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001-es BibID:BIBFORM120944
035-os BibID:(Scopus)85122546501
Első szerző:Brouwer, Edward De
Cím:Corrigendum to Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression : [Computer Methods and Programs in Biomedicine, Volume 208, (September 2021) 106180] / Edward De Brouwer, Thijs Becker, Yves Moreau, Eva Kubala Havrdova, Maria Trojano, Sara Eichau, Serkan Ozakbas, Marco Onofrj, Pierre Grammond, Jens Kuhle, Ludwig Kappos, Patrizia Sola, Elisabetta Cartechini, Jeannette Lechner-Scott, Raed Alroughani, Oliver Gerlach, Tomas Kalincik, Franco Granella, Francois Grand'Maison, Roberto Bergamaschi, Maria José Sá, Bart Van Wijmeersch, Aysun Soysal, Jose Luis Sanchez-Menoyo, Claudio Solaro, Cavit Boz, Gerardo Iuliano, Katherine Buzzard, Eduardo Aguera-Morales, Murat Terzi, Tamara Castillo Trivio, Daniele Spitaleri, Vincent Van Pesch, Vahid Shaygannejad, Fraser Moore, Celia Oreja-Guevara, Davide Maimone, Riadh Gouider, Tunde Csepany, Cristina Ramo-Tello, Liesbet Peeters
Dátum:2022
ISSN:0169-2607
Megjegyzések: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.
Tárgyszavak:Orvostudományok Klinikai orvostudományok hozzászólás
folyóiratcikk
Multiple sclerosis
Machine learning
Longitudinal data
Recurrent neural networks
Electronic health records
Disability progression
Real-world data
Megjelenés:Computer Methods And Programs In Biomedicine. - 213 (2022), p. 1-3. -
További szerzők:Becker, Thijs Moreau, Yves Havrdova, Eva Trojano, Maria Eichau, Sara Ozakbas, Serkan Onofrj, Marco Grammond, Pierre Kuhle, Jens Kappos, Ludwig Sola, Patrizia Cartechini, Elisabetta Lechner-Scott, Jeannette Alroughani, Raed Gerlach, Oliver Kalincik, Tomas Granella, Franco Grand'Maison, Francois Bergamaschi, Roberto Sá, Maria José Wijmeersch, Bart Van Soysal, Aysun Sanchez-Menoyo, Jose Solaro, Claudio Boz, Cavit Iuliano, Gerardo Buzzard, Katherine Aguera-Morales, Eduardo Terzi, Murat Trivio, Tamara Castillo Spitaleri, Daniele Pesch, Vincent van Shaygannejad, Vahid Moore, Fraser Oreja-Guevara, Celia Maimone, Davide Gouider, Riadh Csépány Tünde (1956-) (neurológus, pszichiáter) Ramo-Tello, Cristina Peeters, Liesbet
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2.

001-es BibID:BIBFORM126277
035-os BibID:(scopus)85201493485
Első szerző:De Brouwer, Edward
Cím:Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study / 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 S. J., Cartechini E., Van Pesch V., Sa M. J., Weinstock-Guttman B., Blanco Y., Ampapa R., Spitaleri D., Solaro C., Maimone D., Soysal A., Iuliano G., Gouider R., Castillo-Trivino T., Sánchez-Menoyo J. L., 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 A. P., Mihaela S., Simo M., Hardy T., Decoo D., Hughes S., Grigoriadis N., Sas A., Vella N., Moreau Y., Peeters L.
Dátum:2024
ISSN:2767-3170
Megjegyzések: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.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Machine learning
disability progression
multiple sclerosis
Megjelenés:PLOS Digital Health. - 3 : 7 (2024), p. 1-25. -
További szerzők:Becker, Thijs Werthen-Brabants, Lorin Dewulf, Pieter Iliadis, Dimitrios Dekeyser, Cathérine Laureys, Guy Wijmeersch, Bart Van Popescu, Veronica Dhaene, Tom Deschrijver, Dirk Waegeman, Willem De Baets, Bernard Stock, Michael J. Horakova, Dana Patti, Francesco Izquierdo, Guillermo Eichau, Sara Girard, Marc Prat, Alexandre Lugaresi, Alessandra Grammond, Pierre Kalincik, Tomas Alroughani, Raed Grand'Maison, Francois Skibina, Olga Terzi, Murat Lechner-Scott, Jeannette Gerlach, Oliver Khoury, Samia J. Cartechini, Elisabetta Pesch, Vincent van Sá, Maria José Weinstock-Guttman, Bianca Blanco, Yolanda Ampapa, Radek Spitaleri, Daniele Solaro, Claudio Maimone, Davide Soysal, Aysun Iuliano, Gerardo Gouider, Riadh Castillo Triviño, Tamara Sanchez-Menoyo, Jose Laureys, Guy (Universitary Hospital Ghent) Walt, Anneke van der Oh, Jiwon Aguera-Morales, Eduardo Altintas, Ayse Al-Asmi, Abdullah de Gans, Koen Fragoso, Yara Csépány Tünde (1956-) (neurológus, pszichiáter) Hodgkinson, Suzanne Deri, Norma Al-Harbi, Talal Taylor, Bruce V. Gray, Orla Lalive, Patrice H. Rózsa Csilla McGuigan, Christopher Kermode, Allan G. Sempere, Perez A. Mihaela, Simu Simó Magdolna Hardy, Todd A. Decoo, Danny Hughes, Stella Grigoriadis, Nikolaos Sas Attila Vella Norbert Moreau, Yves Peeters, Liesbet
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Intézményi repozitóriumban (DEA) tárolt változat
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3.

