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1. Patient perceptions of multiple sclerosis and its treatment

Author

de Seze J, Borgel F, Brudon F

Subjects
Medicine (General), R5-920
Abstract

Jérôme de Seze1, Florent Borgel2, Frédérique Brudon31Department of Neurology CHRU de Strasbourg, Strasbourg, 2Medical Center, Grenoble, 3Clinique du Tonkin, Villeurbanne, FranceBackground: In order to improve the treatment outcome in multiple sclerosis, it is important to document the factors that influence adherence to therapy. The purpose of this study was to determine patient perceptions and awareness of multiple sclerosis and its treatment, treatment adherence, and impact on quality of life and daily living.Methods: This was a cross-sectional observational study performed in France. Each participating neurologist included the first three patients with relapsing-remitting multiple sclerosis who consulted after the start of the study. Data on clinical features were collected from a physician questionnaire and on disease and treatment perception and on quality of life from a patient autoquestionnaire.Results: A total of 175 neurologists entered 202 patients in the study. The mean duration of disease was 8.0 ± 7.0 years, and immunomodulatory treatment had been administered for a mean duration of 3.0 ± 2.0 years. A total of 166 patients (82.2%) were treated with interferon-ß preparations and 36 patients (17.8%) with glatiramer acetate. Eighty-five patients (42.1%) reported missing their injections from time to time and 36 patients (17.8%) reported “drug holidays”. The most frequently given reason for nonadherence was forgetfulness (38.7% of cases). Eighty-six patients (42.6%) and 70 patients (34.7%) claimed to be well informed about their disease and treatment, respectively. Adherence was significantly higher in well informed patients (P = 0.035). The majority of patients (176 patients, 87.1%) intended continuing their current treatment and 49.5% considered that their current treatment might reduce relapses. The most frequently reported side effect was muscle pain (124 patients, 61.4%).Conclusion: Patient understanding of treatment for disease enhances treatment adherence. Greater patient involvement in disease management requires better communication between physicians and their patients.Keywords: multiple sclerosis, patient adherence, quality of life

Published
2012

7. Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI

Author

Brochet, B., Casey, R., Cotton, F., De Sèze, J., Douek, P., Guillemin, F., Laplaud, D., Lebrun-Frenay, C., Mansuy, L., Moreau, T., Olaiz, J., Pelletier, J., Rigaud-Bully, C., Stankoff, B., Vukusic, S., Marignier, R., Debouverie, M., Edan, G., Ciron, J., Ruet, A., Collongues, N., Lubetzki, C., Vermersch, P., Labauge, P., Defer, G., Cohen, M., Fromont, A., Wiertlewsky, S., Berger, E., Clavelou, P., Audoin, B., Giannesini, C., Gout, O., Thouvenot, E., Heinzlef, O., Al-Khedr, A., Bourre, B., Casez, O., Cabre, P., Montcuquet, A., Créange, A., Camdessanché, J.-P., Faure, J., Maurousset, A., Patry, I., Hankiewicz, K., Pottier, C., Maubeuge, N., Labeyrie, C., Nifle, C., Ameli, R., Anxionnat, R., Attye, A., Bannier, E., Barillot, C., Ben Salem, D., Boncoeur-Martel, M.-P., Bonneville, F., Boutet, C., Brisset, J.-C., Cervenanski, F., Claise, B., Commowick, O., Constans, J.-M., Dardel, P., Desal, H., Dousset, Vincent, Durand-Dubief, F., Ferre, J.-C., Gerardin, E., Glattard, T., Grand, S., Grenier, T., Guillevin, R., Guttmann, C., Krainik, A., Kremer, S., Lion, S., Menjot de Champfleur, N., Mondot, L., Outteryck, O., Pyatigorskaya, N., Pruvo, J.-P., Rabaste, S., Ranjeva, J.-P., Roch, J.-A., Sadik, J.C., Sappey-Marinier, D., Savatovsky, J., Tanguy, J.-Y., Tourbah, A., Tourdias, T., Roca, P., Colas, L., Tucholka, A., Rubini, P., Cackowski, S., Ding, J., Budzik, J.-F., Renard, F., Doyle, S., Barbier, E.L., Bousaid, I., Lassau, N., and Verclytte, S.

