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1.

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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2.

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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3.

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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4.

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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5.

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
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6.

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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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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