001-es BibID:BIBFORM103017
035-os BibID:(Wos)000685503300008 (Scopus)85107912293
Első szerző:De Brouwer, Edward
Cím:Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression / De Brouwer Edward, Becker Thijs, Moreau Yves, Havrdova Eva Kubala, Trojano Maria, Eichau Sara, Ozakbas Serkan, Onofrj Marco, Grammond Pierre, Kuhle Jens, Kappos Ludwig, Sola Patrizia, Cartechini Elisabetta, Lechner-Scott Jeannette, Alroughani Raed, Gerlach Oliver, Kalincik Tomas, Granella Franco, Grand'Maison Francois, Bergamaschi Roberto, José Sá Maria, Van Wijmeersch Bart, Soysal Aysun, Sanchez-Menoyo Jose Luis, Solaro Claudio, Boz Cavit, Iuliano Gerardo, Buzzard Katherine, Aguera-Morales Eduardo, Terzi Murat, Trivio Tamara Castillo, Spitaleri Daniele, Van Pesch Vincent, Shaygannejad Vahid, Moore Fraser, Oreja-Guevara Celia, Maimone Davide, Gouider Riadh, Csepany Tunde, Ramo-Tello Cristina, Peeters Liesbet
Dátum:2021
ISSN:0169-2607
Megjegyzések: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.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Computer Methods And Programs In Biomedicine. - 208 (2021), p. 1-14. -
További szerzők:Becker, Thijs Moreau, Yves Havrdova, Eva Trojano, Maria Eichau, Sara Ozakbas, Serkan Onofrj, Marco Grammond, Pierre Kuhle, Jens Kappos, Ludwig Sola, Patrizia Cartechini, Elisabetta Lechner-Scott, Jeannette Alroughani, Raed Gerlach, Oliver Kalincik, Tomas Granella, Franco Grand'Maison, Francois Bergamaschi, Roberto José Sá, Maria Wijmeersch, Bart Van Soysal, Aysun Sanchez-Menoyo, Jose Solaro, Claudio Boz, Cavit Iuliano, Gerardo Buzzard, Katherine Aguera-Morales, Eduardo Terzi, Murat Trivio, Tamara Castillo Spitaleri, Daniele Pesch, Vincent van Shaygannejad, Vahid Moore, Fraser Oreja-Guevara, Celia Maimone, Davide Gouider, Riadh Csépány Tünde (1956-) (neurológus, pszichiáter) Ramo-Tello, Cristina Peeters, Liesbet
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Intézményi repozitóriumban (DEA) tárolt változat
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4.

001-es BibID:BIBFORM126270
035-os BibID:(scopus)85190160325 (wos)001201473600001
Első szerző:Dekeyser, Cathérine
Cím:Routine CSF parameters as predictors of disease course in multiple sclerosis : an MSBase cohort study / Dekeyser C., Hautekeete M., Cambron M., Van Pesch V., Patti F., Kuhle J., Khoury S., Lechner Scott J., Gerlach O., Lugaresi A., Maimone D., Surcinelli A., Grammond P., Kalincik T., Habek M., Willekens B., Macdonell R., Lalive P., Csepany T., Butzkueven H., Boz C., Tomassini V., Foschi M., Sánchez-Menoyo J. L., Altintas A., Mrabet S., Iuliano G., Sa M. J., Alroughani R., Karabudak R., Aguera-Morales E., Gray O., de Gans K., van der Walt A., McCombe P. A., Deri N., Garber J., Al-Asmi A., Skibina O., Duquette P., Cartechini E., Spitaleri D., Gouider R., Soysal A., Van Hijfte L., Slee M., Amato M. P., Buzzard K., Laureys G.
Dátum:2024
ISSN:0022-3050 1468-330X
Megjegyzések:Background: It remains unclear whether routine cerebrospinal fluid (CSF) parameters can serve as predictors of multiple sclerosis (MS) disease course. Methods: This large-scale cohort study included persons with MS with CSF data documented in the MSBase registry. CSF parameters to predict time to reach confirmed Expanded Disability Status Scale (EDSS) scores 4, 6 and 7 and annualised relapse rate in the first 2 years after diagnosis (ARR2) were assessed using (cox) regression analysis. Results: In total, 11 245 participants were included of which 93.7% (n=10 533) were persons with relapsing-remitting MS (RRMS). In RRMS, the presence of CSF oligoclonal bands (OCBs) was associated with shorter time to disability milestones EDSS 4 (adjusted HR=1.272 (95% CI, 1.089 to 1.485), p=0.002), EDSS 6 (HR=1.314 (95% CI, 1.062 to 1.626), p=0.012) and EDSS 7 (HR=1.686 (95% CI, 1.111 to 2.558), p=0.014). On the other hand, the presence of CSF pleocytosis (?5 cells/?L) increased time to moderate disability (EDSS 4) in RRMS (HR=0.774 (95% CI, 0.632 to 0.948), p=0.013). None of the CSF variables were associated with time to disability milestones in persons with primary progressive MS (PPMS). The presence of CSF pleocytosis increased ARR2 in RRMS (adjusted R2=0.036, p=0.015). Conclusions: In RRMS, the presence of CSF OCBs predicts shorter time to disability milestones, whereas CSF pleocytosis could be protective. This could however not be found in PPMS. CSF pleocytosis is associated with short-term inflammatory disease activity in RRMS. CSF analysis provides prognostic information which could aid in clinical and therapeutic decision-making.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
CLINICAL NEUROLOGY
CSF
MULTIPLE SCLEROSIS
NEUROIMMUNOLOGY
Megjelenés:Journal of Neurology, Neurosurgery, and Psychiatry . - 95 : 11 (2024), p. 1021-1031. -
További szerzők:Hautekeete, Matthias Cambron, Melissa Pesch, Vincent van Patti, Francesco Kuhle, Jens Khoury, Samia J. Lechner Scott, Jeanette Gerlach, Oliver Lugaresi, Alessandra Maimone, Davide Surcinelli, Andrea Grammond, Pierre Kalincik, Tomas Habek, Mario Willekens, Barbara Macdonell, Richard Lalive, Patrice H. Csépány Tünde (1956-) (neurológus, pszichiáter) Butzkueven, Helmut Boz, Cavit Tomassini, Valentina Foschi, Matteo Sanchez-Menoyo, Jose Altintas, Ayse Mrabet, Saloua Iuliano, Gerardo Sá, Maria José Alroughani, Raed Karabudak, Rana Aguera-Morales, Eduardo Gray, Orla de Gans, Koen Walt, Anneke van der McCombe, Pamela Deri, Norma Garber, Justin Al-Asmi, Abdullah Skibina, Olga Duquette, Pierre Cartechini, Elisabetta Spitaleri, Daniele Gouider, Riadh Soysal, Aysun Van Hijfte, Liesbeth Slee, Mark Amato, Maria Pia Buzzard, Katherine Laureys, Guy
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Intézményi repozitóriumban (DEA) tárolt változat
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5.