Published
2020
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8. Urinary tract infections and multiple sclerosis: Recommendations from the French Multiple Sclerosis Society

Author

Donzé, C., Papeix, C., Lebrun-Frénay, C., Collongues, N., de Seze, M., Dinh, A., Even, A., Scheiber-Nogueira, C., Bensa, C., Bourre, B., Carra-Dallière, C., Ciron, J., Cohen, M., Guennoc, A.M., Louapre, C., Lebreton, F., Michel, L., Maillart, E., Audoin, B., Ayrignac, X., Bernady, P., Brochet, B., Clavelou, P., Colamarino, R., Declemy, A., de Seze, J., Derache, N., Faucheux, J.-M., Heinzlef, O., Labauge, P., Laplaud, D., Lepage, E., Leray, E., Magy, L., Mathey, G., Mekies, C., Mondain, V., Planque, E., Pelletier, J., Pittion, S., Stankhof, B., Tournaire, P., Thouvenot, E., Vukusic, S., Wiertlevski, S., Zephir, H., Alchaar, H., Androdias, G., Benazet, M., Bensmail, D., Biotti, D., Blanchard-Dauphin, A., Bonnan, M., Boutière, C., Branger, P., Bresch, S., Bru, J.-P., Camdessanché, J.-P., Castel Canal, E., Coustans, M., Casez, O., Castan, B., Creange, A., Creisson, E., De Broucker, T., Depaz, R., Douay, X., Dulau, C., Durand-Dubief, F., Fagniez, O., Faucher, M., Floch, A., Fournier, M., Fromont, A., Gallien, P., Gamé, X., Gault, D., Gayou, A., Giroux, M., Gout, O., Grimaud, J., Hautecoeur, P., Kerbrat, A., Kremer, L., Kwiatkowski, A., Labeyrie, C., Lachaud, S., Lanctin-Garcia, C., Lanotte, L., Manchon, E., Maurousset, A., Milor, A.-M., Moisset, X., Mont-Cuquet, A., Moreau, T., Ouallet, J.-C., Patry, I., Peaureaux, D., Pouget, M.-C., Pourcher Martinez, V., Radot, C., Ruet, A., Saint-Val, C., Salmon, A., Taithe, F., Tatevin, P., Vaillant, M., Stahl, J.-P., Vuoto, F., Zaenker, C., and Lebrun-Frenay, C.

Published
2020
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12. Treatment of MOG antibody associated disorders: results of an international survey

Author

Whittam, D. H., Karthikeayan, V., Gibbons, E., Kneen, R., Chandratre, S., Ciccarelli, O., Hacohen, Y., de Seze, J., Deiva, K., Hintzen, R. Q., Wildemann, B., Jarius, S., Kleiter, I., Rostasy, K., Huppke, P., Hemmer, B., Paul, F., Aktas, O., Pröbstel, A. K., Arrambide, G., Tintore, M., Amato, M. P., Nosadini, M., Mancardi, M. M., Capobianco, M., Illes, Z., Siva, A., Altintas, A., Akman-Demir, G., Pandit, L., Apiwattankul, M., Hor, J. Y., Viswanathan, S., Qiu, W., Kim, H. J., Nakashima, I., Fujihara, K., Ramanathan, S., Dale, R. C., Boggild, M., Broadley, S., Lana-Peixoto, M. A., Sato, D. K., Tenembaum, S., Cabre, P., Wingerchuk, D. M., Weinshenker, B. G., Greenberg, B., Matiello, M., Klawiter, E. C., Bennett, J. L., Wallach, A. I., Kister, I., Banwell, B. L., Traboulsee, A., Pohl, D., Palace, J., Leite, M. I., Levy, M., Marignier, R., Solomon, T., Lim, M., Huda, S., and Jacob, A.

Published
2020
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13. Immunization and multiple sclerosis: Recommendations from the French Multiple Sclerosis Society

