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001-es BibID:BIBFORM103014
035-os BibID:(Scopus)85107568058 (Wos)000687405300017
Első szerző:Andersen, Johanna Balslev
Cím:The effectiveness of natalizumab vs fingolimod : a comparison of international registry studies / Andersen Johanna B., Sharmin Sifat, Lefort Mathilde, Koch-Henriksen Nils, Sellebjerg Finn, Srensen Per Soelberg, Hilt Christensen Claudia C., Rasmussen Peter V., Jensen Michael B., Frederiksen Jette L., Bramow Stephan, Mathiesen Henrik K., Schreiber Karen I., Horakova Dana, Havrdova Eva K., Alroughani Raed, Izquierdo Guillermo, Eichau Sara, Ozakbas Serkan, Patti Francesco, Onofrj Marco, Lugaresi Alessandra, Terzi Murat, Grammond Pierre, Grand Maison Francois, Yamout Bassem, Prat Alexandre, Girard Marc, Duquette Pierre, Boz Cavit, Trojano Maria, McCombe Pamela, Slee Mark, Lechner-Scott Jeannette, Turkoglu Recai, Sola Patrizia, Ferraro Diana, Granella Franco, Shaygannejad Vahid, Prevost Julie, Skibina Olga, Solaro Claudio, Karabudak Rana, Wijmeersch Bart V., Csepany Tunde, Spitaleri Daniele, Vucic Steve, Casey Romain, Debouverie Marc, Edan Gilles, Ciron Jonathan, Ruet Aurélie, Seze, Jérome D., Maillart Elisabeth, Zephir Hélene, Labauge Pierre Defer Gilles, Lebrun Christine, Moreau Thibault, Berger Eric, Clavelou Pierre, Pelletier Jean, Stankoff Bruno, Gout Olivier, Thouvenot Eric, Heinzlef Olivier, Al-Khedr Abdullatif, Bourre Bertrand, Casez Olivier, Cabre Philippe, Montcuquet Alexis, Wahab Abir, Camdessanché Jean-Philippe, Marousset Aude, Patry Ivania, Hankiewicz Karolina, Pottier Corinne, Maubeuge Nicolas, Labeyrie Céline, Nifle Chantal, Leray Emmanuelle, Laplaud David A., Butzkueven Helmut, Kalincik Tomas, Vukusic Sandra, Magyari Melinda
Dátum:2021
ISSN:2211-0348
Megjegyzések:Background Natalizumab and fingolimod were the first preparations recommended for disease breakthrough in priorly treated relapsing-remitting multiple sclerosis. Of three published head-to-head studies two showed that natalizumab is the more effective to prevent relapses and EDSS worsening. Methods By re-analyzing original published results from MSBase, France, and Denmark using uniform methodologies, we aimed at identifying the effects of differences in methodology, in the MS-populations, and at re-evaluating the differences in effectiveness between the two drugs. We gained access to copies of the individual amended databases and pooled all data. We used uniform inclusion/exclusion criteria and statistical methods with Inverse Probability Treatment Weighting. Results The pooled analyses comprised 968 natalizumab- and 1479 fingolimod treated patients. The on-treatment natalizumab/fingolimod relapse rate ratio was 0.77 (p=0.004). The hazard ratio (HR) for a first relapse was 0.82 (p=0.030), and the HR for sustained EDSS improvement was 1.4 (p=0.009). There were modest differences between each of the original published studies and the replication study, but the conclusions of the three original studies remained unchanged: in two of them natalizumab was more effective, but in the third there was no difference between natalizumab and fingolimod. Conclusion The results were largely invariant to the epidemiological and statistical methods but differed between the MS populations. Generally, the advantage of natalizumab was confirmed.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Multiple Sclerosis and Related Disorders. - 53 (2021), p. 1-15. -
További szerzők:Sharmin, Sifat Lefort, Mathilde Koch-Henriksen, Niels Sellebjerg, Finn Thorup Srensen, Per Hilt Christensen, Claudia C. Rasmussen, Peter Vestergaard Jensen, Michael Broksgaard Frederiksen, Jette Lautrup Bramow, Stephan Mathiesen, Henrik Kahr Schreiber, Karen Horakova, Dana Havrdova, Eva Alroughani, Raed Izquierdo, Guillermo Eichau, Sara Ozakbas, Serkan Patti, Francesco Onofrj, Marco Lugaresi, Alessandra Terzi, Murat Grammond, Pierre Grand Maison, Francois Yamout, Bassem Prat, Alexandre Girard, Marc Duquette, Pierre Boz, Cavit Trojano, Maria McCombe, Pamela Slee, Mark Lechner-Scott, Jeannette Turkoglu, Recai Sola, Patrizia Ferraro, Diana Granella, Franco Shaygannejad, Vahid Prevost, Julie Skibina, Olga Solaro, Claudio Karabudak, Rana Wijmeersch, Bart Van Csépány Tünde (1956-) (neurológus, pszichiáter) Spitaleri, Daniele Vucic, Steve Casey, Romain Debouverie, Marc Edan, Gilles Ciron, Jonathan Ruet, Aurélie Seze, Jérome D. Maillart, Elisabeth Zephir, Hélène Labauge, Pierre Defer, Gilles Lebrun-Frenay, Christine Moreau, Thibault Berger, Eric Clavelou, Pierre Pelletier, Jean Stankoff, Bruno Gout, Olivier Thouvenot, Eric Heinzlef, Olivier Al-Khedr, Abdullatif Bourre, Bertrand Casez, Olivier Cabre, Philippe Montcuquet, Alexis Wahab, Abir Camdessanche, Jean-Philippe Marousset, Aude Patry, Ivania Hankiewicz, Karolina Pottier, Corinne Maubeuge, Nicolas Labeyrie, Céline Nifle, Chantal Leray, Emmanuelle Laplaud, David Butzkueven, Helmut Kalincik, Tomas Vukusic, Sandra Magyari Melinda
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2.

