Comparative effectiveness and cost-effectiveness of natalizumab and fingolimod in rapidly evolving severe relapsing-remitting multiple sclerosis in the United Kingdom.

AIM: To evaluate the real-world comparative effectiveness and the cost-effectiveness, from a UK National Health Service perspective, of natalizumab versus fingolimod in patients with rapidly evolving severe relapsing-remitting multiple sclerosis (RES-RRMS). METHODS: Real-world data from the MSBase Registry were obtained for patients with RES-RRMS who were previously either naive to disease-modifying therapies or had been treated with interferon-based therapies, glatiramer acetate, dimethyl fumarate, or teriflunomide (collectively known as BRACETD). Matched cohorts were selected by 3-way multinomial propensity score matching, and the annualized relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M) were compared between treatment groups. Comparative effectiveness results were used in a cost-effectiveness model comparing natalizumab and fingolimod, using an established Markov structure over a lifetime horizon with health states based on the Expanded Disability Status Scale. Additional model data sources included the UK MS Survey 2015, published literature, and publicly available sources. RESULTS: In the comparative effectiveness analysis, we found a significantly lower ARR for patients starting natalizumab compared with fingolimod (rate ratio [RR] = 0.65; 95% confidence interval [CI], 0.57-0.73) or BRACETD (RR = 0.46; 95% CI, 0.42-0.53). Similarly, CDI6M was higher for patients starting natalizumab compared with fingolimod (hazard ratio [HR] = 1.25; 95% CI, 1.01-1.55) and BRACETD (HR = 1.46; 95% CI, 1.16-1.85). In patients starting fingolimod, we found a lower ARR (RR = 0.72; 95% CI, 0.65-0.80) compared with starting BRACETD, but no difference in CDI6M (HR = 1.17; 95% CI, 0.91-1.50). Differences in CDW6M were not found between the treatment groups. In the base-case cost-effectiveness analysis, natalizumab dominated fingolimod (0.302 higher quality-adjusted life-years [QALYs] and £17,141 lower predicted lifetime costs). Similar cost-effectiveness results were observed across sensitivity analyses. CONCLUSIONS: This MSBase Registry analysis suggests that natalizumab improves clinical outcomes when compared with fingolimod, which translates to higher QALYs and lower costs in UK patients with RES-RRMS.

There are several medications used to treat people with relapsing remitting multiple sclerosis, such as interferon-based therapies (Betaferon/Betaseron (US), Rebif, Avonex, Extavia), glatiramer acetate (Copaxone), teriflunomide (Aubagio), and dimethyl fumarate (Tecfidera), collectively named BRACETD. Other treatments for multiple sclerosis (MS) have a narrower use, such as natalizumab (Tysabri) or fingolimod (Gilenya), among others.This study objective was to assess how well natalizumab and fingolimod helped treating MS (clinical effectiveness) and subsequently estimate what the cost of these treatments is in comparison to the benefit they bring to people with rapidly evolving severe MS that use them in the United Kingdom (UK) (cost-effectiveness).We used an international disease registry (MSBase), which collects clinical data from people with MS in various centers around the world to compare the effectiveness of natalizumab, fingolimod and BRACETD treatments. We used a technique called propensity score matching to obtain results from comparable patient groups. People treated with natalizumab had better disease control, namely with fewer relapses and higher improvement on their disability level, than patients on fingolimod or BRACETD. Conversely, there were no differences between each group of people on a measure called disability worsening.Based on these clinical results, we built an economic model that simulates the lifetime costs and consequences of treating people with MS with natalizumab in comparison with fingolimod. We found that using natalizumab was less costly and was more effective compared to using fingolimod in UK patients.

Assessing clinical utility of machine learning and artificial intelligence approaches to analyze speech recordings in multiple sclerosis: A pilot study.

BACKGROUND: An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria. METHOD: The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve. RESULTS: The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant. CONCLUSION: Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations.

Associations Between Homeostasis Model Assessment (HOMA) and Routinely Examined Parameters in Individuals With Metabolic Syndrome.

The aim of the study was to investigate whether routine clinical parameters, including visceral adiposity index (VAI) and atherogenic index of plasma (AIP), could become widely applicable predictors of insulin resistance (IR), evaluated using homeostasis model assessment (HOMA-IR, HOMA-ß), with regard to presence of metabolic syndrome (MS). The study comprised 188 individuals identified to meet the MS criteria during regular health examinations and an equal number of age, sex-matched controls without MS. The strongest correlations were noted between HOMA-IR and waist circumference (WC) in the MS group (r=0.57) as well as between HOMA-IR and alanine aminotransferase (ALT, r=0.57) or aspartate aminotransferase (r=0.56) in the controls, with a statistical significance of p<0.001. In a multivariate linear regression model, the predictors of HOMA-IR were WC (linear coefficient ß=0.1, p<0.001), ALT (ß=2.28, p<0.001) and systolic blood pressure (ß=0.04, p<0.001). HOMA-ß was determined by WC (ß=1.97, p=0.032) and ALT (ß=99.49, p=0.004) and inversely associated with age (ß=-1.31, p=0.004). Neither VAI nor AIP were significant predictors. The presence of MS was significantly associated with both HOMA-IR and HOMA-ß. These results indicate that WC and ALT appear to be reliable predictors of IR. Comprehensive assessment of these parameters may serve for estimating the level of IR.