Author

Abadie, V., Achour, C., Ader, F., Alchaar, H., Alkhedr, A., Andreux, F., Androdias, G., Arjmand, R., Audoin, B., Audry, D., Aufauvre, D., Autreaux, C., Ayrignac, X., Bailbe, M., Benazet, M., Bensa, C., Bensmail, D., Berger, E., Bernady, P., Bertagna, Y., Biotti, D., Blanchard-Dauphin, A., Bonenfant, J., Bonnan, M., Bonnemain, B., Borgel, F., Botelho-Nevers, E., Boucly, S., Bourre, B., Boutière, C., Branger, P., Brassat, D., Bresch, S., Breuil, V., Brochet, B., Brugeilles, H., Bugnon, P., Cabre, P., Camdessanché, J.-P., Carra-Dalière, C., Casez, O., Chamouard, J.-M., Chassande, B., Chataignier, P., Chbicheb, M., Chenet, A., Ciron, J., Clavelou, P., Cohen, M., Colamarino, R., Collongues, N., Coman, I., Corail, P.-R., Courtois, S., Coustans, M., Creange, A., Creisson, E., Daluzeau, N., Davenas, C., De Seze, J., Debouverie, M., Depaz, R., Derache, N., Divio, L., Douay, X., Dulau, C., Durand-Dubief, F., Edan, G., Elias, Z., Fagniez, O., Faucher, M., Faucheux, J.-M., Fournier, M., Gagneux-Brunon, A., Gaida, P., Galli, P., Gallien, P., Gaudelus, J., Gault, D., Gayou, A., Genevray, M., Gentil, A., Gere, J., Gignoux, L., Giroux, M., Givron, P., Gout, O., Grimaud, J., Guennoc, A.-M., Hadhoum, N., Hautecoeur, P., Heinzlef, O., Jaeger, M., Jeannin, S., Kremer, L., Kwiatkowski, A., Labauge, P., Labeyrie, C., Lachaud, S., Laffont, I., Lanctin-Garcia, C., Lannoy, J., Lanotte, L., Laplaud, D., Latombe, D., Lauxerois, M., Le Page, E., Lebrun-Frenay, C., Lejeune, P., Lejoyeux, P., Lemonnier, B., Leray, E., Loche, C.-M., Louapre, C., Lubetzki, C., Maarouf, A., Mada, B., Magy, L., Maillart, E., Manchon, E., Marignier, R., Marque, P., Mathey, G., Maurousset, A., Mekies, C., Merienne, M., Michel, L., Milor, A.-M., Moisset, X., Montcuquet, A., Moreau, T., Morel, N., Moussa, M., Naudillon, J.-P., Normand, M., Olive, P., Ouallet, J.-C., Outteryck, O., Pacault, C., Papeix, C., Patry, I., Peaureaux, D., Pelletier, J., Pichon, B., Pittion, S., Planque, E., Pouget, M.-C., Pourcher, V., Radot, C., Robert, I., Rocher, F., Ruet, A., Saint-Val, C., Salle, J.-Y., Salmon, A., Sartori, E., Schaeffer, S., Stankhof, B., Taithe, F., Thouvenot, E., Tizon, C., Tourbah, A., Tourniaire, P., Vaillant, M., Vermersch, P., Vidil, S., Wahab, A., Warter, M.-H., Wiertlewski, S., Wiplosz, B., Wittwer, B., Zaenker, C., Zephir, H., Lebrun, C., and Vukusic, S.

Published
2019
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20. Inaugural tumor-like multiple sclerosis: clinical presentation and medium-term outcome in 87 patients

Author

Balloy, G., Pelletier, J., Suchet, L., Lebrun, C., Cohen, M., Vermersch, P., Zephir, H., Duhin, E., Gout, O., Deschamps, R., Le Page, E., Edan, G., Labauge, P., Carra-Dallieres, C., Rumbach, L., Berger, E., Lejeune, P., Devos, P., N’Kendjuo, J.-B., Coustans, M., Auffray-Calvier, E., Daumas-Duport, B., Michel, L., Lefrere, F., Laplaud, D. A., Brosset, C., Derkinderen, P., de Seze, J., Wiertlewski, S., and On behalf of the Société Francophone de la Sclérose en Plaques

Published
2018
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26. Étude rétrospective multicentrique de 15 cas adultes de xanthomatose cérébrotendineuse : aspects cliniques et paracliniques typiques et atypiques

Author

Lionnet, C., Carra, C., Ayrignac, X., Levade, T., Gayraud, D., Castelnovo, G., Besson, G., Androdias, G., Vukusic, S., Confavreux, C., Zaenker, C., De Seze, J., Collongues, N., Blanc, F., Tranchant, C., Wallon, D., Hannequin, D., Gerdelat-Mas, A., Brassat, D., Clanet, M., Zephir, H., Outteryck, O., Vermersch, P., and Labauge, P.

