T, Taylor B, Gray O, Lalive P, Rozsa C, McGuigan C, Kermode A, Sempere AP, Mihaela S, Simo M, Hardy T, Decoo D, Hughes S, Grigoriadis N, Sas A, Vella N, Moreau Y, and Peeters L
- Abstract
Background: Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking., Methods: Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS., Findings: Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history., Conclusions: Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study., Competing Interests: The authors declare no competing non-financial interests but the following competing financial interests: - Dana Horakova received speaker honoraria and consulting fees from Biogen, Merck, Teva, Roche, Sanofi Genzyme, and Novartis, as well as support for research activities from Biogen and Czech Minsitry of Education [project Progres Q27/LF1]. - Francesco Patti received speaker honoraria and advisory board fees from Almirall, Bayer, Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme and TEVA. He received research funding from Biogen, Merck, FISM (Fondazione Italiana Sclerosi Multipla), Reload Onlus Association and University of Catania. - Guillermo Izquierdo received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. - Sara Eichau received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche and Teva. - Marc Girard received consulting fees from Teva Canada Innovation, Biogen, Novartis and Genzyme Sanofi; lecture payments from Teva Canada Innovation, Novartis and EMD. He has also received a research grant from Canadian Institutes of Health Research. - Alessandra Lugaresi has served as a Biogen, Bristol Myers Squibb, Merck Serono, Novartis, Roche, Sanofi/ Genzyme and Teva Advisory Board Member. She received congress and travel/accommodation expense compensations or speaker honoraria from Biogen, Merck, Mylan, Novartis, Roche, Sanofi/Genzyme, Teva and Fondazione Italiana Sclerosi Multipla (FISM). Her institutions received research grants from Novartis and Sanofi Genzyme. - Pierre Grammond has served in advisory boards for Novartis, EMD Serono, Roche, Biogen idec, Sanofi Genzyme, Pendopharm and has received grant support from Genzyme and Roche, has received research grants for his institution from Biogen idec, Sanofi Genzyme, EMD Serono. - Tomas Kalincik served on scientific advisory boards for BMS, Roche, Janssen, Sanofi Genzyme, Novartis, Merck and Biogen, steering committee for Brain Atrophy Initiative by Sanofi Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Sanofi-Genzyme, Teva, BioCSL and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene and Merck. - Raed Alroughani received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche and Sanofi-Genzyme. - Francois Grand’Maison received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, Mitsubishi and ONO Pharmaceuticals. - Murat Terzi received travel grants from Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. - Jeannette Lechner-Scott travel compensation from Novartis, Biogen, Roche and Merck. Her institution receives the honoraria for talks and advisory board commitment as well as research grants from Biogen, Merck, Roche, TEVA and Novartis. - Samia J. Khoury received compensation for participation in the Novartis Maestro program. - Vincent van Pesch has received travel grants from Merck, Biogen, Sanofi, Bristol Myers Squibb, Almirall and Roche; his institution receives honoraria for consultancy and lectures and research grants from Roche, Biogen, Sanofi, Merck, Bristol Myers Squibb, Janssen, Almirall and Novartis Pharma. - Radek Ampapa received conference travel support from Novartis, Teva, Biogen, Bayer and Merck and has participated in a clinical trials by Biogen, Novartis, Teva and Actelion. - Daniele Spitaleri received honoraria as a consultant on scientific advisory boards by Bayer-Schering, Novartis and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva and Merck. - Claudio Solaro served on scientific advisory boards for Merck, Genzyme, Almirall, and Biogen; received honoraria and travel grants from Sanofi Aventis, Novartis, Biogen, Merck, Genzyme and Teva. - Davide Maimone served on scientific advisory boards for Bayer, Biogen, Merck, Sanofi-Genzyme, Novartis, Roche, and Almirall; received honoraria and travel grants from Sanofi Genzyme, Novartis, Biogen, Merck, and Roche. - Gerardo Iuliano (retired - no PI successor but has approved ongoing use of data) had travel/accommodations/meeting expenses funded by Bayer Schering, Biogen, Merck, Novartis, Sanofi Aventis, and Teva. - Bart Van Wijmeersch received research and travel grants, honoraria for MS-Expert advisor and Speaker fees from Bayer-Schering, Biogen, Sanofi Genzyme, Merck, Novartis, Roche and Teva. - Tamara Castillo Triviño received speaking/consulting fees and/or travel funding from Bayer, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme and Teva. - Jose Luis Sanchez-Menoyo accepted travel compensation from Novartis, Merck and Biogen, speaking honoraria from Biogen, Novartis, Sanofi, Merck, Almirall, Bayer and Teva and has participated in clinical trials by Biogen, Merck and Roche - Guy Laureys received travel and/or consultancy compensation from Sanofi-Genzyme, Roche, Teva, Merck, Novartis, Celgene, Biogen. - Anneke van der Walt served on advisory boards and receives unrestricted research grants from Novartis, Biogen, Merck and Roche She has received speaker’s honoraria and travel support from Novartis, Roche, and Merck. She receives grant support from the National Health and Medical Research Council of Australia and MS Research Australia. - Jiwon Oh has received research funding from the MS Society of Canada, National MS Society, Brain