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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3.

001-es BibID:BIBFORM085749
Első szerző:Brown, Jeremy William L.
Cím:The risk of relapse following on-treatment clinically silent lesions in patients with relapsing-remitting multiple sclerosis / Brown, J. W. L., Lugaresi A., Horakova D., Havrdova E., Jokubaitis V., Lechner-Scott J., Trojano M., Min M., Shaw C., Shuey N., Slee M., Mccombe P., Van Pesch V., Van Wijmeersch B., Prevost J., Moore F., Prat A., Girard M., Duquette P., Ayrignac X., Sempere A. Perez, Sanchez-Menoyo J. L., Ramo-Tello C., Csépány Tünde, Hutchinson M., De Luca G., Bergamaschi R., Granella F., Curti E., Tsantes E., Sola P., Ferraro D., Alroughani R., Hupperts R., Al-Harbi T., Sidhom Y., Boz C., Terzi M., Ozakbas S., Soysal A., Pucci E., Izquierdo G., Iuliano G., Rio M. Edite, Spitaleri D., Grammond P., Grand'Maison F., Butzkueven H., Kalincik T.
Dátum:2017
ISSN:1352-4585
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
folyóiratcikk
Megjelenés:Multiple Sclerosis. - 23 : Suppl. 3 (2017), p. 992-994. -
További szerzők:Lugaresi, Alessandra Horakova, Dana Havrdova, Eva Jokubaitis, Vilija Lechner-Scott, Jeannette Trojano, Maria Min, M. Shaw, C. A. Shuey, Neil Slee, Mark McCombe, Pamela Pesch, Vincent van Wijmeersch, Bart Van Prevost, Julie Moore, Fraser Prat, Alexandre Girard, Marc Duquette, Pierre Ayrignac, X. Sempere, Perez A. Sanchez-Menoyo, Jose Ramo-Tello, Cristina Csépány Tünde (1956-) (neurológus, pszichiáter) Hutchinson, Michael De Luca, Giacomo Bergamaschi, Roberto Granella, Franco Curti, E. Tsantes, E. Sola, Patrizia Ferraro, D. Alroughani, Raed Hupperts, Raymond Al-Harbi, Talal Sidhom, Youssef Boz, Cavit Terzi, Murat Ozakbas, Serkan Soysal, Aysun Pucci, Eugenio Izquierdo, Guillermo Iuliano, Gerardo Rio, Edite M. Spitaleri, Daniele Grammond, Pierre Grand'Maison, Francois Butzkueven, Helmut Kalincik, Tomas
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4.