Published
2014
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38. Artificial intelligence extension of the OSCAR-IB criteria

Author

Petzold, A., Albrecht, P., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., Jensen, G. P., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., Zimmermann, H., Albrecht P., Petzold A., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., P. , Jensen, G., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., and Zimmermann, H.

Subjects
0301 basic medicine, Big Data, medicine.medical_specialty, Neurology, media_common.quotation_subject, Big data, MEDLINE, Reviews, Socio-culturale, Neurosciences. Biological psychiatry. Neuropsychiatry, Review, Public domain, Retina, Cohort Studies, 03 medical and health sciences, Annotation, 0302 clinical medicine, Artificial Intelligence, medicine, Humans, Quality (business), RC346-429, Tomography, media_common, Image pattern recognition, business.industry, General Neuroscience, Nervous System Diseases, Tomography, Optical Coherence, Algorithms, 030104 developmental biology, Optical Coherence, Imaging technology, RC0321, Neurology. Diseases of the nervous system, Neurology (clinical), Artificial intelligence, sense organs, business, 030217 neurology & neurosurgery, RC321-571
Abstract

Artificial intelligence (AI)‐based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human‐led validated consensus quality control criteria (OSCAR‐IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI‐based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five‐point expansion of the OSCAR‐IB criteria to embrace AI (OSCAR‐AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

Published
2021

39. Disease Reactivation After Cessation of Disease-Modifying Therapy in Patients With Relapsing-Remitting Multiple Sclerosis.

Author

Roos I., Malpas C., Leray E., Casey R., Horakova D., Havrdova E.K., Debouverie M., Patti F., De Seze J., Izquierdo G., Eichau S., Edan G., Prat A., Girard M., Ozakbas S., Grammond P., Zephir H., Ciron J., Maillart E., Moreau T., Amato M.P., Labauge P., Alroughani R., Buzzard K., Skibina O., Terzi M., Laplaud D.A., Berger E., Grand'Maison F., Lebrun-Frenay C., Cartechini E., Boz C., Lechner-Scott J., Clavelou P., Stankoff B., Prevost J., Kappos L., Pelletier J., Shaygannejad V., Yamout B.I., Khoury S.J., Gerlach O., Spitaleri D.L.A., Van Pesch V., Gout O., Turkoglu R., Heinzlef O., Thouvenot E., McCombe P.A., Soysal A., Bourre B., Slee M., Castillo-Trivino T., Bakchine S., Ampapa R., Butler E.G., Wahab A., Macdonell R.A., Aguera-Morales E., Cabre P., Ben N.H., Van der Walt A., Laureys G., Van Hijfte L., Ramo-Tello C.M., Maubeuge N., Hodgkinson S., Sanchez-Menoyo J.L., Barnett M.H., Labeyrie C., Vucic S., Sidhom Y., Gouider R., Csepany T., Sotoca J., de Gans K., Al-Asmi A., Fragoso Y.D., Vukusic S., Butzkueven H., Kalincik T., Roos I., Malpas C., Leray E., Casey R., Horakova D., Havrdova E.K., Debouverie M., Patti F., De Seze J., Izquierdo G., Eichau S., Edan G., Prat A., Girard M., Ozakbas S., Grammond P., Zephir H., Ciron J., Maillart E., Moreau T., Amato M.P., Labauge P., Alroughani R., Buzzard K., Skibina O., Terzi M., Laplaud D.A., Berger E., Grand'Maison F., Lebrun-Frenay C., Cartechini E., Boz C., Lechner-Scott J., Clavelou P., Stankoff B., Prevost J., Kappos L., Pelletier J., Shaygannejad V., Yamout B.I., Khoury S.J., Gerlach O., Spitaleri D.L.A., Van Pesch V., Gout O., Turkoglu R., Heinzlef O., Thouvenot E., McCombe P.A., Soysal A., Bourre B., Slee M., Castillo-Trivino T., Bakchine S., Ampapa R., Butler E.G., Wahab A., Macdonell R.A., Aguera-Morales E., Cabre P., Ben N.H., Van der Walt A., Laureys G., Van Hijfte L., Ramo-Tello C.M., Maubeuge N., Hodgkinson S., Sanchez-Menoyo J.L., Barnett M.H., Labeyrie C., Vucic S., Sidhom Y., Gouider R., Csepany T., Sotoca J., de Gans K., Al-Asmi A., Fragoso Y.D., Vukusic S., Butzkueven H., and Kalincik T.

