ABSTRACT
BACKGROUND: Cognitive impairment affects half of the multiple sclerosis (MS) patient population and is an important contributor to patients' daily activities. Most cognitive impairment studies in MS are, however, cross-sectional or/and focused on the early disease stages. OBJECTIVE: We aim to assess the time course of decline of different cognitive domains. METHODS: We collected neuropsychological data on 514 MS patients to construct Kaplan-Meier survival curves of the tests included in the Neuropsychological Screening Battery for MS (NSBMS) and the Symbol Digit Modalities Test (SDMT). Cox-proportional hazard models were constructed to examine the influence of MS onset type, age at onset, gender, depression and level of education on the time course, expressed as age or disease. RESULTS: Survival curves of tests focusing on information processing speed (IPS) declined significantly faster than tests with less specific demands of IPS. Median age for pathological decline was 56.2 years (95% CI: 54.4-58.2) on the SDMT and 63.9 years (95% CI: 60-66.9) on the CLTR, a memory task. CONCLUSION: In conclusion, IPS is the cognitive domain not only most widely affected by MS but it is also the first cognitive deficit to emerge in MS.
Subject(s)
Cognition Disorders/physiopathology , Disease Progression , Multiple Sclerosis/physiopathology , Neuropsychological Tests/statistics & numerical data , Adult , Cognition Disorders/diagnosis , Cognition Disorders/etiology , Female , Humans , Male , Middle Aged , Multiple Sclerosis/complications , Proportional Hazards ModelsABSTRACT
BACKGROUND: Information on the relative influence of cognitive and physical impairment on the quality of life in multiple sclerosis is currently limited and no scientific consensus has been reached yet. OBJECTIVE: For this reason, we wanted to examine the relative contribution of cognitive and physical impairment measures comprised in the MSFC test on quality of life in MS. METHODS: In the National MS Center Melsbroek, patients regularly undergo MSFC and EQ5D measurements. We investigated the correlations between the EQ5D, EQVAS and the MSFC and EDSS scores by the use of ANOVA and multilinear models. RESULTS: We found a significant correlation between the EQVAS score and cognition in a univariate model. When including EDSS score and MSFC outcomes into the model, cognition was, however, excluded based on the Akaike Information Criterion. Cognition was, on the other hand, a significant predictor for the "Usual Activities" question of the EQ5D. CONCLUSIONS: Although cognitive performance as measured on the PASAT-3s does not correlate with a patient's perceived quality of life in a multivariate model, it remains an important predictor for the patient's usual activities.