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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5.

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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6.

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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7.

001-es BibID:BIBFORM132945
035-os BibID:(scopus)85217750289 (wos)001434985500001
Első szerző:D'hondt, Robbe
Cím:Explainable time-to-progression predictions in multiple sclerosis / D'hondt Robbe, Dedja Klest, Aerts Sofie, Van Wijmeersch Bart, Kalincik Tomas, Reddel Stephen, Havrdova Eva Kubala, Lugaresi Alessandra, Weinstock-Guttman Bianca, Mrabet Saloua, Lalive Patrice, Kermode Allan G., Ozakbas Serkan, Patti Francesco, Prat Alexandre, Tomassini Valentina, Roos Izanne, Alroughani Raed, Gerlach Oliver, Khoury Samia J., van Pesch Vincent, Sá Maria José, Prevost Julie, Spitaleri Daniele, McCombe Pamela, Solaro Claudio, van der Walt Anneke, Butzkueven Helmut, Laureys Guy, Sánchez-Menoyo José Luis, de Gans Koen, Al-Asmi Abdullah, Deri Norma, Csepany Tunde, Al-Harbi Talal, Carroll William M., Rozsa Csilla, Singhal Bhim, Hardy Todd A., Ramanathan Sudarshini, Peeters Liesbet, Vens Celine, MSBase Study Group
Dátum:2025
ISSN:0169-2607
Megjegyzések:Background: Prognostic machine learning research in multiple sclerosis has been mainly focusing on black-box models predicting whether a patients' disability will progress in a fixed number of years. However, as this is a binary yes/no question, it cannot take individual disease severity into account. Therefore, in this work we propose to model the time to disease progression instead. Additionally, we use explainable machine learning techniques to make the model outputs more interpretable. Methods: A preprocessed subset of 29,201 patients of the international data registry MSBase was used. Disability was assessed in terms of the Expanded Disability Status Scale (EDSS). We predict the time to significant and confirmed disability progression using random survival forests, a machine learning model for survival analysis. Performance is evaluated on a time-dependent area under the receiver operating characteristic and the precision-recall curves. Importantly, predictions are then explained using SHAP and Bellatrex, two explainability toolboxes, and lead to both global (population-wide) as well as local (patient visit-specific) insights. Results: On the task of predicting progression in 2 years, the random survival forest achieves state-of-the-art performance, comparable to previous work employing a random forest. However, here the random survival forest has the added advantage of being able to predict progression over a longer time horizon, with AUROC >60% for the first 10 years after baseline. Explainability techniques further validated the model by extracting clinically valid insights from the predictions made by the model. For example, a clear decline in the per-visit probability of progression is observed in more recent years since 2012, likely reflecting globally increasing use of more effective MS therapies. Conclusion: The binary classification models found in the literature can be extended to a time-to-event setting without loss of performance, thus allowing a more comprehensive prediction of patient prognosis. Furthermore, explainability techniques proved to be key to reach a better understanding of the model and increase validation of its behaviour.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Disability progression
Explainable artificial intelligence
Longitudinal data
Multiple sclerosis
Survival analysis
Megjelenés:Computer Methods And Programs In Biomedicine. - 263 (2025), p. 1-23. -
További szerzők:Dedja, Klest Aerts, Sofie Wijmeersch, Bart Van Kalincik, Tomas Reddel, Stephen Havrdova, Eva Lugaresi, Alessandra Weinstock-Guttman, Bianca Mrabet, Saloua Lalive, Patrice H. Kermode, Allan G. Ozakbas, Serkan Patti, Francesco Prat, Alexandre Tomassini, Valentina Roos, Izanne Alroughani, Raed Gerlach, Oliver Khoury, Samia J. Pesch, Vincent van Sá, Maria José Prevost, Julie Spitaleri, Daniele McCombe, Pamela Solaro, Claudio Walt, Anneke van der Butzkueven, Helmut Laureys, Guy (Universitary Hospital Ghent) Sanchez-Menoyo, Jose de Gans, Koen Al-Asmi, Abdullah Deri, Norma Csépány Tünde (1956-) (neurológus, pszichiáter) Al-Harbi, Talal Carroll, William M. Rózsa Csilla Singhal, Bhim Hardy, Todd A. Ramanathan, Sudarshini Peeters, Liesbet Vens, Celine MSBase Study Group
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

8.

