The usefulness of evaluative outcome measures in patients with multiple sclerosis

To select the most useful evaluative outcome measures for early multiple sclerosis, we included 156 recently diagnosed patients in a 3-year follow-up study, and assessed them on 23 outcome measures in the domains of disease-specific outcomes, physical functioning, mental health, social functioning and general health. A global rating scale (GRS) and the Expanded Disability Status Scale (EDSS) were used as external criteria to determine the minimally important change (MIC) for each outcome measure. Subsequently, we determined whether the outcome measures could detect their MIC reliably. From these, per domain the outcome measure that was found to be most sensitive to changes (responsive) was identified. At group level, 11 outcomes of the domains of physical functioning, mental health, social functioning and general health could reliably detect the MIC. Of these 11, the most responsive measures per domain were the Medical Outcome Study 36 Short Form sub-scale physical functioning (SF36pf), the Disability and Impact Profile (DIP) sub-scale psychological, the Rehabilitation Activities Profile sub-scale occupation (RAPocc) and the SF36 sub-scale health, respectively. Overall, the most responsive measures were the SF36pf and the RAPocc. In individual patients, none of the measures could reliably detect the MIC. In sum, in the early stages of multiple sclerosis the most useful evaluative outcome measures for research are the SF36pf (physical functioning) and the RAPocc (social functioning). © The Author (2006). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved

Predicting short-term disability progression in early multiple sclerosis: Added value of MRI parameters

Objective: Magnetic resonance imaging (MRI) and clinical parameters are associated with disease progression in multiple sclerosis (MS). The aim of this study was to investigate whether adding MRI parameters to a model with only clinical parameters could improve these associations. Methods: 89 patients (55 women) with recently diagnosed MS had clinical and MRI evaluation at baseline (time of diagnosis) and at follow-up after 2.2 years. Detailed clinical data were available, including disease type (relapse-onset or progressive-onset) and disability, as measured by the Expanded Disability Status Scale (EDSS). MRI parameters included Normalised Brain Volume (NBV) at baseline, percentage brain volume change (PBVC/year), T2- and T1-lesion loads and spinal cord abnormalities. Progression of disability (increase in EDSS of at least 1 point at follow-up) was the main outcome measure. For a model containing only clinical parameters, the added value of MRI parameters was tested using logistic regression. Results: PBVC/year and lesion loads at follow-up were significantly higher in the group with progression. Adding PBVC/year to a clinical model improved the model, indicating that MRI parameters added independent information (p<0.001). Conclusion: The rate of cerebral atrophy conveys added information for the progression of disability in patients with early MS, suggesting that clinical disability is determined by neurodegenerative changes as depicted by MRI

Vitality, perceived social support and disease activity determine the performance of social roles in recently diagnosed multiple sclerosis: a longitudinal analysis.

Objective: The aim of this study was to identify the principal determinants that are longitudinally associated with the performance of social roles in the first 3 years following a diagnosis of multiple sclerosis. Design: Inception cohort with 5 measurements over 3 years. Patients: A total of 156 patients recently diagnosed with multiple sclerosis. Method: Performance of social roles was measured using the 2 role functioning and the social sub-scales of the Medical Outcome Study Short Form 36. Potential determinants (n = 43) were divided into the following clusters: patient and disease characteristics (n = 12), psychosocial characteristics (n= 10), basic functions (n= 18) and basic activities (n= 3). Multivariate longitudinal regression analyses were performed with generalized estimating equations. A backwards selection procedure for every cluster per outcome reduced the large number of potential determinants. In order to determine whether longitudinal associations are present the selected determinants were entered into an overall regression model. Results: Twenty-three candidate determinants were selected. Vitality, measured with the SF36 sub-scale vitality, the T2-weighted supratentorial lesion load and the perceived amount of social support, measured with the Social Support List Discrepancies, were longitudinally associated with the performance of social roles in 2 or 3 of the models. Conclusion: Vitality, the perceived amount of social support, and disease activity, i.e. the T2-weighted supratentorial lesion load, determine the performance of social roles in the early stages of multiple sclerosis. © 2007 The Authors. Journal Compilation © 2007 Foundation of Rehabilitation Information

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

BACKGROUND: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. METHODS: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. RESULTS: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). CONCLUSIONS: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics