A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

Objective: To compare the clinical effectiveness of high- and low-efficacy treatments in patients with recently active and inactive secondary progressive multiple sclerosis (SPMS) after accounting for therapeutic lag. Methods: Patients treated with high- (natalizumab, alemtuzumab, mitoxantrone, ocrelizumab, rituximab, cladribine, fingolimod) or low-efficacy (interferon β, glatiramer acetate, teriflunomide) therapies after SPMS onset were selected from MSBase and OFSEP, two large observational cohorts. Therapeutic lag was estimated for each patient based on their demographic and clinical characteristics. Propensity score was used to match patients treated with high and low-efficacy therapies. Outcomes after disregarding the period of therapeutic lag were compared in paired, pairwise-censored analyses. Results: 1000 patients were included in the primary analysis. Patients with active SPMS treated with high-efficacy therapy experienced less frequent relapses than those on low-efficacy therapy (hazard ratio [HR] 0.7, p=0.006). In patients with inactive SPMS, there was no evidence for a difference in relapse frequency between groups (HR=0.8,p=0.39). No evidence for a difference in the risk of disability progression was observed. Conclusion: In treated patients with SPMS, high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active, but not those with inactive, SPMS. However, more potent therapies do not offer an advantage in reducing disability progression in this patient group. Classification of Evidence: This study provides class III evidence that high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active SPMS whilst we did not find a difference in disability progression between patients treated with high- and low-efficacy therapy.

Background: Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking. Methods: Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS. Findings: Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history. Conclusions: Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study.

Background: Characteristics at clinically isolated syndrome (CIS) examination assist in identification of patient at highest risk of early second attack and could benefit the most from early disease-modifying drugs (DMDs). Objective: To examine determinants of second attack and validate a prognostic nomogram for individualised risk assessment of clinical conversion. Methods: Patients with CIS were prospectively followed up in the MSBase Incident Study. Predictors of clinical conversion were analysed using Cox proportional hazards regression. Prognostic nomograms were derived to calculate conversion probability and validated using concordance indices. Results: A total of 3296 patients from 50 clinics in 22 countries were followed up for a median (inter-quartile range (IQR)) of 1.92 years (0.90, 3.71). In all, 1953 (59.3%) patients recorded a second attack. Higher Expanded Disability Status Scale (EDSS) at baseline, first symptom location, oligoclonal bands and various brain and spinal magnetic resonance imaging (MRI) metrics were all predictors of conversion. Conversely, older age and DMD exposure post-CIS were associated with reduced rates. Prognostic nomograms demonstrated high concordance between estimated and observed conversion probabilities. Conclusion: This multinational study shows that age at CIS onset, DMD exposure, EDSS, multiple brain and spinal MRI criteria and oligoclonal bands are associated with shorter time to relapse. Nomogram assessment may be useful in clinical practice for estimating future clinical conversion.

Background: Natalizumab and fingolimod are used as high-efficacy treatments in relapsing–remitting multiple sclerosis. Several observational studies comparing these two drugs have shown variable results, using different methods to control treatment indication bias and manage censoring. The objective of this empirical study was to elucidate the impact of methods of causal inference on the results of comparative effectiveness studies. Methods: Data from three observational multiple sclerosis registries (MSBase, the Danish MS Registry and French OFSEP registry) were combined. Four clinical outcomes were studied. Propensity scores were used to match or weigh the compared groups, allowing for estimating average treatment effect for treated or average treatment effect for the entire population. Analyses were conducted both in intention-to-treat and per-protocol frameworks. The impact of the positivity assumption was also assessed. Results: Overall, 5,148 relapsing–remitting multiple sclerosis patients were included. In this well-powered sample, the 95% confidence intervals of the estimates overlapped widely. Propensity scores weighting and propensity scores matching procedures led to consistent results. Some differences were observed between average treatment effect for the entire population and average treatment effect for treated estimates. Intention-to-treat analyses were more conservative than per-protocol analyses. The most pronounced irregularities in outcomes and propensity scores were introduced by violation of the positivity assumption. Conclusions: This applied study elucidates the influence of methodological decisions on the results of comparative effectiveness studies of treatments for multiple sclerosis. According to our results, there are no material differences between conclusions obtained with propensity scores matching or propensity scores weighting given that a study is sufficiently powered, models are correctly specified and positivity assumption is fulfilled.

El presente artículo identifica y analiza la producción científica internacional que se enmarca en el conocimiento sobre las representaciones sociales de los docentes frente a la incursión de las tecnologías en su práctica y el efecto tecnosocial que generan. Desde una metodología mixta, donde se conjugan perspectivas cualitativas y cuantitativas, se desarrolló una revisión sistemática de artículos de investigación publicados en bases de datos como Scopus y Science Web. A partir de ahí, se llevó a cabo un análisis de los documentos rastreados, considerando la relación entre las categorías que orientaron el estudio: representaciones sociales y educación ciudadana con las tecnologías de la información y la comunicación (TIC). Los resultados evidencian que, en relación con el uso de las TIC, los docentes las conciben mediante sus percepciones e ideologías; las consideran simplemente como una herramienta desconectada de la enseñanza, lo que no ha permitido potenciar este recurso más allá de su uso instrumental. En este sentido, bajo una mirada sociocrítica de la educación, se examinan sus concepciones y los desafíos planteados en sus prácticas, ahora observadas en escenarios educativos que se han configurado en torno a la ciberciudadanía. De este modo, el profesorado deberá cuestionar su enseñanza, creando así oportunidades para transformar y revisar sus creencias como una forma de empoderamiento en su práctica profesional y pedagógica.