001-es BibID:BIBFORM119146
035-os BibID:(scopus)85177103067 (wos)001030569800001
Első szerző:Diouf, Ibrahima
Cím:Effectiveness of multiple disease-modifying therapies in relapsing-remitting multiple sclerosis : causal inference to emulate a multiarm randomised trial / Diouf Ibrahima, Malpas Charles B., Sharmin Sifat, Roos Izanne, Horakova Dana, Kubala Havrdova Eva, Patti Francesco, Shaygannejad Vahid, Ozakbas Serkan, Eichau Sara, Onofrj Marco, Lugaresi Alessandra, Alroughani Raed, Prat Alexandre, Duquette Pierre, Terzi Murat, Boz Cavit, Grand'Maison Francois, Sola Patrizia, Ferraro Diana, Grammond Pierre, Yamout Bassem, Altintas Ayse, Gerlach Oliver, Lechner-Scott Jeannette, Bergamaschi Roberto, Karabudak Rana, Iuliano Gerardo, McGuigan Christopher, Cartechini Elisabetta, Hughes Stella, Sa Maria Jose, Solaro Claudio, Kappos Ludwig, Hodgkinson Suzanne, Slee Mark, Granella Franco, de Gans Koen, McCombe Pamela A., Ampapa Radek, van der Walt Anneke, Butzkueven Helmut, Sánchez-Menoyo José Luis, Vucic Steve, Laureys Guy, Sidhom Youssef, Gouider Riadh, Castillo-Trivino Tamara, Gray Orla, Aguera-Morales Eduardo, Al-Asmi Abdullah, Shaw Cameron, Al-Harbi Talal M., Csepany Tunde, Sempere Angel P., Trevino Frenk Irene, Stuart Elizabeth A., Kalincik Tomas
Dátum:2023
ISSN:0022-3050
Megjegyzések: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.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
MULTIPLE SCLEROSIS
STATISTICS
Megjelenés:Journal Of Neurology Neurosurgery And Psychiatry. - 94 : 12 (2023), p. 1004-1011. -
További szerzők:Malpas, Charles B. Sharmin, Sifat Roos, Izanne Horakova, Dana Kubala Havrdova, Eva Patti, Francesco Shaygannejad, Vahid Ozakbas, Serkan Eichau, Sara Onofrj, Marco Lugaresi, Alessandra Alroughani, Raed Prat, Alexandre Duquette, Pierre Terzi, Murat Boz, Cavit Grand'Maison, Francois Sola, Patrizia Ferraro, Diana Grammond, Pierre Yamout, Bassem Altintas, Ayse Gerlach, Oliver Lechner-Scott, Jeannette Bergamaschi, Roberto Karabudak, Rana Iuliano, Gerardo McGuigan, Christopher Cartechini, Elisabetta Hughes, Stella Sá, Maria José Solaro, Claudio Kappos, Ludwig Hodgkinson, Suzanne Slee, Mark Granella, Franco de Gans, Koen McCombe, Pamela Ampapa, Radek Walt, Anneke van der Butzkueven, Helmut Sanchez-Menoyo, Jose Vucic, Steve Laureys, Guy Sidhom, Youssef Gouider, Riadh Castillo Triviño, Tamara Gray, Orla Aguera-Morales, Eduardo Al-Asmi, Abdullah Shaw, Cameron Al-Harbi, Talal Csépány Tünde (1956-) (neurológus, pszichiáter) Sempere, Perez A. Trevino-Frenk, Irene Stuart, Elizabeth A. Kalincik, Tomas
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

6.

001-es BibID:BIBFORM107545
035-os BibID:(Scopus)85148460657 (WoS)000952991100026
Első szerző:Diouf, Ibrahima
Cím:Variability of the response to immunotherapy among subgroups of patients with multiple sclerosis / Diouf Ibrahima, Malpas Charles B., Sharmin Sifat, Roos Izanne, Horakova Dana, Havrdova Eva Kubala, Patti Francesco, Shaygannejad Vahid, Ozakbas Serkan, Izquierdo Guillermo, Eichau Sara, Onofrj Marco, Lugaresi Alessandra, Alroughani Raed, Prat Alexandre, Girard Marc, Duquette Pierre, Terzi Murat, Boz Cavit, Grand'Maison Francois, Hamdy Sherif, Sola Patrizia, Ferraro Diana, Grammond Pierre, Turkoglu Recai, Buzzard Katherine, Skibina Olga, Yamout Bassem, Altintas Ayse, Gerlach Oliver, van Pesch Vincent, Blanco Yolanda, Maimone Davide, Lechner-Scott Jeannette, Bergamaschi Roberto, Karabudak Rana, Iuliano Gerardo, McGuigan Chris, Cartechini Elisabetta, Barnett Michael, Hughes Stella, Sa Maria José, Solaro Claudio, Kappos Ludwig, Ramo-Tello Cristina, Cristiano Edgardo, Hodgkinson Suzanne, Spitaleri Daniele, Soysal Aysun, Petersen Thor, Slee Mark, Butler Ernest, Granella Franco, de Gans Koen, McCombe Pamela, Ampapa Radek, Van Wijmeersch Bart, van der Walt Anneke, Butzkueven Helmut, Prevost Julie, Sinnige L. G. F., Sanchez-Menoyo Jose Luis, Vucic Steve, Laureys Guy, Van Hijfte Liesbeth, Khurana Dheeraj, Macdonell Richard, Gouider Riadh, Castillo-Trivino Tamara, Gray Orla, Aguera-Morales Eduardo, Al-Asmi Abdullah, Shaw Cameron, Deri Norma, Al-Harbi Talal, Fragoso Yara, Csepany Tunde, Perez Sempere Angel, Trevino-Frenk Irene, Schepel Jan, Moore Fraser, Kalincik Tomas
Dátum:2023
ISSN:1351-5101
Megjegyzések:Background This study assessed the effect of patient characteristics on the response to disease modifying therapy (DMT) in in multiple sclerosis (MS). Methods We extracted data from 61,810 patients from 135 centres across 35 countries from the MSBase registry. The selection criteria were: clinically isolated syndrome or definite MS; follow-up ?1 year; ?3 EDSS scores; and with ?1 score recorded per year. Marginal structural models with interaction terms were used to compare the hazards of 12-month confirmed worsening and improvement of disability, and the incidence of relapses between treated and untreated patients stratified by their characteristics. Results Among 24,344 patients with relapsing MS, those on DMTs experienced 48% reduction in relapse incidence (hazard ratio (HR)=0.52, 95%CI=0.45-0.60), 46% lower risk of disability worsening (HR=0.54, 95%CI=0.41-0.71) and 32% greater chance of disability improvement (HR=1.32, 95%CI=1.09-1.59). The effect of DMTs on EDSS worsening and improvement and the risk of relapses was attenuated with more severe disability. The magnitude of the effect of DMT on suppressing relapses declined with higher prior relapse rate and prior cerebral MRI activity. We did not find any evidence for the effect of age on the effectiveness of DMT. After inclusion of 1985 participants with progressive MS, the effect of DMT on disability mostly depended on MS phenotype, whereas its effect on relapses was driven mainly by prior relapse activity. Conclusions DMT is generally most effective among patients with lower disability and in relapsing MS phenotypes. There is no evidence attenuation of the effect of DMT with age.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:European Journal Of Neurology. - 30 : 4 (2023), p. 1014-1024. -
További szerzők:Malpas, Charles B. Sharmin, Sifat Roos, Izanne Horakova, Dana Havrdova, Eva Patti, Francesco Shaygannejad, Vahid Ozakbas, Serkan Izquierdo, Guillermo Eichau, Sara Onofrj, Marco Lugaresi, Alessandra Alroughani, Raed Prat, Alexandre Girard, Marc Duquette, Pierre Terzi, Murat Boz, Cavit Grand'Maison, Francois Hamdy, Sherif Sola, Patrizia Ferraro, Diana Grammond, Pierre Turkoglu, Recai Buzzard, Katherine Skibina, Olga Yamout, Bassem Altintas, Ayse Gerlach, Oliver Pesch, Vincent van Blanco, Yolanda Maimone, Davide Lechner-Scott, Jeannette Bergamaschi, Roberto Karabudak, Rana Iuliano, Gerardo McGuigan, Christopher Cartechini, Elisabetta Barnett, Michael Hughes, Stella Sá, Maria José Solaro, Claudio Kappos, Ludwig Ramo-Tello, Cristina Cristiano, Edgardo Hodgkinson, Suzanne Spitaleri, Daniele Soysal, Aysun Petersen, Thor Slee, Mark Butler, Ernest Granella, Franco de Gans, Koen McCombe, Pamela Ampapa, Radek Wijmeersch, Bart Van Walt, Anneke van der Butzkueven, Helmut Prevost, Julie Sinnige, L. G. F. Sanchez-Menoyo, Jose Vucic, Steve Laureys, Guy Van Hijfte, Liesbeth Khurana, Dheeraj Macdonell, Richard Gouider, Riadh Castillo Triviño, Tamara Gray, Orla Aguera-Morales, Eduardo Al-Asmi, Abdullah Shaw, Cameron Deri, Norma Al-Harbi, Talal Fragoso, Yara Csépány Tünde (1956-) (neurológus, pszichiáter) Perez Sempere, Angel Trevino-Frenk, Irene Schepel, Jan Moore, Fraser Kalincik, Tomas
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

