Early clinical markers of aggressive multiple sclerosis

Charles B. Malpas, Ali Manouchehrinia, Sifat Sharmin, Izanne Roos, Dana Horakova, Eva Kubala Havrdova, Maria Trojano, Guillermo Izquierdo, Sara Eichau, Roberto Bergamaschi, Patrizia Sola, Diana Ferraro, Alessandra Lugaresi, Alexandre Prat, Marc Girard, Pierre Duquette, Pierre Grammond, Francois Grand'Maison, Serkan Ozakbas, Vincent Van PeschFranco Granella, Raymond Hupperts, Eugenio Pucci, Cavit Boz, Youssef Sidhom, Riadh Gouider, Daniele Spitaleri, Aysun Soysal, Thor Petersen, Freek Verheul, Rana Karabudak, Recai Turkoglu, Cristina Ramo-Tello, Murat Terzi, Edgardo Cristiano, Mark Slee, Pamela McCombe, Richard Macdonell, Yara Fragoso, Javier Olascoaga, Ayse Altintas, Tomas Olsson, Helmut Butzkueven, Jan Hillert, Tomas Kalincik, MSBase Study Group

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1400-1413
Number of pages14
JournalBrain : a journal of neurology
Volume143
Issue number5
DOIs
Publication statusPublished - May 2020

Keywords

  • aggressive disease
  • disability
  • multiple sclerosis
  • precision medicine
  • prediction

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