Canada, Biogen, Roche, EMD Serono (an affiliate of Merck KGaA); and personal compensation for consulting or speaking from Alexion, Biogen, Celgene (BMS), EMD Serono (an affiliate of Merck KGaA), Novartis, Roche, and Sanofi-Genzyme. - Ayse Altintas received speaker honoraria from Merck, Alexion,; received travel and registration grants from Merck, Biogen - Gen Pharma, Roche, Sanofi-Genzyme. - Yara Fragoso received honoraria as a consultant on scientific advisory boards by Novartis, Teva, Roche and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva, Roche and Merck. - Tunde Csepany received speaker honoraria/ conference travel support from Bayer Schering, Biogen, Merck, Novartis, Roche, Sanofi-Aventis and Teva. - Suzanne Hodgkinson received honoraria and consulting fees from Novartis, Bayer Schering and Sanofi, and travel grants from Novartis, Biogen Idec and Bayer Schering. - Norma Deri received funding from Bayer, Merck, Biogen, Genzyme and Novartis. - Bruce Taylor received funding for travel and speaker honoraria from Bayer Schering Pharma, CSL Australia, Biogen and Novartis, and has served on advisory boards for Biogen, Novartis, Roche and CSL Australia. - Fraser Moore participated in clinical trials sponsored by EMD Serono and Novartis. - Orla Gray received honoraria as consultant on scientific advisory boards for Genzyme, Biogen, Merck, Roche and Novartis; has received travel grants from Biogen, Merck, Roche and Novartis; has participated in clinical trials by Biogen and Merck. - Csilla Rozsa received speaker honoraria from Bayer Schering, Novartis and Biogen, congress and travel expense compensations from Biogen, Teva, Merck and Bayer Schering. - Allan Kermode received speaker honoraria and scientific advisory board fees from Bayer, BioCSL, Biogen, Genzyme, Innate Immunotherapeutics, Merck, Novartis, Sanofi, Sanofi-Aventis, and Teva. - Magdolna Simo received speaker honoraria from Novartis, Biogen, Bayer Schering; congress/travel compensation from Teva, Biogen, Merck, Bayer Schering. - Todd Hardy has received speaking fees or received honoraria for serving on advisory boards for Biogen, Merck, Teva, Novartis, Roche, Bristol-Myers Squibb and Sanofi-Genzyme, is Co-Editor of Advances in Clinical Neurosciences and Rehabilitation, and serves on the editorial board of Journal of Neuroimmunology and Frontiers in Neurology. - Nikolaos Grigoriadis received honoraria, consultancy/lecture fees, travel support and research grants from Biogen Idec, Biologix, Novartis, TEVA, Bayer, Merck Serono, Genesis Pharma, Sanofi – Genzyme, ROCHE, Cellgene, ELPEN and research grants from Hellenic Ministry of Development., (Copyright: © 2024 De Brouwer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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- 2024
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44. Longitudinal determinants of employment status in people with relapsing-remitting multiple sclerosis.
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van Egmond EEA, van der Hiele K, de Rooij MJ, van Gorp DAM, Jongen PJ, van der Klink JJL, Reneman MF, Beenakker EAC, van Eijk JJJ, Frequin STFM, de Gans K, Hoitsma E, Gerlach OHH, Mostert JP, Verhagen WIM, Visser LH, and Middelkoop HAM
- Abstract
Purpose: To investigate longitudinal relationships between employment status and disease-related, (neuro)psychological, and work-related factors in people with multiple sclerosis (MS)., Methods: 170 employed people with MS underwent yearly neurological and neuropsychological examinations to assess MS-related disability and cognitive functioning. Additionally, they completed yearly questionnaires assessing depression, anxiety, fatigue, cognitive complaints, workplace support and coping. Multilevel models for change were fitted to examine progression of these factors over three years, and to assess possible relationships with change in employment status., Results: People with a deteriorated employment status after three years reported more depression ( p= 0.009), a higher impact of fatigue ( p< 0.001), more cognitive complaints ( p< 0.001) and less workplace support ( p= 0.001) at baseline than people with a stable employment status. There were no differences in progression over time of the examined variables between people with a stable or deteriorated employment status., Conclusion: More depression, a higher impact of fatigue, more cognitive complaints and less workplace support are predictive of a deteriorated employment status after three years in individuals with MS. How these factors progress over time is not different between those with a stable or deteriorated employment. MS-related disability, anxiety, objective cognition and coping were not related to a deterioration in employment status., Competing Interests: E.E.A. van Egmond, K. van der Hiele, M.J. de Rooij, D.A.M. van Gorp, J.J.L. van der Klink, M.F. Reneman, E.A.C. Beenakker, S.T.F.M. Frequin, K. de Gans, O.H.H. Gerlach, J.P. Mostert, and H.A.M. Middelkoop declare no conflict of interestP.J. Jongen received honoraria from Bayer Netherlands and Orikami Personalized Health Care for consultancy activities and is chairman of the MSmonitor Foundation.L.H. Visser received a research grant for the multicentre BIA study from Merck, received consultancy fees from Merck, Novartis and JanssenJ.J.J. van Eijk received consultancy fees and honoraria for lectures from Merck, Biogen, Novartis, Sanofi, Janssen and RocheE. Hoitsma received honoraria for lectures and advisory boards from Bayer, Biogen, Roche, Sanofi Genzyme, Merck Serono, Novartis and Teva.W.I.M. Verhagen received consultancy fees from Merck and Biogen, (© 2024 The Authors.)