7.

001-es BibID:BIBFORM135463
035-os BibID:(Scopus)105025260703 (WoS)001643679600001
Első szerző:Lizak, Nathaniel
Cím:Managing reactivation of multiple sclerosis during treatment with natalizumab / Nathaniel Lizak, Sifat Sharmin, Dana Horáková, Eva Kubala Havrdova, Sara Eichau, Anneke van der Walt, Helmut Butzkueven, Jeannette Lechner-Scott, Katherine Buzzard, Olga Skibina, Oliver Gerlach, Alexandre Prat, Marc Girard, Pierre Duquette, Raed Alroughani, Francesco Patti, Francois Grand'Maison, Maria José Sá, Eduardo Aguera-Morales, Suzanne Hodgkinson, Pierre Grammond, Jens Kuhle, Bassem Yamout, Samia J. Khoury, Serkan Ozakbas, Tunde Csepany, Nevin John, Guy Laureys, Murat Terzi, Maria Pia Amato, Cavit Boz, Abdullah Al-Asmi, Elisabetta Cartechini, Riadh Gouider, Saloua Mrabet, Izanne Roos, Tomas Kalincik, MSBase Study Group
Dátum:2025
ISSN:1352-4585
Megjegyzések:Background: Following natalizumab failure, it is unknown whether switching to alternative high-efficacy therapies offers superior effectiveness over continuing natalizumab. Objective: To compare different treatment strategies following natalizumab failure. Methods: Patients suffering a relapse during natalizumab treatment with adequate follow-up were identified from the MSBase registry. Following natalizumab failure, natalizumab continuation was compared to switching to anti-CD20 therapies/alemtuzumab/lower-efficacy therapies and treatment discontinuation. The primary outcome was the risk of further relapses. Secondary outcomes included risk of subsequent magnetic resonance imaging (MRI) activity, confirmed disability worsening and disease-activity-free survival. Multivariable proportional hazards models compared outcomes during time-varying therapy exposures. Four sensitivity analyses were conducted with varied inclusion criteria and treatment failure definitions. Results: Of 1553 patients experiencing a relapse during natalizumab treatment, 1037 met the inclusion criteria. Following natalizumab failure, switch to anti-CD20 therapy was associated with a lower relapse risk (heart rate (HR) = 0.48, 95% confidence interval (CI) = 0.27?0.84) compared to continuing natalizumab; no differences were observed in MRI or disability outcomes. Treatment de-escalation or cessation was associated with increased relapse risk (HR = 1.46, 95% CI = 1.15?1.85; HR = 2.08, 95% CI = 1.223.55, respectively). We did not find evidence of a difference for switching to alemtuzumab. Sensitivity analyses replicated primary findings. Conclusion: This exploratory study indicates that switching to anti-CD20 therapies following natalizumab failure is associated with a >50% reduction in relapse risk. No differences were seen in secondary outcomes, despite consistent trends. Clinicians may consider anti-CD20 therapies following natalizumab failure, noting further research is needed to confirm differences in MRI and disability outcomes.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Multiple sclerosis
natalizumab
disease-modifying treatment
relapses
treatment failure
Megjelenés:Multiple Sclerosis. - 32 : 1 (2025), p. 121-133. -
További szerzők:Sharmin, Sifat Horakova, Dana Havrdova, Eva Eichau, Sara Walt, Anneke van der Butzkueven, Helmut Lechner-Scott, Jeannette Buzzard, Katherine Skibina, Olga Gerlach, Oliver Prat, Alexandre Girard, Marc Duquette, Pierre Alroughani, Raed Patti, Francesco Grand'Maison, Francois Sá, Maria José Aguera-Morales, Eduardo Hodgkinson, Suzanne Grammond, Pierre Kuhle, Jens Yamout, Bassem Khoury, Samia J. Ozakbas, Serkan Csépány Tünde (1956-) (neurológus, pszichiáter) John, Nevin Laureys, Guy Terzi, Murat Amato, Maria Pia Boz, Cavit Al-Asmi, Abdullah Cartechini, Elisabetta Gouider, Riadh Mrabet, Saloua Roos, Izanne Kalincik, Tomas MSBase Study Group
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

8.