Abstract

OBJECTIVES: To evaluate the rate of return of disease activity after cessation of multiple sclerosis (MS) disease-modifying therapy. METHOD(S): This was a retrospective cohort study from two large observational MS registries: MSBase and OFSEP. Patients with relapsing-remitting MS who had ceased a disease-modifying therapy and were followed up for the subsequent 12-months were included in the analysis. The primary study outcome was annualised relapse rate in the 12 months after disease-modifying therapy discontinuation stratified by patients who did, and did not, commence a subsequent therapy. The secondary endpoint was the predictors of first relapse and disability accumulation after treatment discontinuation. RESULT(S): 14,213 patients, with 18,029 eligible treatment discontinuation epochs, were identified for seven therapies. Annualised rates of relapse (ARR) started to increase 2-months after natalizumab cessation (month 2-4 ARR, 95% confidence interval): 0.47, 0.43-0.51). Commencement of a subsequent therapy within 2-4 months reduced the magnitude of disease reactivation (mean ARR difference: 0.15, 0.08-0.22). After discontinuation of fingolimod, rates of relapse increased overall (month 1-2 ARR: 0.80, 0.70-0.89), and stabilised faster in patients who started a new therapy within 1-2 months (mean ARR difference: 0.14, -0.01-0.29). Magnitude of disease reactivation for other therapies was low, but reduced further by commencement of another treatment 1-10 months after treatment discontinuation. Predictors of relapse were higher relapse rate in the year before cessation, female sex, younger age and higher EDSS. Commencement of a subsequent therapy reduced both the risk of relapse (HR 0.76, 95%CI 0.72-0.81) and disability accumulation (0.73, 0.65-0.80). CONCLUSION(S): The rate of disease reactivation after treatment cessation differs among MS treatments, with the peaks of relapse activity ranging from 1 to 10 months in untreated cohorts that discontinued different t

Published
2022

40. Impact of methodological choices in comparative effectiveness studies: application in natalizumab versus fingolimod comparison among patients with multiple sclerosis

Author

Lefort, M, Sharmin, S, Andersen, JB, Vukusic, S, Casey, R, Debouverie, M, Edan, G, Ciron, J, Ruet, A, De Seze, J, Maillart, E, Zephir, H, Labauge, P, Defer, G, Lebrun-Frenay, C, Moreau, T, Berger, E, Clavelou, P, Pelletier, J, Stankoff, B, Gout, O, Thouvenot, E, Heinzlef, O, Al-Khedr, A, Bourre, B, Casez, O, Cabre, P, Montcuquet, A, Wahab, A, Camdessanche, JP, Maurousset, A, Ben Nasr, H, Hankiewicz, K, Pottier, C, Maubeuge, N, Nifle, C, Laplaud, DA, Horakova, D, Dimitri-Boulos, D, Havrdova, EK, Alroughani, R, Izquierdo, G, Eichau, S, Ozakbas, S, Patti, F, Onofrj, M, Lugaresi, A, Terzi, M, Grammond, P, Grand'Maison, F, Yamout, B, Prat, A, Girard, M, Duquette, P, Boz, C, Trojano, M, McCombe, P, Slee, M, Lechner-Scott, J, Turkoglu, R, Sola, P, Ferraro, D, Granella, F, Shaygannejad, V, Prevost, J, Maimone, D, Skibina, O, Buzzard, K, Van der Walt, A, Karabudak, R, Van Wijmeersch, B, Csepany, T, Spitaleri, D, Vucic, S, Koch-Henriksen, N, Sellebjerg, F, Soerensen, PS, Christensen, CCH, Rasmussen, P, Jensen, MB, Frederiksen, JL, Bramow, S, Mathiesen, HK, Schreiber, K, Butzkueven, H, Magyari, M, Kalincik, T, Leray, E, Lefort, M, Sharmin, S, Andersen, JB, Vukusic, S, Casey, R, Debouverie, M, Edan, G, Ciron, J, Ruet, A, De Seze, J, Maillart, E, Zephir, H, Labauge, P, Defer, G, Lebrun-Frenay, C, Moreau, T, Berger, E, Clavelou, P, Pelletier, J, Stankoff, B, Gout, O, Thouvenot, E, Heinzlef, O, Al-Khedr, A, Bourre, B, Casez, O, Cabre, P, Montcuquet, A, Wahab, A, Camdessanche, JP, Maurousset, A, Ben Nasr, H, Hankiewicz, K, Pottier, C, Maubeuge, N, Nifle, C, Laplaud, DA, Horakova, D, Dimitri-Boulos, D, Havrdova, EK, Alroughani, R, Izquierdo, G, Eichau, S, Ozakbas, S, Patti, F, Onofrj, M, Lugaresi, A, Terzi, M, Grammond, P, Grand'Maison, F, Yamout, B, Prat, A, Girard, M, Duquette, P, Boz, C, Trojano, M, McCombe, P, Slee, M, Lechner-Scott, J, Turkoglu, R, Sola, P, Ferraro, D, Granella, F, Shaygannejad, V, Prevost, J, Maimone, D, Skibina, O, Buzzard, K, Van der Walt, A, Karabudak, R, Van Wijmeersch, B, Csepany, T, Spitaleri, D, Vucic, S, Koch-Henriksen, N, Sellebjerg, F, Soerensen, PS, Christensen, CCH, Rasmussen, P, Jensen, MB, Frederiksen, JL, Bramow, S, Mathiesen, HK, Schreiber, K, Butzkueven, H, Magyari, M, Kalincik, T, and Leray, E