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- 2024
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45. Hallmarks of spinal cord pathology in multiple sclerosis.
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Kreiter D, Postma AA, Hupperts R, and Gerlach O
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- Humans, Spinal Cord diagnostic imaging, Spinal Cord pathology, Gray Matter pathology, Brain diagnostic imaging, Brain pathology, Magnetic Resonance Imaging, Multiple Sclerosis diagnostic imaging, Multiple Sclerosis pathology, White Matter pathology
- Abstract
A disparity exists between spinal cord and brain involvement in multiple sclerosis (MS), each independently contributing to disability. Underlying differences between brain and cord are not just anatomical in nature (volume, white/grey matter organization, vascularization), but also in barrier functions (differences in function and composition of the blood-spinal cord barrier compared to blood-brain barrier) and possibly in repair mechanisms. Also, immunological phenotypes seem to influence localization of inflammatory activity. Whereas the brain has gained a lot of attention in MS research, the spinal cord lags behind. Advanced imaging techniques and biomarkers are improving and providing us with tools to uncover the mechanisms of spinal cord pathology in MS. In the present review, we elaborate on the underlying anatomical and physiological factors driving differences between brain and cord involvement in MS and review current literature on pathophysiology of spinal cord involvement in MS and the observed differences to brain involvement., Competing Interests: Declaration of Competing Interest DK, AP and OG have nothing to disclose; RH received institutional research grants and fees for lectures and advisory boards from Biogen, Merck and Genzyme-Sanofi., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
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- 2024
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46. Examining the environmental risk factors of progressive-onset and relapsing-onset multiple sclerosis: recruitment challenges, potential bias, and statistical strategies.
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Li Y, Saul A, Taylor B, Ponsonby AL, Simpson-Yap S, Blizzard L, Broadley S, Lechner-Scott J, Karabudak R, Patti F, Eichau S, Onofrj M, Ozakbas S, Horakova D, Kubala Havrdova E, Grand'Maison F, Alroughani R, Gerlach O, Amato MP, Altintas A, Girard M, Duquette P, Blanco Y, Ramo-Tello C, Laureys G, Kalincik T, Khoury SJ, Shaygannejad V, Etemadifar M, Singhal B, Mrabet S, Foschi M, Habek M, John N, Hughes S, McCombe P, Ampapa R, van der Walt A, Butzkueven H, de Gans K, McGuigan C, Oreja-Guevara C, Sa MJ, Petersen T, Al-Harbi T, Sempere AP, Van Wijmeersch B, Grigoriadis N, Prevost J, Gray O, Castillo-Triviño T, Macdonell R, Lugaresi A, Sajedi SA, and van der Mei I
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- Adult, Female, Humans, Male, Middle Aged, Age of Onset, Australia epidemiology, Case-Control Studies, Recurrence, Risk Factors, Multicenter Studies as Topic, Multiple Sclerosis epidemiology, Multiple Sclerosis etiology, Multiple Sclerosis, Chronic Progressive epidemiology, Multiple Sclerosis, Chronic Progressive etiology
- Abstract
It is unknown whether the currently known risk factors of multiple sclerosis reflect the etiology of progressive-onset multiple sclerosis (POMS) as observational studies rarely included analysis by type of onset. We designed a case-control study to examine associations between environmental factors and POMS and compared effect sizes to relapse-onset MS (ROMS), which will offer insights into the etiology of POMS and potentially contribute to prevention and intervention practice. This study utilizes data from the Primary Progressive Multiple Sclerosis (PPMS) Study and the Australian Multi-center Study of Environment and Immune Function (the AusImmune Study). This report outlines the conduct of the PPMS Study, whether the POMS sample is representative, and the planned analysis methods. The study includes 155 POMS, 204 ROMS, and 558 controls. The distributions of the POMS were largely similar to Australian POMS patients in the MSBase Study, with 54.8% female, 85.8% POMS born before 1970, mean age of onset of 41.44 ± 8.38 years old, and 67.1% living between 28.9 and 39.4° S. The POMS were representative of the Australian POMS population. There are some differences between POMS and ROMS/controls (mean age at interview: POMS 55 years vs. controls 40 years; sex: POMS 53% female vs. controls 78% female; location of residence: 14.3% of POMS at a latitude ≤ 28.9°S vs. 32.8% in controls), which will be taken into account in the analysis. We discuss the methodological issues considered in the study design, including prevalence-incidence bias, cohort effects, interview bias and recall bias, and present strategies to account for it. Associations between exposures of interest and POMS/ROMS will be presented in subsequent publications., (© 2023. The Author(s).)