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:

9.

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:

10.

001-es BibID:BIBFORM083269
Első szerző:Fambiatos, Adam
Cím:Risk of secondary progressive multiple sclerosis : a longitudinal study / Adam Fambiatos, Vilija Jokubaitis, Dana Horakova, Eva Kubala Havrdova, Maria Trojano, Alexandre Prat, Marc Girard, Pierre Duquette, Alessandra Lugaresi, Guillermo Izquierdo, Francois Grand'Maison, Pierre Grammond, Patrizia Sola, Diana Ferraro, Raed Alroughani, Murat Terzi, Raymond Hupperts, Cavit Boz, Jeannette Lechner-Scott, Eugenio Pucci, Roberto Bergamaschi, Vincent Van Pesch, Serkan Ozakbas, Franco Granella, Recai Turkoglu, Gerardo Iuliano, Daniele Spitaleri, Pamela McCombe, Claudio Solaro, Mark Slee, Radek Ampapa, Aysun Soysal, Thor Petersen, Jose Luis Sanchez-Menoyo, Freek Verheul, Julie Prevost, Youssef Sidhom, Bart Van Wijmeersch, Steve Vucic, Edgardo Cristiano, Maria Laura Saladino, Norma Deri, Michael Barnett, Javier Olascoaga, Fraser Moore, Olga Skibina, Orla Gray, Yara Fragoso, Bassem Yamout, Cameron Shaw, Bhim Singhal, Neil Shuey, Suzanne Hodgkinson, Ayse Altintas, Talal Al-Harbi, Tunde Csepany, Bruce Taylor, Jordana Hughes, Jae-Kwan Jun, Anneke van der Walt, Tim Spelman, Helmut Butzkueven, Tomas Kalincik, MSBase Study Group
Dátum:2020
ISSN:1352-4585
Megjegyzések:Background: The risk factors for conversion from relapsing-remitting to secondary progressive multiple sclerosis remain highly contested. Objective: The aim of this study was to determine the demographic, clinical and paraclinical features that influence the risk of conversion to secondary progressive multiple sclerosis. Methods: Patients with adult-onset relapsing?remitting multiple sclerosis and at least four recorded disability scores were selected from MSBase, a global observational cohort. The risk of conversion to objectively defined secondary progressive multiple sclerosis was evaluated at multiple time points per patient using multivariable marginal Cox regression models. Sensitivity analyses were performed. Results: A total of 15,717 patients were included in the primary analysis. Older age (hazard ratio (HR) = 1.02, p < 0.001), longer disease duration (HR = 1.01, p = 0.038), a higher Expanded Disability Status Scale score (HR = 1.30, p < 0.001), more rapid disability trajectory (HR = 2.82, p < 0.001) and greater number of relapses in the previous year (HR = 1.07, p = 0.010) were independently associated with an increased risk of secondary progressive multiple sclerosis. Improving disability (HR = 0.62, p = 0.039) and disease-modifying therapy exposure (HR = 0.71, p = 0.007) were associated with a lower risk. Recent cerebral magnetic resonance imaging activity, evidence of spinal cord lesions and oligoclonal bands in the cerebrospinal fluid were not associated with the risk of conversion. Conclusion: Risk of secondary progressive multiple sclerosis increases with age, duration of illness and worsening disability and decreases with improving disability. Therapy may delay the onset of secondary progression.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Multiple Sclerosis. - 26 : 1 (2020), p. 79-90. -
További szerzők:Jokubaitis, Vilija Horakova, Dana Kubala Havrdova, Eva Trojano, Maria Prat, Alexandre Girard, Marc Duquette, Pierre Lugaresi, Alessandra Izquierdo, Guillermo Grand'Maison, Francois Grammond, Pierre Sola, Patrizia Ferraro, Diana Alroughani, Raed Terzi, Murat Hupperts, Raymond Boz, Cavit Lechner-Scott, Jeannette Pucci, Eugenio Bergamaschi, Roberto Pesch, Vincent van Ozakbas, Serkan Granella, Franco Turkoglu, Recai Iuliano, Gerardo Spitaleri, Daniele McCombe, Pamela Solaro, Claudio Slee, Mark Ampapa, Radek Soysal, Aysun Petersen, Thor Sanchez-Menoyo, Jose Verheul, Freek Prevost, Julie Sidhom, Youssef Wijmeersch, Bart Van Vucic, Steve Cristiano, Edgardo Saladino, Maria Laura Deri, Norma Barnett, Michael Olascoaga, Javier Moore, Fraser Skibina, Olga Gray, Orla Fragoso, Yara Yamout, Bassem Shaw, Cameron Singhal, Bhim Shuey, Neil Hodgkinson, Suzanne Altintas, Ayse Al-Harbi, Talal Csépány Tünde (1956-) (neurológus, pszichiáter) Taylor, Bruce V. Hughes, Jordana Jun, Jae-Kwan Walt, Anneke van der Spelman, Tim Butzkueven, Helmut Kalincik, Tomas MSBase Study Group
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

