Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS).
Cognition
Cohort study
Longitudinal
Multiple sclerosis
Neuropsychology
Journal
Journal of neurology
ISSN: 1432-1459
Titre abrégé: J Neurol
Pays: Germany
ID NLM: 0423161
Informations de publication
Date de publication:
Feb 2019
Feb 2019
Historique:
received:
25
09
2018
accepted:
26
11
2018
revised:
14
11
2018
pubmed:
6
12
2018
medline:
29
5
2019
entrez:
6
12
2018
Statut:
ppublish
Résumé
Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis. Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we investigated whether demographic, clinical and conventional MRI markers at baseline were predictive for CI and longitudinal cognitive changes. At baseline, 22% of patients had CI (impairment in ≥2 cognitive domains) with highest frequencies and severity in processing speed and executive functions. Demographics (fewer years of academic education, higher age, male sex), clinical (EDSS, depressive symptoms) but no conventional MRI characteristics were linked to baseline CI. At follow-up, only 14% of patients showed CI suggesting effects of retesting. Neither baseline characteristics nor initiation of treatment between baseline and follow-up was able to predict cognitive changes within the follow-up period of 1 year. Identification of risk factors for short-term cognitive change in newly diagnosed MS or CIS is insufficient using only demographic, clinical and conventional MRI data. Change-sensitive, re-test reliable cognitive tests and more sophisticated predictors need to be employed in future clinical trials and cohort studies of early-stage MS to improve prediction.
Sections du résumé
BACKGROUND
BACKGROUND
Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis.
METHODS
METHODS
Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we investigated whether demographic, clinical and conventional MRI markers at baseline were predictive for CI and longitudinal cognitive changes.
RESULTS
RESULTS
At baseline, 22% of patients had CI (impairment in ≥2 cognitive domains) with highest frequencies and severity in processing speed and executive functions. Demographics (fewer years of academic education, higher age, male sex), clinical (EDSS, depressive symptoms) but no conventional MRI characteristics were linked to baseline CI. At follow-up, only 14% of patients showed CI suggesting effects of retesting. Neither baseline characteristics nor initiation of treatment between baseline and follow-up was able to predict cognitive changes within the follow-up period of 1 year.
CONCLUSIONS
CONCLUSIONS
Identification of risk factors for short-term cognitive change in newly diagnosed MS or CIS is insufficient using only demographic, clinical and conventional MRI data. Change-sensitive, re-test reliable cognitive tests and more sophisticated predictors need to be employed in future clinical trials and cohort studies of early-stage MS to improve prediction.
Identifiants
pubmed: 30515631
doi: 10.1007/s00415-018-9142-y
pii: 10.1007/s00415-018-9142-y
pmc: PMC6373354
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
386-397Subventions
Organisme : Bundesministerium für Forschung und Technologie
ID : 01GI0914
Organisme : Bundesministerium für Forschung und Technologie
ID : 01GI1601B
Organisme : Bundesministerium für Bildung und Forschung
ID : 01GI0916
Organisme : Bundesministerium für Bildung und Forschung
ID : 01GI1601G
Investigateurs
Seray Demir
(S)
Christoph Schröder
(C)
Lisa A Voithenleitner
(LA)
Achim Berthele
(A)
Sarah Haars
(S)
Sandra Nischwitz
(S)
Matthias J Knop
(MJ)
Susanne Rothacher
(S)
Jana Pöttgen
(J)
Clemens Warnke
(C)
Ralf A Linker
(RA)
Ulf Ziemann
(U)
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