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- 2024
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47. Comparative effectiveness and cost-effectiveness of natalizumab and fingolimod in rapidly evolving severe relapsing-remitting multiple sclerosis in the United Kingdom.
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Spelman T, Herring WL, Acosta C, Hyde R, Jokubaitis VG, Pucci E, Lugaresi A, Laureys G, Havrdova EK, Horakova D, Izquierdo G, Eichau S, Ozakbas S, Alroughani R, Kalincik T, Duquette P, Girard M, Petersen T, Patti F, Csepany T, Granella F, Grand'Maison F, Ferraro D, Karabudak R, Jose Sa M, Trojano M, van Pesch V, Van Wijmeersch B, Cartechini E, McCombe P, Gerlach O, Spitaleri D, Rozsa C, Hodgkinson S, Bergamaschi R, Gouider R, Soysal A, Castillo-Triviño, Prevost J, Garber J, de Gans K, Ampapa R, Simo M, Sanchez-Menoyo JL, Iuliano G, Sas A, van der Walt A, John N, Gray O, Hughes S, De Luca G, Onofrj M, Buzzard K, Skibina O, Terzi M, Slee M, Solaro C, Oreja-Guevara, Ramo-Tello C, Fragoso Y, Shaygannejad V, Moore F, Rajda C, Aguera Morales E, and Butzkueven H
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- Humans, Natalizumab therapeutic use, Fingolimod Hydrochloride therapeutic use, Immunosuppressive Agents therapeutic use, Cost-Effectiveness Analysis, Cost-Benefit Analysis, State Medicine, United Kingdom, Multiple Sclerosis, Relapsing-Remitting drug therapy, Multiple Sclerosis drug therapy
- Abstract
Aim: To evaluate the real-world comparative effectiveness and the cost-effectiveness, from a UK National Health Service perspective, of natalizumab versus fingolimod in patients with rapidly evolving severe relapsing-remitting multiple sclerosis (RES-RRMS)., Methods: Real-world data from the MSBase Registry were obtained for patients with RES-RRMS who were previously either naive to disease-modifying therapies or had been treated with interferon-based therapies, glatiramer acetate, dimethyl fumarate, or teriflunomide (collectively known as BRACETD). Matched cohorts were selected by 3-way multinomial propensity score matching, and the annualized relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M) were compared between treatment groups. Comparative effectiveness results were used in a cost-effectiveness model comparing natalizumab and fingolimod, using an established Markov structure over a lifetime horizon with health states based on the Expanded Disability Status Scale. Additional model data sources included the UK MS Survey 2015, published literature, and publicly available sources., Results: In the comparative effectiveness analysis, we found a significantly lower ARR for patients starting natalizumab compared with fingolimod (rate ratio [RR] = 0.65; 95% confidence interval [CI], 0.57-0.73) or BRACETD (RR = 0.46; 95% CI, 0.42-0.53). Similarly, CDI6M was higher for patients starting natalizumab compared with fingolimod (hazard ratio [HR] = 1.25; 95% CI, 1.01-1.55) and BRACETD (HR = 1.46; 95% CI, 1.16-1.85). In patients starting fingolimod, we found a lower ARR (RR = 0.72; 95% CI, 0.65-0.80) compared with starting BRACETD, but no difference in CDI6M (HR = 1.17; 95% CI, 0.91-1.50). Differences in CDW6M were not found between the treatment groups. In the base-case cost-effectiveness analysis, natalizumab dominated fingolimod (0.302 higher quality-adjusted life-years [QALYs] and £17,141 lower predicted lifetime costs). Similar cost-effectiveness results were observed across sensitivity analyses., Conclusions: This MSBase Registry analysis suggests that natalizumab improves clinical outcomes when compared with fingolimod, which translates to higher QALYs and lower costs in UK patients with RES-RRMS.
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- 2024
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48. Predictors of treatment switching in the Big Multiple Sclerosis Data Network.