001-es BibID:BIBFORM114473
035-os BibID:(Scopus)85148502832 (WoS)000951172400001
Első szerző:Roos, Izanne
Cím:Comparative effectiveness in multiple sclerosis : A methodological comparison / Roos Izanne, Diouf Ibrahima, Sharmin Sifat, Horakova Dana, Havrdova Eva Kubala, Patti Francesco, Shaygannejad Vahid, Ozakbas Serkan, Izquierdo Guillermo, Eichau Sara, Onofrj Marco, Lugaresi Alessandra, Alroughani Raed, Prat Alexandre, Girard Marc, Duquette Pierre, Terzi Murat, Boz Cavit, Grand'Maison Francois, Sola Patrizia, Ferraro Diana, Grammond Pierre, Turkoglu Recai, Buzzard Katherine, Skibina Olga, Yamout Bassem, Altintas Ayse, Gerlach Oliver, van Pesch Vincent, Blanco Yolanda, Maimone Davide, Lechner-Scott Jeannette, Bergamaschi Roberto, Karabudak Rana, McGuigan Chris, Cartechini Elisabetta, Barnett Michael, Hughes Stella, Sa Maria José, Solaro Claudio, Ramo-Tello Cristina, Hodgkinson Suzanne, Spitaleri Daniele, Soysal Aysun, Petersen Thor, Granella Franco, de Gans Koen, McCombe Pamela, Ampapa Radek, Van Wijmeersch Bart, van der Walt Anneke, Butzkueven Helmut, Prevost Julie, Sanchez-Menoyo Jose Luis, Laureys Guy, Gouider Riadh, Castillo-Trivino Tamara, Gray Orla, Aguera-Morales Eduardo, Al-Asmi Abdullah, Shaw Cameron, Deri Norma, Al-Harbi Talal, Fragoso Yara, Csepany Tunde, Sempere Angel Perez, Trevino-Frenk Irene, Schepel Jan, Moore Fraser, Malpas Charles, Kalincik Tomas, MSBase study group
Dátum:2023
ISSN:1352-4585
Megjegyzések: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.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Observational
causal inference
multiple sclerosis
Megjelenés:Multiple Sclerosis. - 29 : 3 (2023), p. 326-332. -
További szerzők:Diouf, Ibrahima Sharmin, Sifat Horakova, Dana Havrdova, Eva Patti, Francesco Shaygannejad, Vahid Ozakbas, Serkan Izquierdo, Guillermo Eichau, Sara Onofrj, Marco Lugaresi, Alessandra Alroughani, Raed Prat, Alexandre Girard, Marc Duquette, Pierre Terzi, Murat Boz, Cavit Grand'Maison, Francois Sola, Patrizia Ferraro, Diana Grammond, Pierre Turkoglu, Recai Buzzard, Katherine Skibina, Olga Yamout, Bassem Altintas, Ayse Gerlach, Oliver Pesch, Vincent van Blanco, Yolanda Maimone, Davide Lechner-Scott, Jeannette Bergamaschi, Roberto Karabudak, Rana McGuigan, Christopher Cartechini, Elisabetta Barnett, Michael Hughes, Stella Sá, Maria José Solaro, Claudio Ramo-Tello, Cristina Hodgkinson, Suzanne Spitaleri, Daniele Soysal, Aysun Petersen, Thor Granella, Franco de Gans, Koen McCombe, Pamela Ampapa, Radek Wijmeersch, Bart Van Walt, Anneke van der Butzkueven, Helmut Prevost, Julie Sanchez-Menoyo, Jose Laureys, Guy Gouider, Riadh Castillo Triviño, Tamara Gray, Orla Aguera-Morales, Eduardo Al-Asmi, Abdullah Shaw, Cameron Deri, Norma Al-Harbi, Talal Fragoso, Yara Csépány Tünde (1956-) (neurológus, pszichiáter) Sempere, Perez A. Trevino-Frenk, Irene Schepel, Jan Moore, Fraser Malpas, Charles Kalincik, Tomas MSBase Study Group
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

9.