11.

001-es BibID:BIBFORM126269
035-os BibID:(scopus)85164541334 (wos)000999038400003
Első szerző:Kalincik, Tomas
Cím:Comparative Effectiveness of Autologous Hematopoietic Stem Cell Transplant vs Fingolimod, Natalizumab, and Ocrelizumab in Highly Active Relapsing-Remitting Multiple Sclerosis / Tomas Kalincik, Sifat Sharmin, Izanne Roos, Mark S. Freedman, Harold Atkins, Joachim Burman, Jennifer Massey, Ian Sutton, Barbara Withers, Richard Macdonell, Andrew Grigg, øivind Torkildsen, Lars Bo, Anne Kristine Lehmann, Eva Kubala Havrdova, Eva Krasulova, Marek Trneny, Tomas Kozak, Anneke van der Walt, Helmut Butzkueven, Pamela McCombe, Olga Skibina, Jeannette Lechner-Scott, Barbara Willekens, Elisabetta Cartechini, Serkan Ozakbas, Raed Alroughani, Jens Kuhle, Francesco Patti, Pierre Duquette, Alessandra Lugaresi, Samia J. Khoury, Mark Slee, Recai Turkoglu, Suzanne Hodgkinson, Nevin John, Davide Maimone, Maria Jose Sa, Vincent van Pesch, Oliver Gerlach, Guy Laureys, Liesbeth Van Hijfte, Rana Karabudak, Daniele Spitaleri, Tunde Csepany, Riadh Gouider, Tamara Castillo-Trivino, Bruce Taylor, Basil Sharrack, John A. Snowden, MSBase Study Group Collaborators
Dátum:2023
ISSN:2168-6149 2168-6157
Megjegyzések:IMPORTANCE Autologous hematopoietic stem cell transplant (AHSCT) is available for treatment of highly active multiple sclerosis (MS). OBJECTIVE To compare the effectiveness of AHSCT vs fingolimod, natalizumab, and ocrelizumab in relapsing-remitting MS by emulating pairwise trials. DESIGN, SETTING, AND PARTICIPANTS This comparative treatment effectiveness study included 6 specialist MS centers with AHSCT programs and international MSBase registry between 2006 and 2021. The study included patients with relapsing-remitting MS treated with AHSCT, fingolimod, natalizumab, or ocrelizumab with 2 or more years study follow-up including 2 or more disability assessments. Patients were matched on a propensity score derived from clinical and demographic characteristics. EXPOSURE AHSCT vs fingolimod, natalizumab, or ocrelizumab. MAIN OUTCOMES Pairwise-censored groups were compared on annualized relapse rates (ARR) and freedom from relapses and 6-month confirmed Expanded Disability Status Scale (EDSS) score worsening and improvement. RESULTS Of 4915 individuals, 167 were treated with AHSCT; 2558, fingolimod; 1490, natalizumab; and 700, ocrelizumab. The prematch AHSCT cohort was younger and with greater disability than the fingolimod, natalizumab, and ocrelizumab cohorts; thematched groups were closely aligned. The proportion ofwomen ranged from65% to70%,and themean (SD)age ranged from 35.3 (9.4) to 37.1 (10.6) years. The