TY - JOUR
T1 - Early clinical markers of aggressive multiple sclerosis
AU - Malpas, Charles B.
AU - Manouchehrinia, Ali
AU - Sharmin, Sifat
AU - Roos, Izanne
AU - Horakova, Dana
AU - Havrdova, Eva Kubala
AU - Trojano, Maria
AU - Izquierdo, Guillermo
AU - Eichau, Sara
AU - Bergamaschi, Roberto
AU - Sola, Patrizia
AU - Ferraro, Diana
AU - Lugaresi, Alessandra
AU - Prat, Alexandre
AU - Girard, Marc
AU - Duquette, Pierre
AU - Grammond, Pierre
AU - Grand'Maison, Francois
AU - Ozakbas, Serkan
AU - Van Pesch, Vincent
AU - Granella, Franco
AU - Hupperts, Raymond
AU - Pucci, Eugenio
AU - Boz, Cavit
AU - Sidhom, Youssef
AU - Gouider, Riadh
AU - Spitaleri, Daniele
AU - Soysal, Aysun
AU - Petersen, Thor
AU - Verheul, Freek
AU - Karabudak, Rana
AU - Turkoglu, Recai
AU - Ramo-Tello, Cristina
AU - Terzi, Murat
AU - Cristiano, Edgardo
AU - Slee, Mark
AU - McCombe, Pamela
AU - Macdonell, Richard
AU - Fragoso, Yara
AU - Olascoaga, Javier
AU - Altintas, Ayse
AU - Olsson, Tomas
AU - Butzkueven, Helmut
AU - Hillert, Jan
AU - Kalincik, Tomas
AU - MSBase Study Group
AU - Cabrera-Gomez, J
AU - Roullet, E
AU - Zwanikken, C
AU - den Braber-Moerland, Leontien
AU - Deri, Norma
AU - Saladino, M
AU - Vrech, Carlos
AU - Kermode, Allan
AU - Fabis-Pedrini, Marzena
AU - Barnett, Michael
AU - Lechner-Scott, Jeannette
AU - Shuey, N
AU - Hodgkinson, Suzanne
AU - McCombe, Pamela
AU - Van Wijmeersch, Bart
AU - Oleschko Arruda, W
AU - Prevost, Julie
AU - Moore, Fraser
AU - Fernandez Bolaños, Ricardo
AU - Oreja-Guevara, C
AU - Perez Sempere, Angel
AU - Sanchez-Menoyo, Jose Luis
AU - Andres Dominguez, Jose
AU - Hughes, Stella
AU - McDonnell, Gavin
AU - Gray, Orla
AU - Csepany, Tunde
AU - Dobos, Eniko
AU - Rajda, Cecilia
AU - Flechter, S
AU - Singhal, Bhim
AU - Amato, Maria Pia
AU - Solaro, Claudio
AU - Yamout, Bassem
AU - Petkovska-Boskova, T
AU - Vella, Norbert
AU - Sinnige, L G F
AU - Alkhaboori, Jabir
AU - Edite Rio, Maria
AU - Sirbu, Carmen
AU - Vitetta, Francesca
AU - Simone, Anna Maria
AU - De Luca, Giovanna
AU - Di Tommaso, Valeria
AU - Travaglini, Daniela
AU - Pietrolongo, Erika
AU - di Ioia, Maria
AU - Farina, Deborah
AU - Mancinelli, Luca
AU - Curti, Erica
AU - Tsantes, Elena
AU - Diamanti, Matteo
AU - Cartechini, E.
AU - Van der Walt, Anneke
AU - Spelman, Timothy
AU - Marriott, M.