001-es BibID:BIBFORM103566
035-os BibID:(WoS)000874431500025 (Scopus)85141339945
Első szerző:Roos, Izanne
Cím:Disease Reactivation After Cessation of Disease-Modifying Therapy in Patients With Relapsing-Remitting Multiple Sclerosis / Roos Izanne, Malpas Charles, Leray Emmanuelle, Casey Romain, Horakova Dana, Havrdova Eva Kubala, Debouverie Marc, Patti Francesco, De Seze Jerome, Izquierdo Guillermo, Eichau Sara, Edan Gilles, Prat Alexandre, Girard Marc, Ozakbas Serkan, Grammond Pierre, Zephir Helene, Ciron Jonathan, Maillart Elisabeth, Moreau Thibault, Amato Maria Pia, Labauge Pierre, Alroughani Raed, Buzzard Katherine, Skibina Olga, Terzi Murat, Laplaud David Axel, Berger Eric, Grand'Maison Francois, Lebrun-Frenay Christine, Cartechini Elisabetta, Boz Cavit, Lechner-Scott Jeannette, Clavelou Pierre, Stankoff Bruno, Prevost Julie, Kappos Ludwig, Pelletier Jean, Shaygannejad Vahid, Yamout Bassem I., Khoury Samia J., Gerlach Oliver, Spitaleri Daniele L. A., Van Pesch Vincent, Gout Olivier, Turkoglu Recai, Heinzlef Olivier, Thouvenot Eric, McCombe Pamela Ann, Soysal Aysun, Bourre Bertrand, Slee Mark, Castillo-Trivino Tamara, Bakchine Serge, Ampapa Radek, Butler Ernest Gerard, Wahab Abir, Macdonell Richard A., Aguera-Morales Eduardo, Cabre Philippe, Ben Nasr Haifa, Van der Walt Anneke, Laureys Guy, Van Hijfte Liesbeth, Ramo-Tello Cristina M., Maubeuge Nicolas, Hodgkinson Suzanne, Sánchez-Menoyo José Luis, Barnett Michael H., Labeyrie Celine, Vucic Steve, Sidhom Youssef, Gouider Riadh, Csepany Tunde, Sotoca Javier, de Gans Koen, Al-Asmi Abdullah, Fragoso Yara Dadalti, Vukusic Sandra, Butzkueven Helmut, Kalincik Tomas, MSBase and OFSEP
Dátum:2022
ISSN:0028-3878 1526-632X
Megjegyzések: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 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. Results: 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: 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 therapies. These results suggest that untreated intervals should be minimised after stopping anti-trafficking therapies (natalizumab and fingolimod). Classification of evidence: This study provides class III that disease reactivation occurs within months of discontinuation of multiple sclerosis disease-modifying therapies. Risk of disease activity is reduced by commencement of a subsequent therapy.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Neurology. - 99 : 17 (2022), p. e1926-e1944. -
További szerzők:Malpas, Charles Leray, Emmanuelle Casey, Romain Horakova, Dana Havrdova, Eva Debouverie, Marc Patti, Francesco De Seze, Jérôme Izquierdo, Guillermo Eichau, Sara Edan, Gilles Prat, Alexandre Girard, Marc Ozakbas, Serkan Grammond, Pierre Zephir, Hélène Ciron, Jonathan Maillart, Elisabeth Moreau, Thibault Amato, Maria Pia Labauge, Pierre Alroughani, Raed Buzzard, Katherine Skibina, Olga Terzi, Murat Laplaud, David Berger, Eric Grand'Maison, Francois Lebrun-Frenay, Christine Cartechini, Elisabetta Boz, Cavit Lechner-Scott, Jeannette Clavelou, Pierre Stankoff, Bruno Prevost, Julie Kappos, Ludwig Pelletier, Jean Shaygannejad, Vahid Yamout, Bassem Khoury, Samia J. Gerlach, Oliver Spitaleri, Daniele L. A. Pesch, Vincent van Gout, Olivier Turkoglu, Recai Heinzlef, Olivier Thouvenot, Eric McCombe, Pamela Soysal, Aysun Bourre, Bertrand Slee, Mark Castillo Triviño, Tamara Bakchine, Serge Ampapa, Radek Butler, Ernest Wahab, Abir Macdonell, Richard Aguera-Morales, Eduardo Cabre, Philippe Ben Nasr, Haifa Walt, Anneke van der Laureys, Guy Van Hijfte, Liesbeth Ramo-Tello, Cristina Maubeuge, Nicolas Hodgkinson, Suzanne Sanchez-Menoyo, Jose Barnett, Michael Labeyrie, Céline Vucic, Steve Sidhom, Youssef Gouider, Riadh Csépány Tünde (1956-) (neurológus, pszichiáter) Sotoca, Javier de Gans, Koen Al-Asmi, Abdullah Fragoso, Yara Vukusic, Sandra Butzkueven, Helmut Kalincik, Tomas OFSEP and the MSBase investigators
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

10.

001-es BibID:BIBFORM103333
035-os BibID:(Scopus)85090969423 (WOS)000607095300025
Első szerző:Roos, Izanne
Cím:Delay from treatment start to full effect of immunotherapies for multiple sclerosis / Roos Izanne, Leray Emmanuelle, Frascoli Federico, Casey Romain, Brown J. William L., Horakova Dana, Havrdova Eva K., Trojano Maria, Patti Francesco, Izquierdo Guillermo, Eichau Sara, Onofrj Marco, Lugaresi Alessandra, Prat Alexandre, Girard Marc, Grammond Pierre, Sola Patrizia, Ferraro Diana, Ozakbas Serkan, Bergamaschi Roberto, Sá Maria José, Cartechini Elisabetta, Boz Cavit, Granella Franco, Hupperts Raymond, Terzi Murat, Lechner-Scott Jeannette, Spitaleri Daniele, Van Pesch Vincent, Soysal Aysun, Olascoaga Javier, Prevost Julie, Aguera-Morales Eduardo, Slee Mark, Csepany Tunde, Turkoglu Recai, Sidhom Youssef, Gouider Riadh, Van Wijmeersch Bart, McCombe Pamela, Macdonell Richard, Coles Alasdair, Malpas Charles B., Butzkueven Helmut, Vukusic Sandra, Kalincik Tomas, MSBase and OFSEP investigators
Dátum:2020
ISSN:0006-8950
Megjegyzések:In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments (Ơtherapeutic lag') on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
multiple sclerosis
therapeutic lag
Megjelenés:Brain. - 143 : 9 (2020), p. 2742-2756. -
További szerzők:Leray, Emmanuelle Frascoli, Federico Casey, Romain Brown, J. William L. Horakova, Dana Havrdova, Eva Trojano, Maria Patti, Francesco Izquierdo, Guillermo Eichau, Sara Onofrj, Marco Lugaresi, Alessandra Prat, Alexandre Girard, Marc Grammond, Pierre Sola, Patrizia Ferraro, Diana Ozakbas, Serkan Bergamaschi, Roberto Sá, Maria José Cartechini, Elisabetta Boz, Cavit Granella, Franco Hupperts, Raymond Terzi, Murat Lechner-Scott, Jeannette Spitaleri, Daniele Pesch, Vincent van Soysal, Aysun Olascoaga, Javier Prevost, Julie Aguera-Morales, Eduardo Slee, Mark Csépány Tünde (1956-) (neurológus, pszichiáter) Turkoglu, Recai Sidhom, Youssef Gouider, Riadh Wijmeersch, Bart Van McCombe, Pamela Macdonell, Richard Coles, Alasdair Malpas, Charles B. Butzkueven, Helmut Vukusic, Sandra Kalincik, Tomas OFSEP and the MSBase investigators
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

11.

001-es BibID:BIBFORM094875
035-os BibID:(WoS)000677275500001 (Scopus)85099300704
Első szerző:Roos, Izanne
Cím:Determinants of therapeutic lag in multiple sclerosis / Izanne Roos, Emmanuelle Leray, Federico Frascoli, Romain Casey, J. William L. Brown, Dana Horakova, Eva Kubala Havrdova, Marc Debouverie, Maria Trojano, Francesco Patti, Guillermo Izquierdo, Sara Eichau, Gilles Edan, Alexandre Prat, Marc Girard, Pierre Duquette, Marco Onofrj, Alessandra Lugaresi, Pierre Grammond, Jonathan Ciron , Aurélie Ruet, Serkan Ozakbas, Jérôme De Seze, Céline Louapre, Hélène Zephir, Maria José Sá, Patrizia Sola, Diana Ferraro, Pierre Labauge, Gilles Defer, Roberto Bergamaschi, Christine Lebrun-Frenay, Cavit Boz, Elisabetta Cartechini, Thibault Moreau, David Laplaud, Jeannette Lechner-Scott, Francois Grand'Maison, Oliver Gerlach, Murat Terzi, Franco Granella, Raed Alroughani, Gerardo Iuliano, Vincent Van Pesch, Bart Van Wijmeersch, Daniele L. A. Spitaleri, Aysun Soysal, Eric Berger, Julie Prevost, Eduardo Aguera-Morales, Pamela McCombe, Tamara Castillo Triviño, Pierre Clavelou, Jean Pelletier, Recai Turkoglu, Bruno Stankoff, Olivier Gout, Eric Thouvenot, Olivier Heinzlef, Youssef Sidhom, Riadh Gouider, Tunde Csepany, Bertrand Bourre, Abdullatif Al Khedr, Olivier Casez, Philippe Cabre, Alexis Montcuquet, Abir Wahab, Jean-Philippe Camdessanche, Aude Maurousset, Ivania Patry, Karolina Hankiewicz, Corinne Pottier, Nicolas Maubeuge, Céline Labeyrie, Chantal Nifle, Alasdair Coles, Charles B. Malpas, Sandra Vukusic, Helmut Butzkueven, Tomas Kalincik, MSBase and OFSEP study groups
Dátum:2021
ISSN:1352-4585
Megjegyzések:Background: A delayed onset of treatment effect, termed therapeutic lag, may influence the assessment of treatment response in some patient subgroups. Objectives: The objective of this study is to explore the associations of patient and disease characteristics with therapeutic lag on relapses and disability accumulation. Methods: Data from MSBase, a multinational multiple sclerosis (MS) registry, and OFSEP, the French MS registry, were used. Patients diagnosed with MS, minimum 1 year of exposure to MS treatment and 3 years of pre-treatment follow-up, were included in the analysis. Studied outcomes were incidence of relapses and disability accumulation. Therapeutic lag was calculated using an objective, validated method in subgroups stratified by patient and disease characteristics. Therapeutic lag under specific circumstances was then estimated in subgroups defined by combinations of clinical and demographic determinants. Results: High baseline disability scores, annualised relapse rate (ARR) ? 1 and male sex were associated with longer therapeutic lag on disability progression in sufficiently populated groups: females with expanded disability status scale (EDSS) < 6 and ARR < 1 had mean lag of 26.6 weeks (95% CI = 18.2-34.9), males with EDSS < 6 and ARR < 1 31.0 weeks (95% CI = 25.3-36.8), females with EDSS < 6 and ARR ? 1 44.8 weeks (95% CI = 24.5-65.1), and females with EDSS ? 6 and ARR < 1 54.3 weeks (95% CI = 47.2-61.5). Conclusions: Pre-treatment EDSS and ARR are the most important determinants of therapeutic lag.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Neurology
multiple sclerosis
observational study
therapeutic lag
Megjelenés:Multiple Sclerosis. - 27 : 12 (2021), p. 1838-1851. -
További szerzők:Leray, Emmanuelle Frascoli, Federico Casey, Romain Brown, J. William L. Horakova, Dana Havrdova, Eva Debouverie, Marc Trojano, Maria Patti, Francesco Izquierdo, Guillermo Eichau, Sara Edan, Gilles Prat, Alexandre Girard, Marc Duquette, Pierre Onofrj, Marco Lugaresi, Alessandra Grammond, Pierre Ciron, Jonathan Ruet, Aurélie Ozakbas, Serkan De Seze, Jérôme Louapre, Céline Zephir, Hélène Sá, Maria José Sola, Patrizia Ferraro, Diana Labauge, Pierre Defer, Gilles Bergamaschi, Roberto Lebrun-Frenay, Christine Boz, Cavit Cartechini, Elisabetta Moreau, Thibault Laplaud, David Lechner-Scott, Jeannette Grand'Maison, Francois Gerlach, Oliver Terzi, Murat Granella, Franco Alroughani, Raed Iuliano, Gerardo Pesch, Vincent van Wijmeersch, Bart Van Spitaleri, Daniele L. A. Soysal, Aysun Berger, Eric Prevost, Julie Aguera-Morales, Eduardo McCombe, Pamela Castillo Triviño, Tamara Clavelou, Pierre Pelletier, Jean Turkoglu, Recai Stankoff, Bruno Gout, Olivier Thouvenot, Eric Heinzlef, Olivier Sidhom, Youssef Gouider, Riadh Csépány Tünde (1956-) (neurológus, pszichiáter) Bourre, Bertrand Al Khedr, Abdullatif Casez, Olivier Cabre, Philippe Montcuquet, Alexis Wahab, Abir Camdessanche, Jean-Philippe Maurousset, Aude Patry, Ivania Hankiewicz, Karolina Pottier, Corinne Maubeuge, Nicolas Labeyrie, Céline Nifle, Chantal Coles, Alasdair Malpas, Charles B. Vukusic, Sandra Butzkueven, Helmut Kalincik, Tomas MSBase and OFSEP study groups
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DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:

12.