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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 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, and Hillert J
- 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., Competing Interests: TSp received compensation for serving on scientific advisory boards, honoraria for consultancy and funding for travel from Biogen; and speaker honoraria from Novartis. MM has served on the scientific advisory board for Sanofi, Novartis, and Merck and has received honoraria for lecturing from Biogen, Merck, Novartis, Roche, Genzyme, and Bristol Myers Squibb. HB is an employee of Monash University and has accepted travel compensation from Merck; his institution receives honoraria for talks, steering committee activities, and research grants from Roche, Merck, Biogen, Novartis, UCB Pharma, Medical Research Future Fund Australia, NHMRC Australia, Trish MS Foundation, MS Australia, and the Pennycook Foundation. He receives personal compensation for steering group activities for the Brain Health Initiative from the Oxford Health Policy Forum and is funded by an NHMRC Australia Investigator Grant. SV received consulting and lecturing fees, travel grants, and research support from Biogen, Celgene, Genentech, Genzyme, Medday Pharmaceuticals, Merck Serono, Novartis, Roche, Sanofi Aventis, and Teva Pharma. MT has served on scientific advisory boards for Biogen, Novartis, Roche, and Genzyme; has received speaker honoraria and travel support from Biogen Idec, Sanofi Aventis, Merck Serono, Teva, Genzyme, and Novartis; and has received research grants for her institution from Biogen Idec, Merck Serono, and Novartis. PI has served on scientific advisory boards for Biogen Idec, Bayer, Teva, Roche, Merck Serono, Novartis, and Genzyme and has received funding for travel and/or speaker honoraria from Sanofi Aventis, Genzyme, Biogen Idec, Teva, Merck Serono, and Novartis. DH was supported by the Charles University Cooperation Program in Neuroscience, the project National Institute for Neurological Research (Programme EXCELES, ID Project No. LX22NPO5107) funded by the European Union (Next Generation EU), and by the General University Hospital in Prague project MH CZ-DRO-VFN64165. She also received compensation for travel, speaker honoraria, and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche, and Teva, as well as support for research activities from Biogen Idec. FP is an employee of Biogen. RH is an employee of Biogen and holds stock. PD served on editorial boards and has been supported to attend meetings by EMD, Biogen, Novartis, Genzyme, and TEVA Neuroscience. He holds grants from the CIHR and the MS Society of Canada and has received funding for investigator-initiated trials from Biogen, Novartis, and Genzyme. JL-S received travel compensation from Novartis, Biogen, Roche, and Merck. Her institution receives honoraria for talks and advisory board commitments, as well as research grants from Biogen, Merck, Roche, TEVA, and Novartis. SS declared no competing interests. PL received honoraria for speaking and/or travel expenses from Biogen, Merck, Novartis, Roche; consulting fees from Biogen, GeNeuro, Merck, Novartis, Roche; and research support from Biogen, Merck, Novartis. None were related to this work. SE received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche, and Teva. RAI received honoraria as a speaker and for serving on scientific advisory boards from Bayer, Biogen, GSK, Merck, Novartis, Roche, and Sanofi-Genzyme. MT received travel grants from Novartis, Bayer-Schering, Merck, and Teva; and has participated in clinical trials by Sanofi Aventis, Roche, and Novartis. MG received consulting fees from Teva Canada Innovation, Biogen, Novartis, and Genzyme Sanofi; and lecture payments from Teva Canada Innovation, Novartis, and EMD. He has also received a research grant from the Canadian Institutes of Health Research. TK served on scientific advisory boards for MS International Federation and World Health Organization, BMS, Roche, Janssen, Sanofi Genzyme, Novartis, Merck, and Biogen; on the steering committee for Brain Atrophy Initiative by Sanofi Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Roche, Sanofi-Genzyme, Teva, BioCSL, and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene, and Merck. FG received honoraria or research funding from Biogen, Genzyme, Novartis, Teva Neurosciences, and ATARA Pharmaceuticals. OS received honoraria and consulting fees from Bayer-Schering, Novartis, Merck, Biogen, and Genzyme. SK received compensation for scientific advisory board activity from Merck and Roche. BY received honoraria as a speaker and member of scientific advisory boards from Sanofi, Bayer, Biogen, Merck, Janssen, Novartis, Roche, and Aspen. MJ received consulting fees, speaker honoraria, and/or travel expenses for scientific meetings from Alexion, Bayer Healthcare, Biogen, Bristol Myers Squibb, Celgene, Janssen, Merck Serono, Novartis, Roche, Sanofi, and Teva. YB received speaker honoraria/consulting fees from Merck, Biogen, Roche, Bristol Myers Squibb, Novartis, Sanofi, and Sandoz. CO-G received honoraria as a consultant on scientific advisory