AU - Kilpatrick, Trevor
AU - King, John
AU - Buzzard, Katherine
AU - Nguyen, Ai Lan
AU - Dwyer, Chris
AU - Monif, Mastura
AU - Rojas, Juan Ignacio
AU - Manouchehrinia, Ali
AU - Olsson, Tomas
AU - Hillert, Jan
PY - 2020/5
Y1 - 2020/5
N2 - Patients with the ‘aggressive’ form of multiple sclerosis accrue disability at an accelerated rate, typically reaching Expanded Disability Status Score (EDSS) ≥ 6 within 10 years of symptom onset. Several clinicodemographic factors have been associated with aggressive multiple sclerosis, but less research has focused on clinical markers that are present in the first year of disease. The development of early predictive models of aggressive multiple sclerosis is essential to optimize treatment in this multiple sclerosis subtype. We evaluated whether patients who will develop aggressive multiple sclerosis can be identified based on early clinical markers. We then replicated this analysis in an independent cohort. Patient data were obtained from the MSBase observational study. Inclusion criteria were (i) first recorded disability score (EDSS) within 12 months of symptom onset; (ii) at least two recorded EDSS scores; and (iii) at least 10 years of observation time, based on time of last recorded EDSS score. Patients were classified as having ‘aggressive multiple sclerosis’ if all of the following criteria were met: (i) EDSS ≥ 6 reached within 10 years of symptom onset; (ii) EDSS ≥ 6 confirmed and sustained over ≥6 months; and (iii) EDSS ≥ 6 sustained until the end of follow-up. Clinical predictors included patient variables (sex, age at onset, baseline EDSS, disease duration at first visit) and recorded relapses in the first 12 months since disease onset (count, pyramidal signs, bowel-bladder symptoms, cerebellar signs, incomplete relapse recovery, steroid administration, hospitalization). Predictors were evaluated using Bayesian model averaging. Independent validation was performed using data from the Swedish Multiple Sclerosis Registry. Of the 2403 patients identified, 145 were classified as having aggressive multiple sclerosis (6%). Bayesian model averaging identified three statistical predictors: age > 35 at symptom onset, EDSS ≥ 3 in the first year, and the presence of pyramidal signs in the first year. This model significantly predicted aggressive multiple sclerosis [area under the curve (AUC) = 0.80, 95% confidence intervals (CIs): 0.75, 0.84, positive predictive value = 0.15, negative predictive value = 0.98]. The presence of all three signs was strongly predictive, with 32% of such patients meeting aggressive disease criteria. The absence of all three signs was associated with a 1.4% risk. Of the 556 eligible patients in the Swedish Multiple Sclerosis Registry cohort, 34 (6%) met criteria for aggressive multiple sclerosis. The combination of all three signs was also predictive in this cohort (AUC = 0.75, 95% CIs: 0.66, 0.84, positive predictive value = 0.15, negative predictive value = 0.97). Taken together, these findings suggest that older age at symptom onset, greater disability during the first year, and pyramidal signs in the first year are early indicators of aggressive multiple sclerosis.
AB - Patients with the ‘aggressive’ form of multiple sclerosis accrue disability at an accelerated rate, typically reaching Expanded Disability Status Score (EDSS) ≥ 6 within 10 years of symptom onset. Several clinicodemographic factors have been associated with aggressive multiple sclerosis, but less research has focused on clinical markers that are present in the first year of disease. The development of early predictive models of aggressive multiple sclerosis is essential to optimize treatment in this multiple sclerosis subtype. We evaluated whether patients who will develop aggressive multiple sclerosis can be identified based on early clinical markers. We then replicated this analysis in an independent cohort. Patient data were obtained from the MSBase observational study. Inclusion criteria were (i) first recorded disability score (EDSS) within 12 months of symptom onset; (ii) at least two recorded EDSS scores; and (iii) at least 10 years of observation time, based on time of last recorded EDSS score. Patients were classified as having ‘aggressive multiple sclerosis’ if all of the following criteria were met: (i) EDSS ≥ 6 reached within 10 years of symptom onset; (ii) EDSS ≥ 6 confirmed and sustained over ≥6 months; and (iii) EDSS ≥ 6 sustained until the end of follow-up. Clinical predictors included patient variables (sex, age at onset, baseline EDSS, disease duration at first visit) and recorded relapses in the first 12 months since disease onset (count, pyramidal signs, bowel-bladder symptoms, cerebellar signs, incomplete relapse recovery, steroid administration, hospitalization). Predictors were evaluated using Bayesian model averaging. Independent validation was performed using data from the Swedish Multiple Sclerosis Registry. Of the 2403 patients identified, 145 were classified as having aggressive multiple sclerosis (6%). Bayesian model averaging identified three statistical predictors: age > 35 at symptom onset, EDSS ≥ 3 in the first year, and the presence of pyramidal signs in the first year. This model significantly predicted aggressive multiple sclerosis [area under the curve (AUC) = 0.80, 95% confidence intervals (CIs): 0.75, 0.84, positive predictive value = 0.15, negative predictive value = 0.98]. The presence of all three signs was strongly predictive, with 32% of such patients meeting aggressive disease criteria. The absence of all three signs was associated with a 1.4% risk. Of the 556 eligible patients in the Swedish Multiple Sclerosis Registry cohort, 34 (6%) met criteria for aggressive multiple sclerosis. The combination of all three signs was also predictive in this cohort (AUC = 0.75, 95% CIs: 0.66, 0.84, positive predictive value = 0.15, negative predictive value = 0.97). Taken together, these findings suggest that older age at symptom onset, greater disability during the first year, and pyramidal signs in the first year are early indicators of aggressive multiple sclerosis.
KW - aggressive disease
KW - disability
KW - multiple sclerosis
KW - precision medicine
KW - prediction
UR - http://www.scopus.com/inward/record.url?scp=85085265562&partnerID=8YFLogxK
UR - http://purl.org/au-research/grants/NHMRC/1129189
UR - http://purl.org/au-research/grants/NHMRC/1140766
UR - http://purl.org/au-research/grants/NHMRC/1157717
U2 - 10.1093/brain/awaa081
DO - 10.1093/brain/awaa081
M3 - Article
C2 - 32386427
AN - SCOPUS:85085265562
SN - 1460-2156
VL - 143
SP - 1400
EP - 1413
JO - Brain : a journal of neurology
JF - Brain : a journal of neurology
IS - 5
ER -