mean (SD) disease duration ranged from 7.9 (5.6) to 8.7 (5.4) years, EDSS score ranged from 3.5 (1.6) to 3.9 (1.9), and frequency of relapses ranged from0.77 (0.94) to0.86 (0.89) in the preceding year. Compared with the fingolimod group (769 [30.0%]), AHSCT (144 [86.2%]) was associated with fewer relapses (ARR: mean [SD], 0.09 [0.30] vs 0.20 [0.44]), similar risk of disability worsening (hazard ratio [HR], 1.70; 95% CI, 0.91-3.17), and higher chance of disability improvement (HR, 2.70; 95% CI, 1.71-4.26) over 5 years. Compared with natalizumab (730 [49.0%]), AHSCT (146 [87.4%]) was associated withmarginally lower ARR (mean [SD],0.08 [0.31]vs0.10 [0.34]), similar risk of disabilityworsening (HR, 1.06; 95% CI,0.54-2.09), and higher chance of disability improvement (HR, 2.68; 95% CI, 1.72-4.18) over 5 years. AHSCT (110 [65.9%]) and ocrelizumab (343 [49.0%])were associatedwith similarARR (mean [SD],0.09 [0.34]vs0.06 [0.32]), disability worsening (HR, 1.77; 95% CI, 0.61-5.08), and disability improvement (HR, 1.37; 95% CI, 0.66-2.82) over 3 years. AHSCT-related mortality occurred in 1 of 159 patients (0.6%). CONCLUSION In this study, the association of AHSCT with preventing relapses and facilitating recovery from disability was considerably superior to fingolimod and marginally superior to natalizumab. This study did not find evidence for difference in the effectiveness of AHSCT and ocrelizumab over a shorter available follow-up time.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
AHSCT
Fingolimod
Natalizumab
Ocrelizumab
multiple sclerosis
Megjelenés:JAMA Neurology. - 80 : 7 (2023), p. 702-713. -
További szerzők:Sharmin, Sifat Roos, Izanne Freedman, Mark S. Atkins, Harold Burman, Joachim Massey, Jennifer Sutton, Ian Withers, Barbara Macdonell, Richard Grigg, Andrew Torkildsen, øivind Bo, Lars Lehmann, Anne Kristine Kubala Havrdova, Eva Krasulova, Eva Trneny, Marek Kozak, Tomas Walt, Anneke van der Butzkueven, Helmut McCombe, Pamela Skibina, Olga Lechner-Scott, Jeannette Willekens, Barbara Cartechini, Elisabetta Ozakbas, Serkan Alroughani, Raed Kuhle, Jens Patti, Francesco Duquette, Pierre Lugaresi, Alessandra Khoury, Samia J. Slee, Mark Turkoglu, Recai Hodgkinson, Suzanne John, Nevin Maimone, Davide José Sá, Maria Pesch, Vincent van Gerlach, Oliver Laureys, Guy Van Hijfte, Liesbeth Karabudak, Rana Spitaleri, Daniele Csépány Tünde (1956-) (neurológus, pszichiáter) Gouider, Riadh Castillo Triviño, Tamara Taylor, Bruce V. Sharrack, Basil Snowden, John A. MSBase Study Group
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Intézményi repozitóriumban (DEA) tárolt változat
Borító:

12.