boards from Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme, and TEVA. AA received speaker honoraria from Novartis and Alexion. SH has received unrestricted educational grants or speaking honoraria from Biogen, Merck Serono, Novartis, Roche, and Sanofi Genzyme. PM received speaker fees and travel grants from Novartis, Biogen, T'évalua, and Sanofi. RAm received conference travel support from Novartis, Teva, Biogen, Bayer, and Merck and has participated in clinical trials by Biogen, Novartis, Teva, and Actelion. KdG served on scientific advisory boards for Roche, Janssen, Sanofi-Genzyme, Novartis, and Merck, received conference fees and travel support from Novartis, Biogen, Sanofi-Genzyme, Teva, AbbVie, and Merck, and received educational event support from Novartis. CM received honoraria as a consultant on scientific advisory boards for Genzyme, BMS, Janssen, Biogen, Merck, Roche, and Novartis; has received travel grants from Roche and Novartis. JP accepted travel compensation from Novartis, Biogen, Genzyme, Teva, and speaking honoraria from Biogen, Novartis, Genzyme, and Teva. NJ is a local principal investigator on commercial studies funded by Novartis, Biogen, Amicus, and Sanofi. JI declared no competing interests. FS has served on scientific advisory boards for, served as a consultant for, received support for congress participation, or received speaker honoraria from Alexion, Biogen, Bristol Myers Squibb, Merck, Novartis, Roche, and Sanofi Genzyme. His laboratory has received research support from Biogen, Merck, Novartis, Roche, and Sanofi Genzyme. HJ declared no competing interests. PR has served on scientific advisory boards for, served as consultant for, received support for congress participation, or received speaker honoraria from Alexion, Biogen, Bristol Myers Squibb, Merck, Novartis, Roche, and Sanofi Genzyme. TSe received and has served on scientific advisory boards for, served as a consultant for, received support for congress participation, or received speaker honoraria from Biogen, Merck, Novartis, Roche, and Sanofi. T. Sejbaeks received unrestricted research grants to his research institution from Biogen, Merck, and Roche and is currently engaged in sponsor-initiated research projects by Eisai, Lundbeck, Roche, and Sanofi. MP declared no competing interests. JC has received speaker honoraria from Biogen. MS has served on scientific advisory boards for, served as a consultant for, received support for congress participation, participated in industrial trials with, or received speaker honoraria from Bayer, Biogen, Merck, Novartis, Roche, and Sanofi Genzyme. JH has received honoraria for serving on advisory boards for Biogen, Sanofi-Genzyme, and Novartis and speaker's fees from Biogen, Novartis, Merck Serono, Bayer-Schering, Teva, and Sanofi-Genzyme. He has served as P.I. for projects or received unrestricted research support from BiogenIdec, Merck Serono, TEVA, Sanofi-Genzyme, and Bayer-Schering. His MS research is funded by the Swedish Research Council and the Swedish Brain Foundation. The authors declare that this study received funding from Biogen. The funder had the following involvement with the study: study design and manuscript review. The funder was not involved in the collection of data, analysis, writing of the article, or the decision to submit it for publication. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (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.)
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- 2023
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49. Risk of secondary progressive multiple sclerosis after early worsening of disability.
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Dzau W, Sharmin S, Patti F, Izquierdo G, Eichau S, Prat A, Girard M, Duquette P, Onofrj M, Lugaresi A, Ozakbas S, Gerlach O, Boz C, Grammond P, Terzi M, Amato MP, La Spitaleri D, Ramo-Tello C, Maimone D, Cartechini E, Buzzard K, Skibina O, van der Walt A, Butzkueven H, Iuliano G, Soysal A, and Kalincik T
- Subjects
- Male, Humans, Adult, Female, Disease Progression, Australia epidemiology, Recurrence, Multiple Sclerosis, Chronic Progressive epidemiology, Multiple Sclerosis, Chronic Progressive drug therapy, Multiple Sclerosis drug therapy, Multiple Sclerosis, Relapsing-Remitting epidemiology, Multiple Sclerosis, Relapsing-Remitting drug therapy
- Abstract
Background: Whether progression independent of relapse activity (PIRA) heralds earlier onset of secondary progressive multiple sclerosis (SPMS) and more rapid accumulation of disability during SPMS remains to be determined. We investigated the association between early PIRA, relapse-associated worsening (RAW) of disability and time to SPMS, subsequent disability progression and their response to therapy., Methods: This observational cohort study included patients with relapsing-remitting multiple sclerosis (RRMS) from the MSBase international registry across 146 centres and 39 countries. Associations between the number of PIRA and RAW during early multiple sclerosis (MS) (the initial 5 years of MS onset) were analysed with respect to: time to SPMS using Cox proportional hazards models adjusted