001-es BibID:BIBFORM116385
035-os BibID:(Scopus)85176495277 (WOS)001063488100001
Első szerző:Sharmin, Sifat
Cím:The risk of secondary progressive multiple sclerosis is geographically determined but modifiable / Sharmin Sifat, Roos Izanne, Simpson-Yap Steve, Charles Malpas, Marina M. Sánchez, Serkan Ozakbas, Dana Horakova, Eva K. Havrdova, Francesco Patti, Raed Alroughani, Guillermo Izquierdo, Sara Eichau, Cavit Boz, Magd Zakaria, Marco Onofrj, Alessandra Lugaresi, Bianca Weinstock-Guttman, Alexandre Prat, Marc Girard, Pierre Duquette, Murat Terzi, Maria Pia Amato, Rana Karabudak, Francois Grand'Maison, Samia J. Khoury, Pierre Grammond, Jeannette Lechner-Scott, Katherine Buzzard, Olga Skibina, Anneke van der Walt, Helmut Butzkueven, Recai Turkoglu, Ayse Altintas, Davide Maimone, Allan Kermode, Nevin Shalaby, Vincent V. Pesch, Ernest Butler, Youssef Sidhom, Riadh Gouider, Saloua Mrabet, Oliver Gerlach, Aysun Soysal, Michael Barnett, Jens Kuhle, Stella Hughes, Maria J. Sa, Suzanne Hodgkinson, Celia Oreja-Guevara, Radek Ampapa, Thor Petersen, Cristina Ramo-Tello, Daniele Spitaleri, Pamela McCombe, Bruce Taylor, Julie Prevost, Matteo Foschi, Mark Slee, Chris McGuigan, Guy Laureys, Liesbeth V. Hijfte, Koen de Gans, Claudio Solaro, Jiwon Oh, Richard Macdonell, Eduardo Aguera-Morales, Bhim Singhal, Orla Gray, Justin Garber, Bart V. Wijmeersch, Mihaela Simu, Tamara Castillo-Triviño, Jose L. Sanchez-Menoyo, Dheeraj Khurana, Abdullah Al-Asmi, Talal Al-Harbi, Norma Deri, Yara Fragoso, Patrice H. Lalive, L. G. F. Sinnige, Cameron Shaw, Neil Shuey, Tunde Csepany, Angel P. Sempere, Fraser Moore, Danny Decoo, Barbara Willekens, Claudio Gobbi, Jennifer Massey, Todd Hardy, John Parratt, Tomas Kalincik, the MSBase investigators
Dátum:2023
ISSN:0006-8950
Megjegyzések:Geographical variations in the incidence and prevalence of multiple sclerosis have been reported globally. Latitude as a surrogate for exposure to ultraviolet radiation but also other lifestyle and environmental factors are regarded as drivers of this variation. No previous studies evaluated geographical variation in the risk of secondary progressive multiple sclerosis, an advanced form of multiple sclerosis that is characterized by steady accrual of irreversible disability.We evaluated differences in the risk of secondary progressive multiple sclerosis in relation to latitude and country of residence, modified by high-to-moderate efficacy immunotherapy in a geographically diverse cohort of patients with relapsing-remitting multiple sclerosis. The study included relapsing-remitting multiple sclerosis patients from the global MSBase registry with at least one recorded assessment of disability. Secondary progressive multiple sclerosis was identified as per clinician diagnosis. Sensitivity analyses used the operationalized definition of secondary progressive multiple sclerosis and the Swedish decision tree algorithm. A proportional hazards model was used to estimate the cumulative risk of secondary progressive multiple sclerosis by country of residence (latitude), adjusted for sex, age at disease onset, time from onset to relapsing-remitting phase, disability (Multiple Sclerosis Severity Score) and relapse activity at study inclusion, national multiple sclerosis prevalence, government health expenditure, and proportion of time treated with high-to-moderate efficacy disease-modifying therapy. Geographical variation in time from relapsing-remitting phase to secondary progressive phase of multiple sclerosis was modelled through a proportional hazards model with spatially correlated frailties.We included 51 126 patients (72% female) from 27 countries. The median survival time from relapsing-remitting phase to secondary progressive multiple sclerosis among all patients was 39 (95% confidence interval: 37 to 43) years. Higher latitude [median hazard ratio = 1.21, 95% credible interval (1.16, 1.26)], higher national multiple sclerosis prevalence [1.07 (1.03, 1.11)], male sex [1.30 (1.22, 1.39)], older age at onset [1.35 (1.30, 1.39)], higher disability [2.40 (2.34, 2.47)] and frequent relapses [1.18 (1.15, 1.21)] at inclusion were associated with increased hazard of secondary progressive multiple sclerosis. Higher proportion of time on high-to-moderate efficacy therapy substantially reduced the hazard of secondary progressive multiple sclerosis [0.76 (0.73, 0.79)] and reduced the effect of latitude [interaction: 0.95 (0.92, 0.99)]. At the country-level, patients in Oman, Tunisia, Iran and Canada had higher risks of secondary progressive multiple sclerosis relative to the other studied regions.Higher latitude of residence is associated with a higher probability of developing secondary progressive multiple sclerosis. High-to-moderate efficacy immunotherapy can mitigate some of this geographically co-determined risk. By analysing longitudinal data from 27 countries, Sharmin et al. reveal a geographically varying risk of conversion to secondary progressive disease in patients with multiple sclerosis. Higher latitude of residence increases the risk while high-to-moderate efficacy immunotherapies reduce the risk substantially.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
disease-modifying therapy
geography
health expenditure
latitude
secondary progressive multiple sclerosis
Megjelenés:Brain. - 146 : 11 (2023), p. 4633-4644. -
További szerzők:Roos, Izanne Simpson-Yap, Steve Malpas, Charles Sánchez, Marina M. Ozakbas, Serkan Horakova, Dana Havrdova, Eva Patti, Francesco Alroughani, Raed Izquierdo, Guillermo Eichau, Sara Boz, Cavit Zakaria, Magd Onofrj, Marco Lugaresi, Alessandra Weinstock-Guttman, Bianca Prat, Alexandre Girard, Marc Duquette, Pierre Terzi, Murat Amato, Maria Pia Karabudak, Rana Grand'Maison, Francois Khoury, Samia J. Grammond, Pierre Lechner-Scott, Jeannette Buzzard, Katherine Skibina, Olga Walt, Anneke van der Butzkueven, Helmut Turkoglu, Recai Altintas, Ayse Maimone, Davide Kermode, Allan G. Shalaby, Nevin Pesch, Vincent van Butler, Ernest Sidhom, Youssef Gouider, Riadh Mrabet, Saloua Gerlach, Oliver Soysal, Aysun Barnett, Michael Kuhle, Jens Hughes, Stella Sá, Maria José Hodgkinson, Suzanne Oreja-Guevara, Celia Ampapa, Radek Petersen, Thor Ramo-Tello, Cristina Spitaleri, Daniele McCombe, Pamela Taylor, Bruce V. Prevost, Julie Foschi, Matteo Slee, Mark McGuigan, Christopher Laureys, Guy Hijfte, Liesbeth V. de Gans, Koen Solaro, Claudio Oh, Jiwon Macdonell, Richard Aguera-Morales, Eduardo Singhal, Bhim Gray, Orla Garber, Justin Wijmeersch, Bart Van Mihaela, Simu Castillo Triviño, Tamara Sanchez-Menoyo, Jose Khurana, Dheeraj Al-Asmi, Abdullah Al-Harbi, Talal Deri, Norma Fragoso, Yara Lalive, Patrice H. Sinnige, L. G. F. Shaw, Cameron Shuey, Neil Csépány Tünde (1956-) (neurológus, pszichiáter) Sempere, Perez A. Moore, Fraser Decoo, Danny Willekens, Barbara Gobbi, Claudio Massey, Jennifer Hardy, Todd A. Parratt, John Kalincik, Tomas the MSBase investigators
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