Photophobia Contributes to Migraine-Associated Disability and Reduced Work Productivity: Results From the American Registry for Migraine Research (ARMR)

BACKGROUND

Photosensitivity, often called "photophobia" in the migraine literature, is a common and bothersome symptom for most people during their migraine attacks. This study aimed to investigate the association of photophobia severity with work productivity, activity impairment, and migraine-associated disability using data from a large cohort of patients with migraine who were enrolled into the American Registry for Migraine Research (ARMR).

METHODS

This study used Photosensitivity Assessment Questionnaire (PAQ) scores to investigate the relationship between photophobia severity with work productivity and activity impairment (using the Work Productivity and Activity Impairment [WPAI] questionnaire) and migraine-related disability (using the Migraine Disability Assessment [MIDAS]) among those with migraine. Summary statistics are presented as means and standard deviations for variables that were normally distributed and as medians and interquartile ranges for variables that were not normally distributed. Multiple linear regression models were developed to measure the relationships between photophobia scores with work productivity and activity impairment and migraine-associated disability, controlling for age, sex, headache frequency, headache intensity, anxiety (using the generalized anxiety disorder [GAD-7]), and depression (using the Patient Health Questionnaire [PHQ-2]).

RESULTS

One thousand eighty-four participants were included. Average age was 46.1 (SD 13.8) years, 87.2% (n = 945) were female, average headache frequency during the previous 90 days was 44.3 (SD 29.9), average headache intensity was 5.9 (SD 1.7), median PHQ-2 score was 1 (IQR 0-2), and median GAD-7 was 5 (IQR 2-8). Mean PAQ score was 0.47 (SD 0.32), and median MIDAS score was 38 (IQR 15.0-80.0). Among the 584 employed participants, 47.4% (n = 277) reported missing work in the past week because of migraine, mean overall work impairment was 42.8% (SD 26.7), mean activity impairment was 42.5% (SD 26.2), mean presenteeism score was 38.4% (SD 24.4), and median absenteeism was 0 (IQR 0-14.5). After controlling for age, sex, headache frequency, average headache intensity, PHQ-2 score, and GAD-7 score, there was a statistically significant association between photophobia scores with: a) MIDAS scores (F[7,1028] = 127.42, P < 0.001, R 2 = 0.461, n = 1,036); b) overall work impairment (F[7,570] = 29.23, P < 0.001, R 2 = 0.255, n = 578); c) activity impairment (F[7,570] = 27.42, P < 0.001, R 2 = 0.243, n = 578); d) presenteeism (F[7,570] = 29.17, P < 0.001, R 2 = 0.255, n = 578); and e) absenteeism for the zero-inflated ( P = 0.003) and negative binomial ( P = 0.045) model components ( P < 0.001, n = 578).

CONCLUSIONS

In those with migraine, severe photophobia is associated with reduced work productivity and higher presenteeism, absenteeism, activity impairment, and migraine-related disability.

Posttraumatic headache is a distinct headache type from migraine

PURPOSE OF REVIEW

Posttraumatic headache (PTH), a headache that develops within 7 days of a causative injury, is one of the most common secondary headaches, mostly attributed to mild traumatic brain injury (mTBI). Because presence of preinjury headache is a risk factor for developing PTH and PTH symptoms often resemble migraine or tension-type headache, the association between PTH and primary headaches has attracted attention from clinicians and scientists.

RECENT FINDINGS

Recent studies on epidemiological aspects, headache features, risk factors, imaging characteristics, and response to treatment, suggest overlapping features and distinct objective findings in PTH compared to migraine.

SUMMARY

We argue that PTH is distinct from migraine. Therefore, PTH epidemiology, pathophysiology, diagnosis, treatment, and prognosis should continue to be investigated separately from migraine.

Photophobia is associated with lower sleep quality in individuals with migraine: results from the American Registry for Migraine Research (ARMR)

BACKGROUND

Patients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aimed to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine.

METHODS

A cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), sleep-related impairments (SRI), and insomnia. Each model was controlled for age, sex, headache frequency, anxiety, and depression.

RESULTS

A total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p < 0.001). Photophobia scores were associated with SQ (p < 0.001), SDis (p < 0.001), SOL (p = 0.011), SRI (p = 0.020), and insomnia (p = 0.005) after controlling for age, sex, headache frequency, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p < 0.007), SOL (p = 0.010), and insomnia (p = 0.014).

CONCLUSION

Results suggest that photophobia is a significant predictor of poor sleep quality and sleep disturbances in migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine.

Posttraumatic Headache

OBJECTIVE

This article provides an overview of the epidemiology, diagnosis, clinical presentation, pathophysiology, prognosis, and treatment of posttraumatic headache attributed to mild traumatic brain injury (mTBI).

LATEST DEVELOPMENTS

The International Classification of Headache Disorders, Third Edition requires that posttraumatic headache begin within 7 days of the inciting trauma. Although posttraumatic headache characteristics and associated symptoms vary, most commonly there is substantial overlap with symptoms of migraine or tension-type headache. New insights into posttraumatic headache pathophysiology suggest roles for neuroinflammation, altered pain processing and modulation, and changes in brain structure and function. Although the majority of posttraumatic headache resolves during the acute phase, about one-third of individuals have posttraumatic headache that persists for at least several months. Additional work is needed to identify predictors and early markers of posttraumatic headache persistence, but several potential predictors have been identified such as having migraine prior to the mTBI, the total number of TBIs ever experienced, and the severity of initial symptoms following the mTBI. Few data are available regarding posttraumatic headache treatment; studies investigating different treatments and the optimal timing for initiating posttraumatic headache treatment are needed.

ESSENTIAL POINTS

Posttraumatic headache begins within 7 days of the causative injury. The characteristics of posttraumatic headache most commonly resemble those of migraine or tension-type headache. Posttraumatic headache persists for 3 months or longer in about one-third of individuals. Additional studies investigating posttraumatic headache treatment are needed.

A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records

OBJECTIVE

To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes.

BACKGROUND

Headache frequency, defined as the number of days with any headache in a month (or 4 weeks), remains a key parameter in the evaluation of treatment response to migraine preventive medications. However, due to the variations and inconsistencies in documentation by clinicians, significant challenges exist to accurately extract headache frequency from the electronic health record (EHR) by traditional NLP algorithms.

METHODS

This was a retrospective cross-sectional study with patients identified from two tertiary headache referral centers, Mayo Clinic Arizona and Mayo Clinic Rochester. All neurology consultation notes written by 15 specialized clinicians (11 headache specialists and 4 nurse practitioners) between 2012 and 2022 were extracted and 1915 notes were used for model fine-tuning (90%) and testing (10%). We employed four different NLP frameworks: (1) ClinicalBERT (Bidirectional Encoder Representations from Transformers) regression model, (2) Generative Pre-Trained Transformer-2 (GPT-2) Question Answering (QA) model zero-shot, (3) GPT-2 QA model few-shot training fine-tuned on clinical notes, and (4) GPT-2 generative model few-shot training fine-tuned on clinical notes to generate the answer by considering the context of included text.

RESULTS

The mean (standard deviation) headache frequency of our training and testing datasets were 13.4 (10.9) and 14.4 (11.2), respectively. The GPT-2 generative model was the best-performing model with an accuracy of 0.92 (0.91, 0.93, 95% confidence interval [CI]) and R2 score of 0.89 (0.87, 0.90, 95% CI), and all GPT-2-based models outperformed the ClinicalBERT model in terms of exact matching accuracy. Although the ClinicalBERT regression model had the lowest accuracy of 0.27 (0.26, 0.28), it demonstrated a high R2 score of 0.88 (0.85, 0.89), suggesting the ClinicalBERT model can reasonably predict the headache frequency within a range of ≤ ± 3 days, and the R2 score was higher than the GPT-2 QA zero-shot model or GPT-2 QA model few-shot training fine-tuned model.

CONCLUSION

We developed a robust information extraction model based on a state-of-the-art large language model, a GPT-2 generative model that can extract headache frequency from EHR free-text clinical notes with high accuracy and R2 score. It overcame several challenges related to different ways clinicians document headache frequency that were not easily achieved by traditional NLP models. We also showed that GPT-2-based frameworks outperformed ClinicalBERT in terms of accuracy in extracting headache frequency from clinical notes. To facilitate research in the field, we released the GPT-2 generative model and inference code with open-source license of community use in GitHub. Additional fine-tuning of the algorithm might be required when applied to different health-care systems for various clinical use cases.

Brain Structural and Functional Abnormalities Associated with Acute Post-Traumatic Headache: Iron Deposition and Functional Connectivity

Background

The purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs and time since most recent TBI.

Methods

Sixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 10 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons).

Results

The acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* and SCAT symptom severity score in the left posterior cingulate (p = 0.05) and with headache frequency in the left cuneus (p = 0.04).

Conclusions

Iron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Guidelines of the International Headache Society for controlled trials of pharmacological preventive treatment for persistent post-traumatic headache attributed to mild traumatic brain injury

BACKGROUND

Persistent headache attributed to traumatic injury to the head is divided into two subtypes, one attributed to moderate or severe traumatic injury and another attributed to mild traumatic injury (i.e., concussion). The latter is much more prevalent, in part because more than 90% of cases with traumatic brain injury are classified as mild. The pathophysiology of persistent post-traumatic headache is poorly understood and the underlying mechanisms are likely multifactorial. There is currently no approved treatment specifically for persistent post-traumatic headache, and management strategies rely on medications used for migraine or tension-type headache. Therefore, high-quality trials are urgently needed to support clinical decision-making and optimize management strategies. International guidelines can facilitate appropriate trial design and ensure the acquisition of high-quality data evaluating the efficacy, tolerability, and safety of available and novel pharmacological therapies for the preventive treatment of persistent post-traumatic headache.

METHODS

The development of this guideline was based on a literature review of available studies in MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials, along with a review of previously published guidelines for controlled trials of preventive treatment for episodic and chronic migraine. The identified literature was critically appraised, and due to the scarcity of scientific evidence, recommendations were primarily based on the consensus of experts in the field.

OBJECTIVE

To provide guidelines for designing state-of-the-art controlled clinical trials aimed at evaluating the effectiveness of preventive treatments for persistent post-traumatic headache attributed to mild traumatic brain injury.

Comparing the Efficacy and Safety of Galcanezumab Versus Rimegepant for Prevention of Episodic Migraine: Results from a Randomized, Controlled Clinical Trial

INTRODUCTION

There have been no prior trials directly comparing the efficacy of different calcitonin gene-related peptide (CGRP) antagonists for migraine prevention. Reported are the results from the first head-to-head study of two CGRP antagonists, galcanezumab (monoclonal antibody) versus rimegepant (gepant), for the prevention of episodic migraine.

METHODS

In this 3-month, double-blind, double-dummy study, participants were randomized (1:1) to subcutaneous (SC) galcanezumab 120 mg per month (after a 240 mg loading dose) and a placebo oral disintegrating tablet (ODT) every other day (q.o.d.) or to rimegepant 75 mg ODT q.o.d. and a monthly SC placebo. The primary endpoint was the proportion of participants with a ≥ 50% reduction in migraine headache days per month from baseline across the 3-month double-blind treatment period. Key secondary endpoints were overall mean change from baseline in: migraine headache days per month across 3 months and at month 3, 2, and 1; migraine headache days per month with acute migraine medication use; Migraine-Specific Quality of Life Questionnaire Role Function-Restrictive domain score at month 3; and a ≥ 75% and 100% reduction from baseline in migraine headache days per month across 3 months.

RESULTS

Of 580 randomized participants (galcanezumab: 287, rimegepant: 293; mean age: 42 years), 83% were female and 81% Caucasian. Galcanezumab was not superior to rimegepant in achieving a ≥ 50% reduction from baseline in migraine headache days per month (62% versus 61% respectively; P = 0.70). Given the pre-specified multiple testing procedure, key secondary endpoints cannot be considered statistically significant. Overall, treatment-emergent adverse events were reported by 21% of participants, with no significant differences between study intervention groups.

CONCLUSIONS

Galcanezumab was not superior to rimegepant for the primary endpoint; however, both interventions demonstrated efficacy as preventive treatments in participants with episodic migraine. The efficacy and safety profiles observed in galcanezumab-treated participants were consistent with previous studies.

TRIAL REGISTRATION

ClinTrials.gov-NCT05127486 (I5Q-MC-CGBD).

Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images

Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare diseases, which involve high costs, time, and effort for annotation. Unsupervised disease detection methods, such as anomaly detection, can significantly reduce human effort in these scenarios. While anomaly detection typically focuses on learning from images of healthy subjects only, real-world situations often present unannotated datasets with a mixture of healthy and diseased subjects. Recent studies have demonstrated that utilizing such unannotated images can improve unsupervised disease and anomaly detection. However, these methods do not utilize knowledge specific to registered neuroimages, resulting in a subpar performance in neurologic disease detection. To address this limitation, we propose Brainomaly, a GAN-based image-to-image translation method specifically designed for neurologic disease detection. Brainomaly not only offers tailored image-to-image translation suitable for neuroimages but also leverages unannotated mixed images to achieve superior neurologic disease detection. Additionally, we address the issue of model selection for inference without annotated samples by proposing a pseudo-AUC metric, further enhancing Brainomaly's detection performance. Extensive experiments and ablation studies demonstrate that Brainomaly outperforms existing state-of-the-art unsupervised disease and anomaly detection methods by significant margins in Alzheimer's disease detection using a publicly available dataset and headache detection using an institutional dataset. The code is available from https://github.com/mahfuzmohammad/Brainomaly.

Ubrogepant for the treatment of migraine attacks during the prodrome: a phase 3, multicentre, randomised, double-blind, placebo-controlled, crossover trial in the USA

BACKGROUND

Ubrogepant is a calcitonin gene-related peptide (CGRP) receptor antagonist that is approved for acute treatment of migraine. The prodrome is the earliest phase of a migraine attack and is characterised by non-aura symptoms that precede headache onset. The aim of this trial was to evaluate the efficacy, safety, and tolerability of ubrogepant 100 mg compared with placebo for the acute treatment of migraine when administered during the prodrome.

METHODS

This PRODROME trial was a phase 3, multicentre, randomised, double-blind, placebo-controlled, crossover trial of ubrogepant 100 mg conducted at 75 research centres and headache clinics in the USA. Eligible participants were adults aged 18-75 years who had at least a 1-year history of migraine with or without aura and a history of two to eight migraine attacks per month with moderate to severe headache in each of the 3 months before screening. Eligible participants were randomly assigned (1:1) to either receive placebo to treat the first qualifying prodrome event and ubrogepant 100 mg to treat the second qualifying prodrome event or to receive ubrogepant 100 mg to treat the first qualifying prodrome event and placebo to treat the second qualifying prodrome event. An automated interactive web-response system used permuted blocks of four to manage randomisation. All people giving interventions and assessing outcomes were masked to group assignment during the study. People doing data analysis, which occurred after study completion, were not masked to group assignment. During the double-blind treatment period, each participant was instructed to orally take two tablets of the study drug at the onset of each qualifying prodrome event. The primary endpoint was absence of moderate or severe intensity headache within 24 h after study-drug dose; efficacy analyses were conducted with the modified intention-to-treat (mITT) population, defined as all randomly assigned participants with at least one headache assessment within 24 h after taking the study drug during the treatment period. The safety population included all treated participants who took at least one administration of study drug. The trial is registered with ClinicalTrials.gov (NCT04492020).

FINDINGS

Between Aug 21, 2020, and April 19, 2022, 518 participants were randomly assigned to double-blind crossover treatment. The safety population included 480 participants and the mITT population included 477 participants; 421 (88%) of 480 participants were female and 59 (12%) were male. Absence of moderate or severe headache within 24 h after a dose occurred after 190 (46%) of 418 qualifying prodrome events that had been treated with ubrogepant and after 121 (29%) of 423 qualifying prodrome events that had been treated with placebo (odds ratio 2·09, 95% CI 1·63-2·69; p<0·0001). Adverse events that occurred within 48 h after study-drug administration were reported after 77 (17%) of 456 qualifying prodrome events that had been treated with ubrogepant and after 55 (12%) of 462 events that had been treated with placebo.

INTERPRETATION

Ubrogepant was effective and well tolerated for the treatment of migraine attacks when taken during the prodrome.

FUNDING

AbbVie.

Healthcare costs and resource utilization in patients with migraine treated with erenumab: A retrospective, non-interventional study using claims data from the United States

OBJECTIVE

To assess healthcare costs and healthcare resource utilization (HCRU) among adult patients who newly initiated erenumab in the United States.

METHODS

This retrospective, non-interventional analysis included adult patients (aged ≥18 years) newly initiating erenumab and who had three consecutive monthly claims for erenumab (11/1/2017-9/1/2019) from the Komodo Health database. Outcomes included migraine-related and all-cause costs, use of other preventive/acute migraine medications, and HCRU. All outcomes were compared during the 180-day pre- versus the 180-day post-index periods. Cost outcomes were also assessed for longer periods including post-index Days 91-270 and monthly mean post-index costs for the longest time of continuous insurance enrollment.

RESULTS

Overall, 1839 patients with migraine were included for analysis. Compared to the 180-day pre-index period, an increase in total migraine-related costs (+$2639; p < 0.0001), migraine-related prescription costs (+$3435, p < 0.0001), all-cause total costs (+$2977; p < 0.001), and all-cause prescription costs (+$4102; p < 0.0001) were observed during the 180-day post-index period after adjusting for covariates. Conversely, reduction in migraine-related medical costs (-$896; p < 0.0001), and significantly lower odds of migraine-related emergency room visits (odds ratio [OR] 0.60, 95% confidence interval [CI] 0.44-0.82; p = 0.001), migraine-related office visits (OR 0.58, 95% CI 0.53-0.64; p < 0.0001), and migraine-related neurologist visits (OR 0.69, 95% CI 0.63-0.75; p < 0.0001) were observed during the 180-days post-index period. There were significant decreases in the odds of having overall preventive migraine medications (OR 0.81, 95% CI 0.75-0.87; p < 0.0001), acute-migraine medications (OR 0.92, 95% CI 0.85-1.00; p = 0.038), and triptan (OR 0.79, 95% CI 0.73-0.85; p < 0.0001) during the 180-day post-index period. Sensitivity analyses on cost outcomes found no statistically significant differences in pre-index migraine-related costs compared to post-index migraine-related costs when assessing longer post-index follow-up periods.

CONCLUSION

Initiation of therapy with a novel treatment is often associated with an increase in overall healthcare costs due to the entrance costs associated with novel therapy. For a chronic condition such as migraine, cost versus health benefits should be evaluated over a long period (e.g., ≥2 years) to better understand the true benefits of therapy. Data from this study suggest that the entrance cost for erenumab, the primary driver of the high post-index prescription costs gets mitigated by reduced medical costs over long-term follow-up. The results indicate better disease management in adult patients with migraine, which should be an important consideration for both patients and payors, as these findings have shown an offset between migraine-related prescription and medical costs.

Identification of brain areas in mice with peak neural activity across the acute and persistent phases of post-traumatic headache

BACKGROUND

Post-traumatic headache is very common after a mild traumatic brain injury. Post-traumatic headache may persist for months to years after an injury in a substantial proportion of people. The pathophysiology underlying post-traumatic headache remains unknown but is likely distinct from other headache disorders. Identification of brain areas activated in acute and persistent phases of post-traumatic headache can provide insights into the underlying circuits mediating headache pain. We used an animal model of mild traumatic brain injury-induced post-traumatic headache and c-fos immunohistochemistry to identify brain regions with peak activity levels across the acute and persistent phases of post-traumatic headache.

METHODS

Male and female C57BL/6 J mice were briefly anesthetized and subjected to a sham procedure or a weight drop closed-head mild traumatic brain injury . Cutaneous allodynia was assessed in the periorbital and hindpaw regions using von Frey filaments. Immunohistochemical c-fos based neural activity mapping was then performed on sections from whole brain across the development of post-traumatic headache (i.e. peak of the acute phase at 2 days post- mild traumatic brain injury), start of the persistent phase (i.e. >14 days post-mild traumatic brain injury) or after provocation with stress (bright light). Brain areas with consistent and peak levels of c-fos expression across mild traumatic brain injury induced post-traumatic headache were identified and included for further analysis.

RESULTS

Following mild traumatic brain injury, periorbital and hindpaw allodynia was observed in both male and female mice. This allodynia was transient and subsided within the first 14 days post-mild traumatic brain injury and is representative of acute post-traumatic headache. After this acute post-traumatic headache phase, exposure of mild traumatic brain injury mice to a bright light stress reinstated periorbital and hindpaw allodynia for several hours - indicative of the development of persistent post-traumatic headache. Acute post-traumatic headache was coincident with an increase in neuronal c-fos labeling in the spinal nucleus of the trigeminal caudalis, primary somatosensory cortex, and the nucleus accumbens. Neuronal activation returned to baseline levels by the persistent post-traumatic headache phase in the spinal nucleus of the trigeminal caudalis and primary somatosensory cortex but remained elevated in the nucleus accumbens. In the persistent post-traumatic headache phase, coincident with allodynia observed following bright light stress, we observed bright light stress-induced c-fos neural activation in the spinal nucleus of the trigeminal caudalis, primary somatosensory cortex, and nucleus accumbens.

CONCLUSION

Examination of mild traumatic brain injury-induced changes in peak c-fos expression revealed brain regions with significantly increased neural activity across the acute and persistent phases of post-traumatic headache. Our findings suggest mild traumatic brain injury-induced post-traumatic headache produces neural activation along pain relevant pathways at time-points matching post-traumatic headache-like pain behaviors. These observations suggest that the spinal nucleus of the trigeminal caudalis, primary somatosensory cortex, and nucleus accumbens may contribute to both the induction and maintenance of post-traumatic headache.

Rethinking headache as a global public health case model for reaching the SDG 3 HEALTH by 2030

The 2030 Agenda for Sustainable Development sets out, through 17 Sustainable Development Goals (SDGs), a path for the prosperity of people and the planet. SDG 3 in particular aims to ensure healthy lives and promote well-being for all at all ages and includes several targets to enhance health. This review presents a "headache-tailored" perspective on how to achieve SDG 3 by focusing on six specific actions: targeting chronic headaches; reducing the overuse of acute pain-relieving medications; promoting the education of healthcare professionals; granting access to medication in low- and middle-income countries (LMIC); implementing training and educational opportunities for healthcare professionals in low and middle income countries; building a global alliance against headache disorders. Addressing the burden of headache disorders directly impacts on populations' health, as well as on the possibility to improve the productivity of people aged below 50, women in particular. Our analysis pointed out several elements, and included: moving forward from frequency-based parameters to define headache severity; recognizing and managing comorbid diseases and risk factors; implementing a disease management multi-modal management model that incorporates pharmacological and non-pharmacological treatments; early recognizing and managing the overuse of acute pain-relieving medications; promoting undergraduate, postgraduate, and continuing medical education of healthcare professionals with specific training on headache; and promoting a culture that favors the recognition of headaches as diseases with a neurobiological basis, where this is not yet recognized. Making headache care more sustainable is an achievable objective, which will require multi-stakeholder collaborations across all sectors of society, both health-related and not health-related. Robust investments will be needed; however, considering the high prevalence of headache disorders and the associated disability, these investments will surely improve multiple health outcomes and lift development and well-being globally.

A Large Language Model-Based Generative Natural Language Processing Framework Finetuned on Clinical Notes Accurately Extracts Headache Frequency from Electronic Health Records

Background

Headache frequency, defined as the number of days with any headache in a month (or four weeks), remains a key parameter in the evaluation of treatment response to migraine preventive medications. However, due to the variations and inconsistencies in documentation by clinicians, significant challenges exist to accurately extract headache frequency from the electronic health record (EHR) by traditional natural language processing (NLP) algorithms.

Methods

This was a retrospective cross-sectional study with human subjects identified from three tertiary headache referral centers- Mayo Clinic Arizona, Florida, and Rochester. All neurology consultation notes written by more than 10 headache specialists between 2012 to 2022 were extracted and 1915 notes were used for model fine-tuning (90%) and testing (10%). We employed four different NLP frameworks: (1) ClinicalBERT (Bidirectional Encoder Representations from Transformers) regression model (2) Generative Pre-Trained Transformer-2 (GPT-2) Question Answering (QA) Model zero-shot (3) GPT-2 QA model few-shot training fine-tuned on Mayo Clinic notes; and (4) GPT-2 generative model few-shot training fine-tuned on Mayo Clinic notes to generate the answer by considering the context of included text.

Results

The GPT-2 generative model was the best-performing model with an accuracy of 0.92[0.91 - 0.93] and R2 score of 0.89[0.87, 0.9], and all GPT2-based models outperformed the ClinicalBERT model in terms of the exact matching accuracy. Although the ClinicalBERT regression model had the lowest accuracy 0.27[0.26 - 0.28], it demonstrated a high R2 score 0.88[0.85, 0.89], suggesting the ClinicalBERT model can reasonably predict the headache frequency within a range of ≤ ± 3 days, and the R2 score was higher than the GPT-2 QA zero-shot model or GPT-2 QA model few-shot training fine-tuned model.

Conclusion

We developed a robust model based on a state-of-the-art large language model (LLM)- a GPT-2 generative model that can extract headache frequency from EHR free-text clinical notes with high accuracy and R2 score. It overcame several challenges related to different ways clinicians document headache frequency that were not easily achieved by traditional NLP models. We also showed that GPT2-based frameworks outperformed ClinicalBERT in terms of accuracy in extracting headache frequency from clinical notes. To facilitate research in the field, we released the GPT-2 generative model and inference code with open-source license of community use in GitHub.

Real-world persistence and costs among patients with chronic migraine treated with onabotulinumtoxinA or calcitonin gene-related peptide monoclonal antibodies

BACKGROUND: Chronic migraine (CM) is a common neurologic disorder that imposes substantial burden on payers, patients, and society. Low rates of persistence to oral migraine preventive medications have been previously documented; however, less is known about persistence and costs associated with innovative nonoral migraine preventive medications. OBJECTIVE: To evaluate real-world persistence and costs among adults with CM treated with onabotulinumtoxinA (onabotA) or calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs). METHODS: This was a retrospective, longitudinal, observational study analyzing the IBM MarketScan Commercial and Medicare databases. The study sample included adults with CM initiating treatment with either onabotA or a CGRP mAb on or after January 1, 2018. Persistence and costs over 12 months after treatment initiation were evaluated using chi-square and Student's t-tests. Persistence to onabotA was compared with CGRP mAbs as a weighted average of the class and by individual CGRP mAbs. Mean pharmacy (acute and preventive), medical (inpatient, emergency department, and outpatient), and total costs are reported. Multivariate regression analyses were conducted to generate adjusted estimates of persistence and costs after controlling for potential confounders (age, sex, region, insurance type, number of baseline comorbidities, Charlson Comorbidity Index, and number of previously used oral migraine preventive medications). RESULTS: Of 66,303 individuals with onabotA or CGRP mAb claims, 2,697 with CM met the inclusion/exclusion criteria. In the total population, individuals were primarily female (85.5%), lived in the South (48.5%), and had a mean (SD) age of 44 (12) years, which was consistent across the onabotA and CGRP mAb cohorts. Common comorbid conditions included anxiety (23.9%), depression (18.2%), hypertension (16.5%), and sleep disorders (16.9%). After adjusting for potential confounding variables, persistence to onabotA during the 12-month follow-up period was 40.7% vs 27.8% for CGRP mAbs (odds ratio [OR] = 0.683; 95% CI = 0.604-0.768; P < 0.0001). Persistence to erenumab, fremanezumab, and galcanezumab was 25.5% (OR = 0.627; 95% CI = 0.541-0.722; P < 0.0001), 30.3% (OR = 0.746; 95% CI = 0.598-0.912; P = 0.0033), and 33.7% (OR = 0.828; 95% CI = 0.667-1.006; P = 0.058). All-cause ($18,292 vs $18,275; P = 0.9739) and migraine-related ($8,990 vs $9,341; P = 0.1374) costs were comparable between the onabotA and CGRP mAb groups. CONCLUSIONS: Among adults with CM receiving onabotA and CGRP mAbs, individuals initiating onabotA treatment had higher persistence compared with those receiving CGRP mAbs. Total all-cause and migraine-related costs over 12 months were comparable between those receiving onabotA and CGRP mAbs. DISCLOSURES: This study was sponsored by Allergan (prior to its acquisition by AbbVie), they contributed to the design and interpretation of data and the writing, reviewing, and approval of final version. Writing and editorial assistance was provided to the authors by Dennis Stancavish, MS, of Peloton Advantage, LLC, an OPEN Health company, Parsippany, NJ, and was funded by AbbVie. The opinions expressed in this article are those of the authors. The authors received no honorarium/fee or other form of financial support related to the development of this article. Dr Schwedt serves on the Board of Directors for the American Headache Society and the American Migraine Foundation. Within the prior 12 months he has received research support from Amgen, Henry Jackson Foundation, Mayo Clinic, National Institutes of Health, Patient-Centered Outcomes Research Institute, SPARK Neuro, and US Department of Defense. Within the past 12 months, he has received personal compensation for serving as a consultant or advisory board member for AbbVie, Allergan, Axsome, BioDelivery Science, Biohaven, Collegium, Eli Lilly, Ipsen, Linpharma, Lundbeck, and Satsuma. He holds stock options in Aural Analytics and Nocira. He has received royalties from UpToDate. Dr Lee and Ms Shah are employees of AbbVie and may hold AbbVie stock. Dr Gillard was an employee of AbbVie and may hold AbbVie stock. Dr Knievel has served as a consultant for AbbVie, Amgen, Eli Lilly, and Biohaven; conducted research for AbbVie, Amgen, and Eli Lilly; and is on speaker programs for AbbVie and Amgen. Dr McVige has served as a speaker and/or received research support from Allergan (now AbbVie Inc.), Alder, Amgen/Novartis, Avanir, Biohaven, Eli Lilly, Lundbeck, and Teva. Ms Wang and Ms Wu are employees of Genesis Research, which provides consulting services to AbbVie. Dr Blumenfeld, within the past 12 months, has served on advisory boards for Allergan, AbbVie, Aeon, Alder, Amgen, Axsome, BDSI, Biohaven, Impel, Lundbeck, Lilly, Novartis, Revance, Teva, Theranica, and Zosano; as a speaker for Allergan, AbbVie, Amgen, BDSI, Biohaven, Lundbeck, Lilly, and Teva; as a consultant for Allergan, AbbVie, Alder, Amgen, Biohaven, Lilly, Lundbeck, Novartis, Teva, and Theranica; and as a contributing author for Allergan, AbbVie, Amgen, Biohaven, Novartis, Lilly, and Teva. He has received grant support from AbbVie and Amgen. AbbVie is committed to responsible data sharing regarding the clinical trials we sponsor. This includes access to anonymized, individual, and trial-level data (analysis data sets), as well as other information (eg, protocols, clinical study reports, or analysis plans), as long as the trials are not part of an ongoing or planned regulatory submission. This includes requests for clinical trial data for unlicensed products and indications. These clinical trial data can be requested by any qualified researchers who engage in rigorous, independent scientific research, and will be provided following review and approval of a research proposal and Statistical Analysis Plan and execution of a Data Sharing Agreement. Data requests can be submitted at any time after approval in the United States and Europe and after acceptance of this manuscript for publication. The data will be accessible for 12 months, with possible extensions considered. For more information on the process, or to submit a request, visit the following link: https://www.abbvieclinicaltrials.com/hcp/data-sharing/.

Prevalence of and Risk Factors for Post-traumatic Headache in Civilian Patients After Mild Traumatic Brain Injury: A TRACK-TBI Study

OBJECTIVE

To ascertain the prevalence of and risk factors for post-traumatic headache (PTH) attributed to mild traumatic brain injury (mTBI).

PATIENTS AND METHODS

A prospective, longitudinal, multicenter cohort study of patients with mTBI and orthopedic trauma controls who were enrolled from February 26, 2014, to August 8, 2018. The baseline assessment was conducted as soon as possible following evaluation at the emergency department. Follow-ups were scheduled at 2 weeks, 3 months, 6 months, and 12 months postinjury. Eligible patients with mTBI included those 18 years of age or older who presented to the emergency department within 24 hours of head injury warranting evaluation by noncontrast head computed tomography scan. Acute PTH was considered present when a patient reported a headache score of greater than or equal to 2 on the Rivermead Post-concussion Questionnaire at 2 weeks postinjury (ie, headache is at least a mild problem compared with pre-injury). Persistent PTH was defined when a patient with acute PTH reported a Rivermead Post-concussion Questionnaire headache score of greater than or equal to 2 at the scheduled follow-up examinations.

RESULTS

Acute PTH was reported by 963 (60.4%) of 1594 patients with mTBI at 2 weeks postinjury. Among those with acute PTH, 439 (52.4%) of 837 patients reported persistent PTH at 3 months postinjury. This figure decreased over time and 278 (37.5%) of 742 patients continued to report persistent PTH at 6 months, whereas 187 (28.9%) of 646 patients did so as well at 12 months postinjury. Risk factors for acute PTH included younger age, female sex, fewer years of formal education, computed tomography-positive scans, alteration of consciousness, psychiatric history, and history of migraine. Risk factors for persistent PTH included female sex, fewer years of formal education, and history of migraine.

CONCLUSION

Post-traumatic headache is a prevalent sequela of mTBI that persists for at least 12 months in a considerable proportion of affected individuals. The attributable burden necessitates better patient follow-up, disease characterization, improved awareness of PTH in clinical practice, and identification of effective therapies.

Sensory hypersensitivities are associated with post-traumatic headache-related disability

OBJECTIVE

To examine whether sensory hypersensitivity contributes to headache-related disability in a secondary analysis of patients with post-traumatic headache.

BACKGROUND

Up to one-third of individuals with traumatic brain injuries report persistent headache 3 months post-injury. High rates of allodynia and photophobia have been observed in clinical studies and animal models of post-traumatic headache, but we do not fully understand how sensory amplifications impact post-traumatic headache-related disability.

METHODS

We identified a cross-sectional sample of patients from the American Registry for Migraine Research database with new or worsening headaches post-head injury from 2016 to 2020 and performed a secondary analysis of those data. We modeled the relationship between sensory sensitivity and Migraine Disability Assessment scores using questionnaires. Candidate variables included data collection features (study site and year), headache-related and general clinical features (headache frequency, migraine diagnosis, abuse history, sex, age, cognitive and affective symptom scores), and sensory symptoms (related to light, sound, and touch sensitivity).

RESULTS

The final sample included 193 patients (median age 46, IQR 22; 161/193, 83.4% female). Migraine Disability Assessment scores ranged from 0 to 260 (median 47, IQR 87). The final model included allodynia, hyperacusis, photosensitivity, headache days per month, abuse history, anxiety and depression, cognitive dysfunction, and age (R2  = 0.43). An increase of one point in allodynia score corresponded to a 3% increase in headache disability (95% CI: 0%-7%; p = 0.027), an increase of one-tenth of a point in the photosensitivity score corresponded to a 12% increase (95% CI: 3%-25%; p = 0.002), and an increase of one point in the hyperacusis score corresponded to a 2% increase (95% CI: 0%-4%; p = 0.016).

CONCLUSIONS

Increased photosensitivity, allodynia, and hyperacusis were associated with increased headache-related disability in this sample of patients with post-traumatic headache. Symptoms of sensory amplification likely contribute to post-traumatic headache-related disability and merit an ongoing investigation into their potential as disease markers and treatment targets.

Harmonizing Healthy Cohorts to Support Multicenter Studies on Migraine Classification using Brain MRI Data

Multicenter and multi-scanner imaging studies might be needed to provide sample sizes large enough for developing accurate predictive models. However, multicenter studies, which likely include confounding factors due to subtle differences in research participant characteristics, MRI scanners, and imaging acquisition protocols, might not yield generalizable machine learning models, that is, models developed using one dataset may not be applicable to a different dataset. The generalizability of classification models is key for multi-scanner and multicenter studies, and for providing reproducible results. This study developed a data harmonization strategy to identify healthy controls with similar (homogenous) characteristics from multicenter studies to validate the generalization of machine-learning techniques for classifying individual migraine patients and healthy controls using brain MRI data. The Maximum Mean Discrepancy (MMD) was used to compare the two datasets represented in Geodesic Flow Kernel (GFK) space, capturing the data variabilities for identifying a "healthy core". A set of homogeneous healthy controls can assist in overcoming some of the unwanted heterogeneity and allow for the development of classification models that have high accuracy when applied to new datasets. Extensive experimental results show the utilization of a healthy core. One dataset consists of 120 individuals (66 with migraine and 54 healthy controls) and another dataset consists of 76 (34 with migraine and 42 healthy controls) individuals. A homogeneous dataset derived from a cohort of healthy controls improves the performance of classification models by about 25% accuracy improvements for both episodic and chronic migraineurs.

Generalizable Natural Language Processing Framework for Migraine Reporting from Social Media

Migraine is a highly prevalent and disabling neurological disorder. However, information about migraine management in real-world settings is limited to traditional health information sources. In this paper, we (i) verify that there is substantial migraine-related chatter available on social media (Twitter and Reddit), self-reported by those with migraine; (ii) develop a platform-independent text classification system for automatically detecting self-reported migraine-related posts, and (iii) conduct analyses of the self-reported posts to assess the utility of social media for studying this problem. We manually annotated 5750 Twitter posts and 302 Reddit posts, and used them for training and evaluating supervised machine learning methods. Our best system achieved an F₁ score of 0.90 on Twitter and 0.93 on Reddit. Analysis of information posted by our 'migraine cohort' revealed the presence of a plethora of relevant information about migraine therapies and sentiments associated with them. Our study forms the foundation for conducting an in-depth analysis of migraine-related information using social media data.

Questionnaire and structural imaging data accurately predict headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury

BACKGROUND

Our prior work demonstrated that questionnaires assessing psychosocial symptoms have utility for predicting improvement in patients with acute post-traumatic headache following mild traumatic brain injury. In this cohort study, we aimed to determine whether prediction accuracy can be refined by adding structural magnetic resonance imaging (MRI) brain measures to the model.

METHODS

Adults with acute post-traumatic headache (enrolled 0-59 days post-mild traumatic brain injury) underwent T1-weighted brain MRI and completed three questionnaires (Sports Concussion Assessment Tool, Pain Catastrophizing Scale, and the Trait Anxiety Inventory Scale). Individuals with post-traumatic headache completed an electronic headache diary allowing for determination of headache improvement at three- and at six-month follow-up. Questionnaire and MRI measures were used to train prediction models of headache improvement and headache trajectory.

RESULTS

Forty-three patients with post-traumatic headache (mean age = 43.0, SD = 12.4; 27 females/16 males) and 61 healthy controls were enrolled (mean age = 39.1, SD = 12.8; 39 females/22 males). The best model achieved cross-validation Area Under the Curve of 0.801 and 0.805 for predicting headache improvement at three and at six months. The top contributing MRI features for the prediction included curvature and thickness of superior, middle, and inferior temporal, fusiform, inferior parietal, and lateral occipital regions. Patients with post-traumatic headache who did not improve by three months had less thickness and higher curvature measures and notably greater baseline differences in brain structure vs. healthy controls (thickness: p < 0.001, curvature: p = 0.012) than those who had headache improvement.

CONCLUSIONS

A model including clinical questionnaire data and measures of brain structure accurately predicted headache improvement in patients with post-traumatic headache and achieved improvement compared to a model developed using questionnaire data alone.

Patient preferences for attributes of injected or infused preventive migraine medications: Findings from a discrete choice experiment

OBJECTIVE

To assess preferences among adults with migraine for differentiating attributes of injected or infused preventive treatment options and evaluate their importance in determining a treatment choice.

BACKGROUND

Adults with migraine and health-care providers consider many factors when making treatment decisions. Injected or infused preventive migraine treatment options differ in several attributes, including mode of administration and dosing frequency, which may be preferentially selected or avoided by patients. Understanding a patient's preference is important for clinicians as they advise on various treatment options.

METHODS

A total of 604 US adults diagnosed with migraine participated in an online survey that captured information on demographics, migraine history, and treatment preferences. A discrete choice experiment (DCE) was used to evaluate participants' preferences for specific attributes of injected/infused preventive migraine therapies. The DCE data were utilized to estimate attribute importance (expressed as a percentage) and identify subgroups that had different distributions of preferences.

RESULTS

In the overall migraine population, mode of administration (28.8%), durability of effectiveness (27.0%), and speed of onset (25.5%) had the highest relative importance, whereas administration setting (9.9%) and dosing frequency (8.8%) had the lowest. Four distinct subgroups were identified: Group 1 (n = 128) preferred self-injection administration and durability of effectiveness; Group 2 (n = 189) expressed aversion to cranial injections; Group 3 (n = 158) prioritized rapid speed of onset; and Group 4 (n = 129) favored health-care provider administration and durability of effectiveness.

CONCLUSIONS

Speed of onset, durability of effectiveness, and mode of administration are key moderators of treatment preference among US adults with migraine. Certain segments of the migraine population prioritize specific treatment attributes over others, with intravenous infusion not considered a barrier in three of four identified segments. Clinicians can best help their patients find the right medication if they understand which medication attributes are most and least important to them.

Longitudinal differences in iron deposition in periaqueductal gray matter and anterior cingulate cortex are associated with response to erenumab in migraine

OBJECTIVES

The objective of this longitudinal study was to determine whether brain iron accumulation, measured using magnetic resonance imaging magnetic transverse relaxation rates (T2*), is associated with response to erenumab for the treatment of migraine.

METHODS

Participants (n = 28) with migraine, diagnosed using international classification of headache disorders 3rd edition criteria, were eligible if they had six to 25 migraine days during a four-week headache diary run-in phase. Participants received two treatments with 140 mg erenumab, one immediately following the pre-treatment run-in phase and a second treatment four weeks later. T2* data were collected immediately following the pre-treatment phase, and at two weeks and eight weeks following the first erenumab treatment. Patients were classified as erenumab responders if their migraine-day frequency at five-to-eight weeks post-initial treatment was reduced by at least 50% compared to the pre-treatment run-in phase. A longitudinal Sandwich estimator approach was used to compare longitudinal group differences (responders vs non-responders) in T2* values, associated with iron accumulation. Group visit effects were calculated with a significance threshold of p = 0.005 and cluster forming threshold of 250 voxels. T2* values of 19 healthy controls were used for a reference. The average of each significant region was compared between groups and visits with Bonferroni corrections for multiple comparisons with significance defined as p < 0.05.

RESULTS

Pre- and post-treatment longitudinal imaging data were available from 28 participants with migraine for a total of 79 quantitative T2* images. Average subject age was 42 ± 13 years (25 female, three male). Of the 28 subjects studied, 53.6% were erenumab responders. Comparing longitudinal T2* between erenumab responders vs non-responders yielded two comparisons which survived the significance threshold of p < 0.05 after correction for multiple comparisons: the difference at eight weeks between the erenumab-responders and non-responders in the periaqueductal gray (mean ± standard error; responders 43 ± 1 ms vs non-responders 32.5 ± 1 ms, p = 0.002) and the anterior cingulate cortex (mean ± standard error; responders 50 ± 1 ms vs non-responders 40 ± 1 ms, p = 0.01).

CONCLUSIONS

Erenumab response is associated with higher T2* in the periaqueductal gray and anterior cingulate cortex, regions that participate in pain processing and modulation. T2* differences between erenumab responders vs non-responders, a measure of brain iron accumulation, are seen at eight weeks post-treatment. Less iron accumulation in the periaqueductal gray and anterior cingulate cortex might play a role in the therapeutic mechanisms of migraine reduction associated with erenumab.

The value of brain MRI functional connectivity data in a machine learning classifier for distinguishing migraine from persistent post-traumatic headache

Background

Post-traumatic headache (PTH) and migraine often have similar phenotypes. The objective of this exploratory study was to develop classification models to differentiate persistent PTH (PPTH) from migraine using clinical data and magnetic resonance imaging (MRI) measures of brain structure and functional connectivity (fc).

Methods

Thirty-four individuals with migraine and 48 individuals with PPTH attributed to mild TBI were included. All individuals completed questionnaires assessing headache characteristics, mood, sensory hypersensitivities, and cognitive function and underwent brain structural and functional imaging during the same study visit. Clinical features, structural and functional resting-state measures were included as potential variables. Classifiers using ridge logistic regression of principal components were fit on the data. Average accuracy was calculated using leave-one-out cross-validation. Models were fit with and without fc data. The importance of specific variables to the classifier were examined.

Results

With internal variable selection and principal components creation the average accuracy was 72% with fc data and 63.4% without fc data. This classifier with fc data identified individuals with PPTH and individuals with migraine with equal accuracy.

Conclusion

Multivariate models based on clinical characteristics, fc, and brain structural data accurately classify and differentiate PPTH vs. migraine suggesting differences in the neuromechanism and clinical features underlying both headache disorders.

Thalamic subfield iron accumulation after acute mild traumatic brain injury as a marker of future post-traumatic headache intensity

OBJECTIVE

To explore alterations in thalamic subfield volume and iron accumulation in individuals with post-traumatic headache (PTH) relative to healthy controls.

BACKGROUND

The thalamus plays a pivotal role in the pathomechanism of pain and headache, yet the role of the thalamus in PTH attributed to mild traumatic brain injury (mTBI) remains unclear.

METHODS

A total of 107 participants underwent multimodal T1-weighted and T2* brain magnetic resonance imaging. Using a clinic-based observational study, thalamic subfield volume and thalamic iron accumulation were explored in 52 individuals with acute PTH (mean age = 41.3; standard deviation [SD] = 13.5), imaged on average 24 days post mTBI, and compared to 55 healthy controls (mean age = 38.3; SD = 11.7) without history of mTBI or migraine. Symptoms of mTBI and headache characteristics were assessed at baseline (0-59 days post mTBI) (n = 52) and 3 months later (n = 46) using the Symptom Evaluation of the Sports Concussion Assessment Tool (SCAT-5) and a detailed headache history questionnaire.

RESULTS

Relative to controls, individuals with acute PTH had significantly less volume in the lateral geniculate nucleus (LGN) (mean volume: PTH = 254.1, SD = 43.4 vs. controls = 278.2, SD = 39.8; p = 0.003) as well as more iron deposition in the left LGN (PTH: T2* signal = 38.6, SD = 6.5 vs. controls: T2* signal = 45.3, SD = 2.3; p = 0.048). Correlations in individuals with PTH revealed a positive relationship between left LGN T2* iron deposition and SCAT-5 symptom severity score at baseline (r = -0.29, p = 0.019) and maximum headache intensity at the 3-month follow-up (r = -0.47, p = 0.002).

CONCLUSION

Relative to healthy controls, individuals with acute PTH had less volume and higher iron deposition in the left LGN. Higher iron deposition in the left LGN might reflect mTBI severity and poor headache recovery.

Headache classification and automatic biomarker extraction from structural MRIs using deep learning

Data-driven machine-learning methods on neuroimaging (e.g. MRI) are of great interest for the investigation and classification of neurological diseases. However, traditional machine learning requires domain knowledge to delineate the brain regions first, followed by feature extraction from the regions. Compared with this semi-automated approach, recently developed deep learning methods have advantages since they do not require such prior knowledge; instead, deep learning methods can automatically find features that differentiate MRIs from different cohorts. In the present study, we developed a deep learning-based classification pipeline distinguishing brain MRIs of individuals with one of three types of headaches [migraine (n = 95), acute post-traumatic headache (n = 48) and persistent post-traumatic headache (n = 49)] from those of healthy controls (n = 532) and identified the brain regions that most contributed to each classification task. Our pipeline included: (i) data preprocessing; (ii) binary classification of healthy controls versus headache type using a 3D ResNet-18; and (iii) biomarker extraction from the trained 3D ResNet-18. During the classification at the second step of our pipeline, we resolved two common issues in deep learning methods, limited training data and imbalanced samples from different categories, by incorporating a large public data set and resampling among the headache cohorts. Our method achieved the following classification accuracies when tested on independent test sets: (i) migraine versus healthy controls-75% accuracy, 66.7% sensitivity and 83.3% specificity; (2) acute post-traumatic headache versus healthy controls-75% accuracy, 66.7% sensitivity and 83.3% specificity; and (3) persistent post-traumatic headache versus healthy controls-91.7% accuracy, 100% sensitivity and 83.3% specificity. The most significant biomarkers identified by the classifier for migraine were caudate, caudal anterior cingulate, superior frontal, thalamus and ventral diencephalon. For acute post-traumatic headache, lateral occipital, cuneus, lingual, pericalcarine and superior parietal regions were identified as most significant biomarkers. Finally, for persistent post-traumatic headache, the most significant biomarkers were cerebellum, middle temporal, inferior temporal, inferior parietal and superior parietal. In conclusion, our study shows that the deep learning methods can automatically detect aberrations in the brain regions associated with different headache types. It does not require any human knowledge as input which significantly reduces human effort. It uncovers the great potential of deep learning methods for classification and automatic extraction of brain imaging-based biomarkers for these headache types.

Developing multivariable models for predicting headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury: A preliminary study

OBJECTIVES/BACKGROUND

Post-traumatic headache (PTH) is a common symptom after mild traumatic brain injury (mTBI). Although there have been several studies that have used clinical features of PTH to attempt to predict headache recovery, currently no accurate methods exist for predicting individuals' improvement from acute PTH. This study investigated the utility of clinical questionnaires for predicting (i) headache improvement at 3 and 6 months, and (ii) headache trajectories over the first 3 months.

METHODS

We conducted a clinic-based observational longitudinal study of patients with acute PTH who completed a battery of clinical questionnaires within 0-59 days post-mTBI. The battery included headache history, symptom evaluation, cognitive tests, psychological tests, and scales assessing photosensitivity, hyperacusis, insomnia, cutaneous allodynia, and substance use. Each participant completed a web-based headache diary, which was used to determine headache improvement.

RESULTS

Thirty-seven participants with acute PTH (mean age = 42.7, standard deviation [SD] = 12.0; 25 females/12 males) completed questionnaires at an average of 21.7 (SD = 13.1) days post-mTBI. The classification of headache improvement or non-improvement at 3 and 6 months achieved cross-validation area under the curve (AUC) of 0.72 (95% confidence interval [CI] 0.55 to 0.89) and 0.84 (95% CI 0.66 to 1.00). Sub-models trained using only the top five features still achieved 0.72 (95% CI 0.55 to 0.90) and 0.77 (95% CI 0.52 to 1.00) AUC. The top five contributing features were from three questionnaires: Pain Catastrophizing Scale total score and helplessness sub-domain score; Sports Concussion Assessment Tool Symptom Evaluation total score and number of symptoms; and the State-Trait Anxiety Inventory score. The functional regression model achieved R = 0.64 for modeling headache trajectory over the first 3 months.

CONCLUSION

Questionnaires completed following mTBI have good utility for predicting headache improvement at 3 and 6 months in the future as well as the evolving headache trajectory. Reducing the battery to only three questionnaires, which assess post-concussive symptom load and biopsychosocialecologic factors, was helpful to determine a reasonable prediction accuracy for headache improvement.

Longitudinal changes in functional connectivity and pain-induced brain activations in patients with migraine: a functional MRI study pre- and post- treatment with Erenumab

Abstract

Background

Migraine involves central and peripheral nervous system mechanisms. Erenumab, an anti-calcitonin gene-related peptide (CGRP) receptor monoclonal antibody with little central nervous system penetrance, is effective for migraine prevention. The objective of this study was to determine if response to erenumab is associated with alterations in brain functional connectivity and pain-induced brain activations.

Methods

Adults with 6–25 migraine days per month during a 4-week headache diary run-in phase underwent pre-treatment brain functional MRI (fMRI) that included resting-state functional connectivity and BOLD measurements in response to moderately painful heat stimulation to the forearm. This was followed by two treatments with 140 mg erenumab, at baseline and 4 weeks later. Post-treatment fMRI was performed 2 weeks and 8 weeks following the first erenumab treatment. A longitudinal Sandwich estimator analysis was used to identify pre- to post-treatment changes in resting-state functional connectivity and brain activations in response to thermal pain. fMRI findings were compared between erenumab treatment-responders vs. erenumab non-responders.

Results

Pre- and post-treatment longitudinal imaging data were available from 32 participants. Average age was 40.3 (+/− 13) years and 29 were female. Pre-treatment average migraine day frequency was 13.8 (+/− 4.7) / 28 days and average headache day frequency was 15.8 (+/− 4.4) / 28 days. Eighteen of 32 (56%) were erenumab responders. Compared to erenumab non-responders, erenumab responders had post-treatment differences in 1) network functional connectivity amongst pain-processing regions, including higher global efficiency, clustering coefficient, node degree, regional efficiency, and modularity, 2) region-to-region functional connectivity between several regions including temporal pole, supramarginal gyrus, and hypothalamus, and 3) pain-induced activations in the middle cingulate, posterior cingulate, and periaqueductal gray matter.

Conclusions

Reductions in migraine day frequency accompanying erenumab treatment are associated with changes in resting state functional connectivity and central processing of extracranial painful stimuli that differ from erenumab non-responders.

Trial registration

clinicaltrials.gov (NCT03773562).

Guidelines of the International Headache Society for Clinic-Based Headache Registries, 1st edition

Clinic-based headache registries collect data for a wide variety of purposes including delineating disease characteristics, longitudinal natural disease courses, headache management approaches, quality of care, treatment safety and effectiveness, factors that predict treatment response, health care resource utilization, clinician adherence to guidelines, and cost-effectiveness. Registry data are valuable for numerous stakeholders, including individuals with headache disorders and their caregivers, healthcare providers, scientists, healthcare systems, regulatory authorities, pharmaceutical companies, employers, and policymakers. This International Headache Society document may serve as guidance for developing clinic-based headache registries. Use of registry data requires a formal research protocol that includes: 1) research aims; 2) methods for data collection, harmonization, analysis, privacy, and protection; 3) methods for human subject protection; and 4) publication and dissemination plans. Depending upon their objectives, headache registries should include validated headache-specific questionnaires, patient reported outcome measures, data elements that are used consistently across studies (i.e., "common data elements"), and medical record data. Amongst other data types, registries may be linked to healthcare and pharmacy claims data, biospecimens, and neuroimaging data. Headache diagnoses should be made according to the International Classification of Headache Disorders diagnostic criteria. The data from well-designed headache registries can provide wide-ranging and novel insights into the characteristics, burden, and treatment of headache disorders and ultimately lead to improvements in the management of patients with headache.

Magnetic resonance spectroscopy studies in migraine

This review summarizes major findings and recent advances in magnetic resonance spectroscopy (MRS) of migraine. A multi database search of PubMed, EMBASE, and Web of Science was performed with variations of magnetic resonance spectroscopy and headache until 20th September 2021. The search generated 2897 studies, 676 which were duplicates and 1836 were not related to headache. Of the remaining 385 studies examined, further exclusions for not migraine (n = 114), and not MRS of human brain (n = 128), and non-original contributions (n = 51) or conferences (n = 24) or case studies (n = 11) or non-English (n = 3), were applied. The manuscripts of all resulting reports were reviewed for their possible inclusion in this manuscript (n = 54). The reference lists of all included reports were carefully reviewed and articles relevant to this review were added (n = 2).Included are 56 studies of migraine with and without aura that involve magnetic resonance spectroscopy of the human brain. The topics are presented in the form of a narrative review. This review aims to provide a summary of the metabolic changes measured by MRS in patients with migraine. Despite the variability reported between studies, common findings focused on regions functionally relevant to migraine such as occipital cortices, thalamic nuclei, cerebellum and cingulate. The most reproducible results were decreased N-acetyl-aspartate (NAA) in cerebellum in patients with hemiplegic migraine and in the thalamus of chronic migraine patients. Increased lactate (Lac) in the occipital cortex was found for migraine with aura but not in subjects without aura. MRS studies support the hypothesis of impaired energetics and mitochondrial dysfunction in migraine. Although results regarding GABA and Glu were less consistent, studies suggest there might be an imbalance of these important inhibitory and excitatory neurotransmitters in the migraine brain. Multinuclear imaging studies in migraine with and without aura, predominantly investigating phosphorous, report alterations of PCr in occipital, parietal, and posterior brain regions. There have been too few studies to assess the diagnostic relevance of sodium imaging in migraine.

The Characteristics of White Matter Hyperintensities in Patients With Migraine

Background

The presence of white matter hyperintensities (WMHs) in migraine is well-documented, but the location of WMH in patients with migraine is insufficiently researched. This study assessed WMH in patients with migraine using a modified version of the Scheltens visual rating scale, a semiquantitative scale for categorizing WMH in periventricular, lobar, basal ganglia, and infratentorial regions.

Methods

In total, 263 patients with migraine (31 men and232 women) enrolled in the American Registry for Migraine Research (ARMR) from Mayo Clinic Arizona and who had clinical brain magnetic resonance imaging (MRI) were included in this study. Those with imaging evidence for gross anatomical abnormalities other than WMHs were excluded. A board-certified neuroradiologist identified WMHs on axial T2 and fluid-attenuated inversion recovery (FLAIR) sequences. WMHs were characterized via manual inspection and categorized according to the scale's criteria.

Results

Results showed that 95 patients (36.1%, mean age: 41.8 years) had no WMHs on axial T2 and FLAIR imaging and 168 patients (63.9%, mean age: 51.4 year) had WMHs. Of those with WMHs, 94.1% (n = 158) had lobar hyperintensities (frontal: 148/158, 93.7%; parietal: 57/158, 36.1%; temporal: 35/158, 22.1%; and occipital: 9/158, 5.7%), 13/168, 7.7% had basal ganglia WMHs, 49/168, 29.1% had periventricular WMHs, and 17/168, 10.1% had infratentorial WMHs. In addition, 101/168 patients (60.1%) had bilateral WMHs and 67/168 (39.9%) had unilateral WMHs (34 right hemisphere/33 left hemisphere).

Discussion

Among ARMR participants who were enrolled by Mayo Clinic Arizona and who had clinical brain MRIs, nearly two-thirds had WMHs. The WMHs were the most common in the frontal lobes. Describing the features of WMHs in those with migraine, and comparing them with WMHs attributable to other etiologies, might be useful for developing classifiers that differentiate between migraine-specific WMH and other causes of WMH.

Preclinical assessment of onabotulinumtoxinA for the treatment of mild traumatic brain injury-related acute and persistent post-traumatic headache

Objective

Investigation of onabotulinumtoxinA in a murine model of acute and persistent post-traumatic headache.

Methods

Mild traumatic brain injury was induced with a weight drop method. Periorbital and hindpaw cutaneous allodynia were measured for 14 days. Mice were then exposed to bright light stress and allodynia was reassessed. OnabotulinumtoxinA (0.5 U) was injected subcutaneously over the cranial sutures at different post-injury time points.

Results

After milt traumatic brain injury, mice exhibited periorbital and hindpaw allodynia that lasted for approximately 14 days. Allodynia could be reinstated on days 14–67 by exposure to stress only in previously injured mice. OnabotulinumtoxinA administration at 2 h after mild traumatic brain injury fully blocked both transient acute and stress-induced allodynia up to day 67. When administered 72 h post-mild traumatic brain injury, onabotulinumtoxinA reversed acute allodynia, but only partially prevented stress-induced allodynia. OnabotulinumtoxinA administration at day 12, when initial allodynia was largely resolved, produced incomplete and transient prevention of stress-induced allodynia. The degree of acute allodynia correlated positively with subsequent stress-induced allodynia.

Conclusion

Mild traumatic brain injury induced transient headache-like pain followed by long lasting sensitization and persistent vulnerability to a normally innocuous stress stimulus, respectively modeling acute and persistent post-traumatic headache.. Administration of onabotulinumtoxinA following the resolution of acute post-traumatic headache diminished persistent post-traumatic headache but the effects were transient, suggesting that underlying persistent mild traumatic brain injury-induced maladaptations were not reversed. In contrast, early onabotulinumtoxinA administration fully blocked both acute post-traumatic headache as well as the transition to persistent post-traumatic headache suggesting prevention of neural adaptations that promote vulnerability to headache-like pain. Additionally, the degree of acute post-traumatic headache was predictive of risk of persistent post-traumatic headache.

Patient-Centered Treatment of Chronic Migraine With Medication Overuse: A Prospective, Randomized, Pragmatic Clinical Trial

BACKGROUND AND OBJECTIVES

Overuse of symptomatic (i.e., acute) medications is common among those with chronic migraine. It is associated with developing frequent headaches, medication side effects, and reduced quality of life. The optimal treatment strategy for patients who have chronic migraine with medication overuse (CMMO) has long been debated. The study objective was to determine whether migraine preventive therapy without switching or limiting the frequency of the overused medication was noninferior to migraine preventive therapy with switching from the overused medication to an alternative medication that could be used on ≤2 d/wk.

METHODS

The Medication Overuse Treatment Strategy (MOTS) trial was an open-label, pragmatic clinical trial, randomizing adult participants 1:1 to migraine preventive medication and (1) switching from the overused medication to an alternative used ≤2 d/wk or (2) continuation of the overused medication with no maximum limit. Participants were enrolled between February 2017 and December 2020 from 34 clinics in the United States, including headache specialty, general neurology, and primary care clinics. The primary outcome was moderate to severe headache day frequency during weeks 9 to 12 and subsequently during weeks 1 to 2 after randomization.

RESULTS

Seven hundred twenty participants were randomized; average age was 44 (SD 13) years; and 87.5% were female. At baseline, participants averaged 22.5 (SD 5.1) headache days over 4 weeks, including 12.8 (SD 6.7) moderate to severe headache days and 21.4 (SD 5.8) days of symptomatic medication use. Migraine preventive medication without switching of the overused medication was not inferior to preventive medication with switching for moderate to severe headache day frequency during weeks 9 to 12 (switching 9.3 [SD 7.2] vs no switching 9.1 [SD 6.8]; p = 0.75, 95% CI -1.0 to 1.3). The treatment strategies also provided similar outcomes during the first 2 weeks (switching 6.6 [SD 3.7] moderate to severe headaches days vs no switching 6.4 [SD 3.6]; p = 0.57, 95% CI -0.4 to 0.7).

DISCUSSION

When reduction in moderate to severe headache days was used as the outcome of interest for the management of CMMO, migraine preventive medication without switching or limiting symptomatic medication is not inferior to migraine preventive medication with switching to a different symptomatic medication with a maximum limit of 2 treatment days per week.

TRIAL REGISTRATION INFORMATION

ClinicalTrials.gov identifier NCT02764320.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that, for patients who have CMMO, migraine preventive medication without switching or limiting the overused medication is noninferior to migraine preventive medication with switching and limiting symptomatic medication.

Differentiating Between Migraine and Post-traumatic Headache Using a Machine Learning Classifier

OBJECTIVE

The objective was to develop classification models differentiating persistent PTH (PPTH) and migraine using clinical data and MRI-based measures of brain structure and functional connectivity.

BACKGROUND

PTH and migraine commonly have similar phenotypes. Furthermore, migraine is a risk factor for developing PTH, sometimes making it difficult to differentiate PTH from exacerbation of migraine symptoms.

DESIGN/METHODS

Thirty-four individuals with migraine without history of TBI and 48 individuals with mild TBI attributed to PPTH but without history of migraine or prior frequent tension type headache were included. Subjects completed questionnaires assessing headache characteristics, mood, sensory hypersensitivities and cognitive function and underwent MRI imaging during the same day. Clinical features and structural brain measures from T1-weighted imaging, diffusion tensor imaging and functional resting-state measures were included as potential variables. A classifier using ridge logistic regression of principal components (PC) was fit. Since PCs can hinder identification of significant variables in a model, a second regression model was fit directly to the data. In the non-PC based model, input variables were selected based on lowest t-test or chi-square p-value by modality. Average accuracy was calculated using leave-one-out cross validation. The importance of variables to the classifier were examined.

