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001-es BibID:	BIBFORM103017
035-os BibID:	(Wos)000685503300008 (Scopus)85107912293 (cikkazonosító)106180
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 Van Wijmeersch, Bart 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
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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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 Van Wijmeersch, Bart Simu, Mihaela 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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