Abstract

BACKGROUND: Natalizumab and fingolimod are used as high-efficacy treatments in relapsing-remitting multiple sclerosis. Several observational studies comparing these two drugs have shown variable results, using different methods to control treatment indication bias and manage censoring. The objective of this empirical study was to elucidate the impact of methods of causal inference on the results of comparative effectiveness studies. METHODS: Data from three observational multiple sclerosis registries (MSBase, the Danish MS Registry and French OFSEP registry) were combined. Four clinical outcomes were studied. Propensity scores were used to match or weigh the compared groups, allowing for estimating average treatment effect for treated or average treatment effect for the entire population. Analyses were conducted both in intention-to-treat and per-protocol frameworks. The impact of the positivity assumption was also assessed. RESULTS: Overall, 5,148 relapsing-remitting multiple sclerosis patients were included. In this well-powered sample, the 95% confidence intervals of the estimates overlapped widely. Propensity scores weighting and propensity scores matching procedures led to consistent results. Some differences were observed between average treatment effect for the entire population and average treatment effect for treated estimates. Intention-to-treat analyses were more conservative than per-protocol analyses. The most pronounced irregularities in outcomes and propensity scores were introduced by violation of the positivity assumption. CONCLUSIONS: This applied study elucidates the influence of methodological decisions on the results of comparative effectiveness studies of treatments for multiple sclerosis. According to our results, there are no material differences between conclusions obtained with propensity scores matching or propensity scores weighting given that a study is sufficiently powered, models are correctly specified and positivity assumption is ful

Published
2022

41. Disease Reactivation After Cessation of Disease-Modifying Therapy in Patients With Relapsing-Remitting Multiple Sclerosis

