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- Kuhle, J., et al.
(författare)
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Conversion from clinically isolated syndrome to multiple sclerosis: A large multicentre study
- 2015
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Ingår i: Multiple Sclerosis Journal. - : SAGE Publications. - 1352-4585 .- 1477-0970. ; 21:8, s. 1013-1024
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: We explored which clinical and biochemical variables predict conversion from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) in a large international cohort. Methods: Thirty-three centres provided serum samples from 1047 CIS cases with at least two years' follow-up. Age, sex, clinical presentation, T2-hyperintense lesions, cerebrospinal fluid (CSF) oligoclonal bands (OCBs), CSF IgG index, CSF cell count, serum 25-hydroxyvitamin D3 (25-OH-D), cotinine and IgG titres against Epstein-Barr nuclear antigen 1 (EBNA-1) and cytomegalovirus were tested for association with risk of CDMS. Results: At median follow-up of 4.31 years, 623 CIS cases converted to CDMS. Predictors of conversion in multivariable analyses were OCB (HR = 2.18, 95% CI = 1.71-2.77, p < 0.001), number of T2 lesions (two to nine lesions vs 0/1 lesions: HR = 1.97, 95% CI = 1.52-2.55, p < 0.001; >9 lesions vs 0/1 lesions: HR = 2.74, 95% CI = 2.04-3.68, p < 0.001) and age at CIS (HR per year inversely increase = 0.98, 95% CI = 0.98-0.99, p < 0.001). Lower 25-OH-D levels were associated with CDMS in univariable analysis, but this was attenuated in the multivariable model. OCB positivity was associated with higher EBNA-1 IgG titres. Conclusions: We validated MRI lesion load, OCB and age at CIS as the strongest independent predictors of conversion to CDMS in this multicentre setting. A role for vitamin D is suggested but requires further investigation.
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- Fissolo, N., et al.
(författare)
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Serum biomarker levels predict disability progression in patients with primary progressive multiple sclerosis
- 2023
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Ingår i: Journal of Neurology Neurosurgery and Psychiatry. - 0022-3050.
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundWe aimed to investigate the potential of serum biomarker levels to predict disability progression in a multicentric real-world cohort of patients with primary progressive multiple sclerosis (PPMS).MethodsA total of 141 patients with PPMS from 18 European MS centres were included. Disability progression was investigated using change in Expanded Disability Status Scale (EDSS) score over three time intervals: baseline to 2 years, 6 years and to the last follow-up. Serum levels of neurofilament light chain (sNfL), glial fibrillar acidic protein (sGFAP) and chitinase 3-like 1 (sCHI3L1) were measured using single-molecule array assays at baseline. Correlations between biomarker levels, and between biomarkers and age were quantified using Spearman's r. Univariable and multivariable linear models were performed to assess associations between biomarker levels and EDSS change over the different time periods.ResultsMedian (IQR) age of patients was 52.9 (46.4-58.5) years, and 58 (41.1%) were men. Median follow-up time was 9.1 (7.0-12.6) years. Only 8 (5.7%) patients received treatment during follow-up. sNfL and sGFAP levels were moderately correlated (r=0.43) and both weakly correlated with sCHI3L1 levels (r=0.19 and r=0.17, respectively). In multivariable analyses, levels of the three biomarkers were associated with EDSS changes across all time periods. However, when analysis was restricted to non-inflammatory patients according to clinical and radiological parameters (n=64), only sCHI3L1 levels remained associated with future EDSS change.ConclusionsLevels of sNfL, sGFAP and sCHI3L1 are prognostic biomarkers associated with disability progression in patients with PPMS, being CHI3L1 findings less dependent on the inflammatory component associated with disease progression.
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| 9. |
- Lopez-Soley, E, et al.
(författare)
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Diffusion tensor imaging metrics associated with future disability in multiple sclerosis
- 2023
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 13:1, s. 3565-
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Tidskriftsartikel (refereegranskat)abstract
- The relationship between brain diffusion microstructural changes and disability in multiple sclerosis (MS) remains poorly understood. We aimed to explore the predictive value of microstructural properties in white (WM) and grey matter (GM), and identify areas associated with mid-term disability in MS patients. We studied 185 patients (71% female; 86% RRMS) with the Expanded Disability Status Scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), and Symbol Digit Modalities Test (SDMT) at two time-points. We used Lasso regression to analyse the predictive value of baseline WM fractional anisotropy and GM mean diffusivity, and to identify areas related to each outcome at 4.1 years follow-up. Motor performance was associated with WM (T25FW: RMSE = 0.524, R2 = 0.304; 9HPT dominant hand: RMSE = 0.662, R2 = 0.062; 9HPT non-dominant hand: RMSE = 0.649, R2 = 0.139), and SDMT with GM diffusion metrics (RMSE = 0.772, R2 = 0.186). Cingulum, longitudinal fasciculus, optic radiation, forceps minor and frontal aslant were the WM tracts most closely linked to motor dysfunction, and temporal and frontal cortex were relevant for cognition. Regional specificity related to clinical outcomes provide valuable information that can be used to develop more accurate predictive models that could improve therapeutic strategies.
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- Lopez-Soley, E, et al.
(författare)
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Dynamics and Predictors of Cognitive Impairment along the Disease Course in Multiple Sclerosis
- 2021
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Ingår i: Journal of personalized medicine. - : MDPI AG. - 2075-4426. ; 11:11
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Tidskriftsartikel (refereegranskat)abstract
- (1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper features a longitudinal study with 212 patients who underwent several cognitive examinations at different time points. Dynamics of cognition were assessed using mixed-effects linear spline models. Machine learning techniques were used to identify which baseline demographic, clinical, and neuroimaging measures best predicted CI. (3) Results: In the first 5 years of MS, we detected an increase in the z-scores of global cognition, verbal memory, and information processing speed, which was followed by a decline in global cognition and memory (p < 0.05) between years 5 and 15. From 15 to 30 years of disease onset, cognitive decline continued, affecting global cognition and verbal memory. The baseline measures that best predicted CI were education, disease severity, lesion burden, and hippocampus and anterior cingulate cortex volume. (4) Conclusions: In MS, cognition deteriorates 5 years after disease onset, declining steadily over the next 25 years and more markedly affecting verbal memory. Education, disease severity, lesion burden, and volume of limbic structures predict future CI and may be helpful when identifying at-risk patients.
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