for disease characteristics; and disability progression during SPMS, calculated as the change of Multiple Sclerosis Severity Scores over time, using multivariable linear regression., Results: 10 692 patients met the inclusion criteria: 3125 (29%) were men and the mean MS onset age was 32.2 years. A higher number of early PIRA (HR=1.50, 95% CI 1.28 to 1.76, p<0.001) and RAW (HR=2.53, 95% CI 2.25 to 2.85, p<0.001) signalled a higher risk of SPMS. A higher proportion of early disease-modifying therapy exposure (per 10%) reduced the effect of early RAW (HR=0.94, 95% CI 0.89 to 1.00, p=0.041) but not PIRA (HR=0.97, 95% CI 0.91 to 1.05, p=0.49) on SPMS risk. No association between early PIRA/RAW and disability progression during SPMS was found., Conclusions: Early disability increase during RRMS is associated with a greater risk of SPMS but not the rate of disability progression during SPMS. The deterioration associated with early relapses represents a potentially treatable risk factor of SPMS., Trial Registration Number: Australian New Zealand Clinical Trials Registry (ACTRN12605000455662)., Competing Interests: Competing interests: WD has nothing to declare. SS has nothing to declare. FP received speaker honoraria and advisory board fees from Almirall, Bayer, Biogen, Celgene, Merck, Novartis, Roche, Sanofi-Genzyme and TEVA. He received research funding from Biogen, Merck, FISM (Fondazione Italiana Sclerosi Multipla), Reload Onlus Association and University of Catania. GI received speaking honoraria from Biogen, Novartis, Sanofi, Merck, Roche, Almirall and Teva. SE received speaker honoraria and consultant fees from Biogen Idec, Novartis, Merck, Bayer, Sanofi Genzyme, Roche and Teva. AP has nothing to declare. MG received consulting fees from Teva Canada Innovation, Biogen, Novartis and Genzyme Sanofi; lecture payments from Teva Canada Innovation, Novartis and EMD. He has also received a research grant from Canadian Institutes of Health Research. PD served on editorial boards and has been supported to attend meetings by EMD, Biogen, Novartis, Genzyme, and TEVA Neuroscience. He holds grants from the CIHR and the MS Society of Canada and has received funding for investigator-initiated trials from Biogen, Novartis, and Genzyme. MO has nothing to declare. AL has received personal compensation for consulting, serving on a scientific advisory board, speaking or other activities from Biogen, Merck Serono, Mylan, Novartis, Roche, Sanofi/Genzyme, Teva. Her institutions have receved research grants from Novartis [last 4 yrs]. SO has nothing to declare. OG has nothing to declare. CB received conference travel support from Biogen, Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. PG has served in advisory boards for Novartis, EMD Serono, Roche, Biogen idec, Sanofi Genzyme, Pendopharm and has received grant support from Genzyme and Roche, has received research grants for his institution from Biogen idec, Sanofi Genzyme, EMD Serono. MT received travel grants from Novartis, Bayer-Schering, Merck and Teva; has participated in clinical trials by Sanofi Aventis, Roche and Novartis. MPA received honoraria as consultant on scientific advisory boards by Biogen, Bayer-Schering, Merck, Teva and Sanofi-Aventis; has received research grants by Biogen, Bayer-Schering, Merck, Teva and Novartis. DS received honoraria as a consultant on scientific advisory boards by Bayer-Schering, Novartis and Sanofi-Aventis and compensation for travel from Novartis, Biogen, Sanofi Aventis, Teva and Merck. CR-T received research funding, compensation for travel or speaker honoraria from Biogen, Novartis, Genzyme and Almirall. DM received speaker honoraria for Advisory Board and travel grants from Almirall, Biogen, Merck, Novartis, Roche, Sanofi-Genzyme, and Teva. EC has nothing to declare. TK served on scientific advisory boards for BMS, Roche, Sanofi Genzyme, Novartis, Merck and Biogen, steering committee for Brain Atrophy Initiative by Sanofi Genzyme, received conference travel support and/or speaker honoraria from WebMD Global, Eisai, Novartis, Biogen, Sanofi-Genzyme, Teva, BioCSL and Merck and received research or educational event support from Biogen, Novartis, Genzyme, Roche, Celgene and Merck. KB received honoraria and consulting fees from Biogen, Teva, Novartis, Genzyme-Sanofi, Roche, Merck, CSL and Grifols. OS has nothing to declare. AvdW has nothing to declare. HB Institution (Monash university) has received compensation for consulting, talks, advisory/steering board activities from Biogen, Merck, Novartis, Genzyme, Alfred Health; research support from Novartis, Biogen, Roche, Merck, NHMRC, Pennycook Foundation, MSRA. HB has received compensation for same activities from Oxford Health Policy Forum, Merck, Biogen, Novartis. GI had travel/accommodations/meeting expenses funded by Bayer Schering, Biogen, Merck, Novartis, Sanofi Aventis, and Teva. AS has nothing to declare., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2023
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50. Effectiveness of multiple disease-modifying therapies in relapsing-remitting multiple sclerosis: causal inference to emulate a multiarm randomised trial.
- Author
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Diouf I, Malpas CB, Sharmin S, Roos I, Horakova D, Kubala Havrdova E, Patti F, Shaygannejad V, Ozakbas S, Eichau S, Onofrj M, Lugaresi A, Alroughani R, Prat A, Duquette P, Terzi M, Boz C, Grand'Maison F, Sola P, Ferraro D, Grammond P, Yamout B, Altintas A, Gerlach O, Lechner-Scott J, Bergamaschi R, Karabudak R, Iuliano G, McGuigan C, Cartechini E, Hughes S, Sa MJ, Solaro C, Kappos L, Hodgkinson S, Slee M, Granella F, de Gans K, McCombe PA, Ampapa R, van der Walt A, Butzkueven H, Sánchez-Menoyo JL, Vucic S, Laureys G, Sidhom Y, Gouider R, Castillo-Trivino T, Gray O, Aguera-Morales E, Al-Asmi A, Shaw C, Al-Harbi TM, Csepany T, Sempere AP, Treviño Frenk I, Stuart EA, and Kalincik T
- Subjects
- Humans, Pregnancy, Female, Glatiramer Acetate therapeutic use, Fingolimod Hydrochloride therapeutic use, Immunosuppressive Agents therapeutic use, Natalizumab therapeutic use, Dimethyl Fumarate therapeutic use, Interferon-beta therapeutic use, Recurrence, Multiple Sclerosis, Relapsing-Remitting drug therapy, Multiple Sclerosis drug therapy
- Abstract
Background: Simultaneous comparisons of multiple disease-modifying therapies for relapsing-remitting multiple sclerosis (RRMS) over an extended follow-up are lacking. Here we emulate a randomised trial simultaneously comparing the effectiveness of six commonly used therapies over 5 years., Methods: Data from 74 centres in 35 countries were sourced from MSBase. For each patient, the first eligible intervention was analysed, censoring at change/discontinuation of treatment. The compared interventions included natalizumab, fingolimod, dimethyl fumarate, teriflunomide, interferon beta, glatiramer acetate and no treatment. Marginal structural Cox models (MSMs) were used to estimate the average treatment effects (ATEs) and the average treatment effects among the treated (ATT), rebalancing the compared groups at 6-monthly intervals on age, sex, birth-year, pregnancy status, treatment, relapses, disease duration, disability and disease course. The outcomes analysed were incidence of relapses, 12-month confirmed disability worsening and improvement., Results: 23 236 eligible patients were diagnosed with RRMS or clinically isolated syndrome. Compared with glatiramer acetate (reference), several therapies showed a superior ATE in reducing relapses: natalizumab (HR=0.44, 95% CI=0.40 to 0.50), fingolimod (HR=0.60, 95% CI=0.54 to 0.66) and dimethyl fumarate (HR=0.78, 95% CI=0.66 to 0.92). Further, natalizumab (HR=0.43, 95% CI=0.32 to 0.56) showed a superior ATE in reducing disability worsening and in disability improvement (HR=1.32, 95% CI=1.08 to 1.60). The pairwise ATT comparisons also showed superior effects of natalizumab followed by fingolimod on relapses and disability., Conclusions: The effectiveness of natalizumab and fingolimod in active RRMS is superior to dimethyl fumarate, teriflunomide, glatiramer acetate and interferon beta. This study demonstrates the utility of MSM in emulating trials to compare clinical effectiveness among multiple interventions simultaneously., Competing Interests: Competing interests: The authors report the following relationships: speaker honoraria, advisory board or steering committee fees, research support and/or conference travel support from Acthelion (EKH, RA), Almirall (MT, FG, RB, CRT, JLS-M), Bayer (MT, AL, PS, RA, MT, CB, JL-S, EP, VVP, RB, DS, RA, JO, JLSM, SH, CR, AGK, TC, NS, BT, MS, CAS), BioCSL (TK, AGK, BT), Biogen (TK, TS, DH, EKH, MT, GI, AL, MG, PD, PG, VJ, AVW, FG, PS, DF, RA, RH, CB, JLS, EP, VVP, FG, RB, RA, CRT, JP, JO, MB, JLSM, SH, CR, CSh, OGerlach, AGK, TC, BS, NS, BT, MS, HB), Biologix (RA), BMS/Celgene (EKH, AL), Genpharm (RA), Genzyme-Sanofi (TK, EKH, MT, GI, AL, MG, PD, PG, AVW, FG, PS, DF, RA, RH, MT, CB, JLS, EP, EP, VVP, FG, RB, RB, DS, CRT, JP, JO, MB, JLSM, SH, O Gerlach, AGK, HB), GSK (RA), Innate Immunotherapeutics (AGK), Lundbeck (EP), Merck / EMD (TK, DH, EKH, MT, GI, AL(Merck Serono), MG, PD, PG, VJ, AVW, PS, DF, RA, RH, MT, CB, JLS, EP, VVP, FG, RB, DS, RA, JO, MB, JLSM, CR, FM, O Gerlach, AGK, TC, BS, MS, HB), Mitsubishi (FG),Novartis (TK, TS, DH, EKH, MT, GI, AL, MG, PD, PG, VJ, AVW, FG, PS, DF, RA, RH, MT, CB, JLS, EP, VVP, FG, RB, DS, RA, CRT, JP, JO, MB, JLSM, SH, CR, FM, CSh, OG, AGK, TC, NS, BT, MS, HB), ONO Pharmaceuticals (FG), Roche (TK, EKH, AL, MT, CB, VVP, BT), Teva (TK, DH, EKH, MT, GI, AL, MG, PD, PG, VJ, FG, PS, DF, RH, MT, CB, JLS, VVP, RB, DS, RA, JP, JO, JLSM, CR, AGK, TC, MS, CAS), WebMD (TK), UCB (EP)., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)
- Published
- 2023
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