Migraine is a disabling primary headache disorder that directly affects more than one billion people worldwide. Despite its widespread prevalence, migraine remains under-diagnosed and under-treated. To support clinical decision-making, we convened a European panel of experts to develop a ten-step approach to the diagnosis and management of migraine. Each step was established by expert consensus and supported by a review of current literature, and the Consensus Statement is endorsed by the European Headache Federation and the European Academy of Neurology. In this Consensus Statement, we introduce typical clinical features, diagnostic criteria and differential diagnoses of migraine. We then emphasize the value of patient centricity and patient education to ensure treatment adherence and satisfaction with care provision. Further, we outline best practices for acute and preventive treatment of migraine in various patient populations, including adults, children and adolescents, pregnant and breastfeeding women, and older people. In addition, we provide recommendations for evaluating treatment response and managing treatment failure. Lastly, we discuss the management of complications and comorbidities as well as the importance of planning long-term follow-up.

A substantial proportion of patients with migraine does not respond to, or cannot tolerate, oral preventive treatments. Erenumab is a novel CGRP-receptor antibody with preventive efficacy in migraine. We assessed its efficacy and tolerability in patients with episodic migraine in whom previous treatment with two-to-four migraine preventives had been unsuccessful. LIBERTY was a 12-week, double-blind, placebo-controlled randomised study at 59 sites in 16 countries. Eligible patients were aged 18-65 years and had a history of episodic migraine with or without aura for at least 12 months, had migraine for an average of 4-14 days per month during the 3 months before screening, and had been treated unsuccessfully (in terms of either efficacy or tolerability, or both) with between two and four preventive treatments. Eligible participants were randomly assigned (1:1) to receive either erenumab 140 mg (via two 70 mg injections) or placebo every 4 weeks subcutaneously for 12 weeks. Randomisation was by interactive response technology and was stratified by monthly frequency of migraine headache (4-7 vs 8-14 migraine days per month) during the baseline phase. Cenduit generated the randomisation list and assigned participants to groups. Participants, investigators, people doing various assessments, and the study sponsor were masked to treatment assignment. The primary endpoint was the proportion of patients achieving a 50% or greater reduction in the mean number of monthly migraine days during weeks 9-12. Efficacy was measured in the full analysis set, which included all randomly assigned patients who started their assigned treatment and completed at least one post-baseline monthly migraine day measurement. Safety and tolerability were assessed by recording adverse events and by physical examination, assessment of vital signs, clinical laboratory assessments, and electrocardiography. Safety was assessed in all randomly assigned patients who received at least one dose of study drug. This trial is registered with ClinicalTrials.gov, number NCT03096834. The trial is closed to new participants, but the open-label extension phase is ongoing. Between March 20, 2017, and Oct 27, 2017, 246 participants were randomly assigned, 121 to the erenumab group and 125 to the placebo group. 95 of 246 (39%) participants had previously unsuccessfully tried two preventive drugs, 93 (38%) had tried three, and 56 (23%) had tried four. At week 12, 36 (30%) patients in the erenumab had a 50% or greater reduction from baseline in the mean number of monthly migraine days, compared with 17 (14%) in the placebo group (odds ratio 2·7 [95% CI 1·4-5·2]; p=0·002). The tolerability and safety profiles of erenumab and placebo were similar. The most frequent treatment-emergent adverse event was injection site pain, which occurred in seven (6%) participants in both groups. Compared with placebo, erenumab was efficacious in patients with episodic migraine who previously did not respond to or tolerate between two and four previous migraine preventive treatments. Erenumab might be an option for patients with difficult-to-treat migraine who have high unmet needs and few treatment options. Novartis Pharma.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and these models are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to susceptible–infected–recovered (SIR) and susceptible-exposed-infectious-removed (SEIR) models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP; and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior across nations, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. This paper further suggests that a genuine novelty in outbreak prediction can be realized by integrating machine learning and SEIR models.

The three primary headaches, tension-type headache, migraine and cluster headache, occur in both genders, but all seem to have a sex-specific prevalence. These gender differences suggest that both male and female sex hormones could have an influence on the course of primary headaches. This review aims to summarise the most relevant and recent literature on this topic. Two independent reviewers searched PUBMED in a systematic manner. Search strings were composed using the terms LH, FSH, progesteron*, estrogen*, DHEA*, prolactin, testosterone, androgen*, headach*, migrain*, “tension type” or cluster. A timeframe was set limiting the search to articles published in the last 20 years, after January 1st 1997. Migraine tends to follow a classic temporal pattern throughout a woman’s life corresponding to the fluctuation of estrogen in the different reproductive stages. The estrogen withdrawal hypothesis forms the basis for most of the assumptions made on this behalf. The role of other hormones as well as the importance of sex hormones in other primary headaches is far less studied. The available literature mainly covers the role of sex hormones in migraine in women. Detailed studies especially in the elderly of both sexes and in cluster headache and tension-type headache are warranted to fully elucidate the role of these hormones in all primary headaches.

This paper provides a comprehensive state-of-the-art investigation of the recent advances in data science in emerging economic applications. The analysis is performed on the novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a broad and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, is used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which outperform other learning algorithms. It is further expected that the trends will converge toward the evolution of sophisticated hybrid deep learning models.

We compared the tolerability and efficacy of erenumab, a monoclonal antibody binding to the calcitonin gene-related peptide receptor, to topiramate for migraine prophylaxis in adults. HER-MES was a 24-week, randomised, double-blind, double-dummy, controlled trial conducted in 82 sites in Germany. Patients with ≥4 migraine days per month and naïve to study drugs were randomly assigned (1:1) to either subcutaneous erenumab (70 or 140 mg/month) plus topiramate placebo (erenumab group) or oral topiramate at the individual dose with optimal efficacy (50–100 mg/day) plus erenumab placebo (topiramate group). The primary endpoint was medication discontinuation due to an adverse event during the double-blind phase. The proportion of patients that achieved ≥50% reduction from baseline in monthly migraine days during the last 3 months of the double-blind phase was a secondary endpoint. Seven hundred and seventy-seven patients were randomised (from 22 February 2019 to 29 July, 2020) and 95.1% completed the study. In the erenumab group, 10.6% discontinued medication due to adverse events compared to 38.9% in the topiramate group (odds ratio, 0.19; 95% confidence interval 0.13–0.27; p < 0.001). Significantly more patients achieved a ≥50% reduction in monthly migraine days from baseline with erenumab (55.4% vs. 31.2%; odds ratio 2.76; 95% confidence interval 2.06–3.71; p < 0.001). No new safety signals occurred. Erenumab demonstrated a favourable tolerability and efficacy profile compared to topiramate. Trial registration: ClinicalTrials.gov NCT03828539, URL: https://clinicaltrials.gov/ct2/show/NCT03828539