001-es BibID:BIBFORM103011
035-os BibID:(Scopus)85102090793 (Wos)000656637200025
Első szerző:Kalincik, Tomas
Cím:Effect of Disease-Modifying Therapy on Disability in Relapsing-Remitting Multiple Sclerosis Over 15 Years / Kalincik Tomas, Diouf Ibrahima, Sharmin Sifat, Malpas Charles, Spelman Tim, Horakova Dana, Havrdova Eva Kubala, Trojano Maria, Izquierdo Guillermo, Lugaresi Alessandra, Prat Alexandre, Girard Marc, Duquette Pierre, Grammond Pierre, Jokubaitis Vilija, van der Walt Anneke, Grand'Maison Francois, Sola Patrizia, Ferraro Diana, Shaygannejad Vahid, Alroughani Raed, Hupperts Raymond, Terzi Murat, Boz Cavit, Lechner-Scott Jeannette, Pucci Eugenio, Van Pesch Vincent, Granella Franco, Bergamaschi Roberto, Spitaleri Daniele, Slee Mark, Vucic Steve, Ampapa Radek, McCombe Pamela, Ramo-Tello Cristina, Prevost Julie, Olascoaga Javier, Cristiano Edgardo, Barnett Michael, Saladino Maria Laura, Sanchez-Menoyo Jose Luis, Hodgkinson Suzanne, Rozsa Csilla, Hughes Stella, Moore Fraser, Shaw Cameron, Butler Ernest, Skibina Olga, Gray Orla, Kermode Allan, Csepany Tunde, Singhal Bhim, Shuey Neil, Piroska Imre, Taylor Bruce, Simo Magdolna, Sirbu Carmen-Adella, Sas Attila, Butzkueven Helmut, MSBase Study Group
Dátum:2021
ISSN:0028-3878 1526-632X
Megjegyzések:Objective To test the hypothesis that immunotherapy prevents long-term disability in relapsing-remitting multiple sclerosis (MS), we modeled disability outcomes in 14,717 patients. Methods We studied patients from MSBase followed for ?1 year, with ?3 visits, ?1 visit per year, and exposed to MS therapy, and a subset of patients with ?15-year follow-up. Marginal structural models were used to compare the cumulative hazards of 12-month confirmed increase and decrease in disability, Expanded Disability Status Scale (EDSS) step 6, and the incidence of relapses between treated and untreated periods. Marginal structural models were continuously readjusted for patient age, sex, pregnancy, date, disease course, time from first symptom, prior relapse history, disability, and MRI activity. Results A total of 14,717 patients were studied. During the treated periods, patients were less likely to experience relapses (hazard ratio 0.60, 95% confidence interval [CI] 0.43?0.82, p = 0.0016), worsening of disability (0.56, 0.38?0.82, p = 0.0026), and progress to EDSS step 6 (0.33, 0.19?0.59, p = 0.00019). Among 1,085 patients with ?15-year follow-up, the treated patients were less likely to experience relapses (0.59, 0.50?0.70, p = 10?9) and worsening of disability (0.81, 0.67?0.99, p = 0.043). Conclusion Continued treatment with MS immunotherapies reduces disability accrual by 19%?44% (95% CI 1%?62%), the risk of need of a walking aid by 67% (95% CI 41%?81%), and the frequency of relapses by 40?41% (95% CI 18%?57%) over 15 years. This study provides evidence that disease-modifying therapies are effective in improving disability outcomes in relapsing-remitting MS over the long term. Classification of Evidence This study provides Class IV evidence that, for patients with relapsing-remitting MS, long-term exposure to immunotherapy prevents neurologic disability.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Neurology. - 96 : 5 (2021), p. e783-e797. -
További szerzők:Diouf, Ibrahima Sharmin, Sifat Malpas, Charles Spelman, Tim Horakova, Dana Havrdova, Eva Trojano, Maria Izquierdo, Guillermo Lugaresi, Alessandra Prat, Alexandre Girard, Marc Duquette, Pierre Grammond, Pierre Jokubaitis, Vilija Walt, Anneke van der Grand'Maison, Francois Sola, Patrizia Ferraro, Diana Shaygannejad, Vahid Alroughani, Raed Hupperts, Raymond Terzi, Murat Boz, Cavit Lechner-Scott, Jeannette Pucci, Eugenio Pesch, Vincent van Granella, Franco Bergamaschi, Roberto Spitaleri, Daniele Slee, Mark Vucic, Steve Ampapa, Radek McCombe, Pamela Ramo-Tello, Cristina Prevost, Julie Olascoaga, Javier Cristiano, Edgardo Barnett, Michael Saladino, Maria Laura Sanchez-Menoyo, Jose Hodgkinson, Suzanne Rózsa Csilla Hughes, Stella Moore, Fraser Shaw, Cameron Butler, Ernest Skibina, Olga Gray, Orla Kermode, Allan G. Csépány Tünde (1956-) (neurológus, pszichiáter) Singhal, Bhim Shuey, Neil Piroska Imre Taylor, Bruce V. Simó Magdolna Sirbu, Carmen-Adella Sas Attila Butzkueven, Helmut MSBase Study Group
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