Author

Roos, I, Malpas, C, Leray, E, Casey, R, Horakova, D, Havrdova, EK, Debouverie, M, Patti, F, De Seze, J, Izquierdo, G, Eichau, S, Edan, G, Prat, A, Girard, M, Ozakbas, S, Grammond, P, Zephir, H, Ciron, J, Maillart, E, Moreau, T, Amato, MP, Labauge, P, Alroughani, R, Buzzard, K, Skibina, O, Terzi, M, Laplaud, DA, Berger, E, Grand'Maison, F, Lebrun-Frenay, C, Cartechini, E, Boz, C, Lechner-Scott, J, Clavelou, P, Stankoff, B, Prevost, J, Kappos, L, Pelletier, J, Shaygannejad, V, Yamout, B, Khoury, SJ, Gerlach, O, Spitaleri, DLA, Van Pesch, V, Gout, O, Turkoglu, R, Heinzlef, O, Thouvenot, E, McCombe, PA, Soysal, A, Bourre, B, Slee, M, Castillo-Trivino, T, Bakchine, S, Ampapa, R, Butler, EG, Wahab, A, Macdonell, RA, Aguera-Morales, E, Cabre, P, Ben, NH, Van der Walt, A, Laureys, G, Van Hijfte, L, Ramo-Tello, CM, Maubeuge, N, Hodgkinson, S, Sanchez-Menoyo, JL, Barnett, MH, Labeyrie, C, Vucic, S, Sidhom, Y, Gouider, R, Csepany, T, Sotoca, J, de Gans, K, Al-Asmi, A, Fragoso, YD, Vukusic, S, Butzkueven, H, Kalincik, T, Roos, I, Malpas, C, Leray, E, Casey, R, Horakova, D, Havrdova, EK, Debouverie, M, Patti, F, De Seze, J, Izquierdo, G, Eichau, S, Edan, G, Prat, A, Girard, M, Ozakbas, S, Grammond, P, Zephir, H, Ciron, J, Maillart, E, Moreau, T, Amato, MP, Labauge, P, Alroughani, R, Buzzard, K, Skibina, O, Terzi, M, Laplaud, DA, Berger, E, Grand'Maison, F, Lebrun-Frenay, C, Cartechini, E, Boz, C, Lechner-Scott, J, Clavelou, P, Stankoff, B, Prevost, J, Kappos, L, Pelletier, J, Shaygannejad, V, Yamout, B, Khoury, SJ, Gerlach, O, Spitaleri, DLA, Van Pesch, V, Gout, O, Turkoglu, R, Heinzlef, O, Thouvenot, E, McCombe, PA, Soysal, A, Bourre, B, Slee, M, Castillo-Trivino, T, Bakchine, S, Ampapa, R, Butler, EG, Wahab, A, Macdonell, RA, Aguera-Morales, E, Cabre, P, Ben, NH, Van der Walt, A, Laureys, G, Van Hijfte, L, Ramo-Tello, CM, Maubeuge, N, Hodgkinson, S, Sanchez-Menoyo, JL, Barnett, MH, Labeyrie, C, Vucic, S, Sidhom, Y, Gouider, R, Csepany, T, Sotoca, J, de Gans, K, Al-Asmi, A, Fragoso, YD, Vukusic, S, Butzkueven, H, and Kalincik, T

Abstract

BACKGROUND AND OBJECTIVES: To evaluate the rate of return of disease activity after cessation of multiple sclerosis (MS) disease-modifying therapy. METHODS: This was a retrospective cohort study from 2 large observational MS registries: MSBase and OFSEP. Patients with relapsing-remitting MS who had ceased a disease-modifying therapy and were followed up for the subsequent 12 months were included in the analysis. The primary study outcome was annualized relapse rate in the 12 months after disease-modifying therapy discontinuation stratified by patients who did, and did not, commence a subsequent therapy. The secondary endpoint was the predictors of first relapse and disability accumulation after treatment discontinuation. RESULTS: A total of 14,213 patients, with 18,029 eligible treatment discontinuation epochs, were identified for 7 therapies. Annualized rates of relapse (ARRs) started to increase 2 months after natalizumab cessation (month 2-4 ARR 0.47, 95% CI 0.43-0.51). Commencement of a subsequent therapy within 2-4 months reduced the magnitude of disease reactivation (mean ARR difference: 0.15, 0.08-0.22). After discontinuation of fingolimod, rates of relapse increased overall (month 1-2 ARR: 0.80, 0.70-0.89) and stabilized faster in patients who started a new therapy within 1-2 months (mean ARR difference: 0.14, -0.01 to 0.29). The magnitude of disease reactivation for other therapies was low but reduced further by commencement of another treatment 1-10 months after treatment discontinuation. Predictors of relapse were a higher relapse rate in the year before cessation, female sex, younger age, and higher EDSS score. Commencement of a subsequent therapy reduced both the risk of relapse (HR 0.76, 95% CI 0.72-0.81) and disability accumulation (0.73, 0.65-0.80). DISCUSSION: The rate of disease reactivation after treatment cessation differs among MS treatments, with the peaks of relapse activity ranging from 1 to 10 months in untreated cohorts that discontinued di

Published
2022

44. Isolated tumefactive demyelinating lesions: diagnosis and long-term evolution of 16 patients in a multicentric study

Author

Siri, A., Carra-Dalliere, Clarisse, Ayrignac, X., Pelletier, J., Audoin, B., Pittion-Vouyovitch, S., Debouverie, M., Lionnet, C., Viala, F., Sablot, D., Brassat, D., Ouallet, J.-C., Ruet, A., Brochet, B., Taillandier, L., Bauchet, L., Derache, N., Defer, G., Cabre, P., de Seze, J., Lebrun Frenay, C., Cohen, M., and Labauge, P.

Published
2015
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