Identification of multiple sclerosis patients at highest risk of cognitive impairment using an integrated brain magnetic resonance imaging assessment approach.

BACKGROUND AND PURPOSE: While impaired cognitive performance is common in multiple sclerosis (MS), it has been largely underdiagnosed. Here a magnetic resonance imaging (MRI) screening algorithm is proposed to identify patients at highest risk of cognitive impairment. The objective was to examine whether assessment of lesion burden together with whole brain atrophy on MRI improves our ability to identify cognitively impaired MS patients. METHODS: Of the 1253 patients enrolled in the study, 1052 patients with all cognitive, volumetric MRI and clinical data available were included in the analysis. Brain MRI and neuropsychological assessment with the Brief International Cognitive Assessment for Multiple Sclerosis were performed. Multivariable logistic regression and individual prediction analysis were used to investigate the associations between MRI markers and cognitive impairment. The results of the primary analysis were validated at two subsequent time points (months 12 and 24). RESULTS: The prevalence of cognitive impairment was greater in patients with low brain parenchymal fraction (BPF) (<0.85) and high T2 lesion volume (T2-LV) (>3.5 ml) than in patients with high BPF (>0.85) and low T2-LV (<3.5 ml), with an odds ratio (OR) of 6.5 (95% CI 4.4-9.5). Low BPF together with high T2-LV identified in 270 (25.7%) patients predicted cognitive impairment with 83% specificity, 82% negative predictive value, 51% sensitivity and 75% overall accuracy. The risk of confirmed cognitive decline over the follow-up was greater in patients with high T2-LV (OR 2.1; 95% CI 1.1-3.8) and low BPF (OR 2.6; 95% CI 1.4-4.7). CONCLUSIONS: The integrated MRI assessment of lesion burden and brain atrophy may improve the stratification of MS patients who may benefit from cognitive assessment.

Multiple sclerosis and the accumulation of iron in the Basal Ganglia: quantitative assessment of brain iron using MRI t(2) relaxometry.

The aim of this work was to quantify the accumulation of iron in the basal ganglia in multiple sclerosis (MS) patients and in a control group, and to investigate the relationship between iron accumulation and other parameters assessed in MS, i.e. lesion load (LL) and brain parenchymal fraction (BPF). Magnetic resonance imaging T(2) relaxometry was used for the measurement. 970 patients with clinically definite MS and 117 controls were examined. Patients were divided into three subgroups according to LL and BPF. This work provides quantitative evidence of increased iron accumulation in the basal ganglia in MS patients in comparison to healthy controls. We also found that in the subgroup with small LL value, iron accumulation is higher than in the subgroup with large LL value. The hypothesis of a neurodegenerative component of MS is supported by the changes in iron content in the brain.

[Assessment of the incidence of metabolic syndrome]. / Posouzení frekvence výskytu metabolického syndromu.

BACKGROUND: Metabolic syndrome represents a disease with high prevalence and influence on the cardiovascular morbidity and mortality. The aim of this study is to estimate frequency of metabolic syndrome in the district Sumperk, in years 1979-1981 based on the analysis of large Preventive check-ups database. METHODS AND RESULTS: Database of Preventive oncologic check-ups from Sumperk district comprising 40 099 subjects with follow up in years 1979-1981 has been used to assess the metabolic syndrome prevalence. Incidence of the risk factors of the metabolic syndrome have been calculated and compared with current situation in the Czech Republic. The estimated incidence of metabolic syndrome ranged from 2.2% to 8.4%, according to the selected criteria. As risk factors diabetes type II or glycaemia higher than 6.1 mmol/l, systolic or diastolic hypertension and BMI higher than 30.0 kg/m2 were considered. It has been found that metabolic syndrome is increasing with increasing age in both male and female population. CONCLUSIONS: It is possible to assume, based on the results of this study that the incidence of the metabolic syndrome is increasing in the last decades. It is necessary to focus our attention on the simple and practical methods for early detection of metabolic syndrome. Important is also the prevention because metabolic syndrome plays important role as a predictor of serious cardiovascular and metabolic diseases.