RESULTS

The PC-based classifier achieved an average classification accuracy of 85%. The non-PC based classifier achieved an average classification accuracy of 74.4%. Both classifiers were more accurate at classifying migraine subjects than PPTH. The PC-based model incorrectly classified 9/48 (18.8%) PPTH subjects compared to 3/34 (8.8%) migraine patients, whereas the non-PC classifier incorrectly classed 16/48 (33.3%) vs 5/34 (14.7%) of migraine subjects. Important variables in the non-PC model included static and dynamic functional connectivity values, several questions from the Beck Depression Inventory, and worsening symptoms and headaches with mental activity.

CONCLUSIONS

Multivariate models including clinical characteristics, functional connectivity, and brain structural data accurately classify and differentiate PPTH vs migraine.

A History of Mild Traumatic Brain Injury Is Associated With a a More Severe Long-term Migraine Phenotype

OBJECTIVE

This study aimed to investigate the effect of prior mTBI on the clinical features and disability in patients presenting with migraine.

BACKGROUND

Head injury is a risk factor for chronic migraine (CM) and migraine is a risk factor for persistent headache after mild traumatic brain injury (mTBI).

DESIGN/METHODS

Of 2,161 migraine patients without a diagnosis of post-traumatic headache (PTH) who participated in the American Registry for Migraine Research (ARMR) between February 2016 and March 2020, 1,120 answered questions about a history of mTBI. After controlling for age, gender, and having CM, demographics, headache characteristics, Patient Health Questionnaire-2 (PHQ-2) score, General Anxiety Disorder-7 (GAD-7) grade, and Migraine Disability Assessment Scale (MIDAS) scores were compared between those with a history of mTBI to those without.

RESULTS

Among 1,098 migraine patients, 37.6% (n = 413) had a history of mTBI. The patients with mTBI were more likely to have CM (p = 0.004), dizziness (p = 0.003), vertigo (p = 0.009), and difficulty finding words (p < 0.001). Patients with mTBI had significantly greater scores on the MIDAS (58.6 ± 52.6 vs 50.0 ± 47.8, p = 0.034) and PHQ-2 (1.6 ± 1.8 vs 1.3 ± 1.6, p = 0.012), and had significantly higher proportion of moderate to severe GAD-7 grade (21.7% vs 17.1%, p = 0.017) compared to those without mTBI.

CONCLUSIONS

In patients presenting with migraine, a prior history of mTBI was associated with a diagnosis of chronic migraine, disability, anxiety and depression severity, as well as dizziness, vertigo, and word finding difficulty. A history of mTBI should be assessed in patients presenting with migraine, and people with migraine who have a high exposure risk to mTBI, should be aware of the potential for migraine progression and psychiatric symptoms after mTBI.

Discriminant Subgraph Learning from Functional Brain Sensory Data

The human brain is a complex system with many functional units interacting with each other. This interacting relationship, known as the functional connectivity network (FCN), is critical for brain functions. To learn the FCN, machine learning algorithms can be built based on brain signals captured by sensing technologies such as EEG and fMRI. In neurological diseases, past research has revealed that the FCN is altered. Also, focusing on a specific disease, some part of the FCN, i.e., a sub-network, can be more susceptible than other parts. However, the current knowledge about disease-specific sub-networks is limited. We propose a novel Discriminant Subgraph Learner (DSL) to identify a functional sub-network that best differentiates patients with a specific disease from healthy controls based on brain sensory data. We develop an integrated optimization framework for DSL to simultaneously learn the FCN of each class and identify the discriminant sub-network. Further, we develop tractable and converging algorithms to solve the optimization. We apply DSL to identify a functional sub-network that best differentiates patients with episodic migraine (EM) from healthy controls based on a fMRI dataset. DSL achieved the best accuracy compared to five state-of-the-art competing algorithms.

T2* reduction in patients with acute post-traumatic headache

OBJECTIVES

Although iron accumulation in pain-processing brain regions has been associated with repeated migraine attacks, brain structural changes associated with post-traumatic headache have yet to be elucidated. To determine whether iron accumulation is associated with acute post-traumatic headache, magnetic resonance transverse relaxation rates (T2*) associated with iron accumulation were investigated between individuals with acute post-traumatic headache attributed to mild traumatic brain injury and healthy controls.

METHODS

Twenty individuals with acute post-traumatic headache and 20 age-matched healthy controls underwent 3T brain magnetic resonance imaging including quantitative T2* maps. T2* differences between individuals with post-traumatic headache versus healthy controls were compared using age-matched paired t-tests. Associations of T2* values with headache frequency and number of mild traumatic brain injuries were investigated using multiple linear regression in individuals with post-traumatic headache. Significance was determined using uncorrected p-value and cluster size threshold.

RESULTS

Individuals with post-traumatic headache had lower T2* values compared to healthy controls in cortical (bilateral frontal, bilateral anterior and posterior cingulate, right postcentral, bilateral temporal, right supramarginal, right rolandic, left insula, left occipital, right parahippocampal), subcortical (left putamen, bilateral hippocampal) and brainstem regions (pons). Within post-traumatic headache subjects, multiple linear regression showed a negative association between T2* in the right inferior parietal/supramarginal regions and number of mild traumatic brain injuries and a negative association between T2* in bilateral cingulate, bilateral precuneus, bilateral supplementary motor areas, bilateral insula, right middle temporal and right lingual areas and headache frequency.

CONCLUSIONS

Acute post-traumatic headache is associated with iron accumulation in multiple brain regions. Correlations with headache frequency and number of lifetime mild traumatic brain injuries suggest that iron accumulation is part of the pathophysiology or a marker of mild traumatic brain injury and post-traumatic headache.

Time course of efficacy of atogepant for the preventive treatment of migraine: Results from the randomized, double-blind ADVANCE trial

Background

Atogepant is an oral, small-molecule, calcitonin gene–related peptide receptor antagonist for the preventive treatment of migraine.

Methods

In the double-blind, phase 3 ADVANCE trial, participants with 4–14 migraine days/month were randomized to atogepant 10 mg, 30 mg, 60 mg, or placebo once daily for 12 weeks. We evaluated the time course of efficacy of atogepant for the preventive treatment of migraine. Analyses included change from baseline in mean monthly migraine days during each of the three 4-week treatment periods, change in weekly migraine days during weeks 1–4, and proportion of participants with a migraine on each day during the first week.

Results

We analyzed 873 participants (n = 214 atogepant 10 mg, n = 223 atogepant 30 mg, n = 222 atogepant 60 mg, n = 214 placebo). For weeks 1–4, mean change from baseline in mean monthly migraine days ranged from −3.1 to −3.9 across atogepant doses vs −1.6 for placebo (p < 0.0001). For weeks 5–8 and 9–12, reductions in mean monthly migraine days ranged from −3.7 to −4.2 for atogepant vs −2.9 for placebo (p ≤ 0.012) and −4.2 to −4.4 for atogepant vs −3.0 for placebo (p < 0.0002), respectively. Mean change from baseline in weekly migraine days in week 1 ranged from −0.77 to −1.03 for atogepant vs −0.29 with placebo (p < 0.0001). Percentages of participants reporting a migraine on post-dose day 1 ranged from 10.8% to 14.1% for atogepant vs 25.2% with placebo (p ≤ 0.0071).

Conclusion

Atogepant demonstrated treatment benefits as early as the first full day after treatment initiation, and sustained efficacy across each 4-week interval during the 12-week treatment period.

Clinical trial registration: ClinicalTrials.gov identifier: NCT03777059

Medication Overuse and Headache Burden: Results From the CaMEO Study

Objective

To estimate the relative frequency of acute medication overuse (AMO) among people with episodic migraine and chronic migraine, to characterize the types of acute medications overused for migraine, and to identify factors associated with AMO.

Methods

We analyzed data from the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study (ClinicalTrials.gov, NCT01648530), a cross-sectional and longitudinal internet study that included a systematic sampling of the US population. From September 2012 to November 2013, the CaMEO Study respondents participated in different modules to collect data on the clinical course of migraine, family burden, barriers to care, endophenotypes, and comorbidities. Among people who met the criteria for migraine consistent with the International Classification of Headache Disorders, third edition (ICHD-3), we evaluated types and frequency of medications used for headache/migraine, selected comorbidities, and emergency department (ED) and urgent care (UC) use. AMO was defined by days per month of medication use as specified by ICHD-3 criteria for medication overuse headache (MOH) without the requirement for ≥15 monthly headache days (MHDs). Nested, multivariable binary logistic regression modeling was used to identify factors associated with an increased risk of AMO.

Results

Of 16,789 CaMEO respondents with migraine, 2,975 (17.7%) met the AMO criteria. Approximately 67.9% (2,021/2,975) of AMO respondents reported <15 MHDs. Simple analgesics, combination analgesics, and opioids were the medication classes most commonly overused. Factors associated with AMO in the final multivariable logistic regression model included ≥15 MHDs, moderate to severe disability, severe migraine interictal burden, use of preventive medication, and an ED/UC visit for headache within 6 months.

Conclusions

Approximately two-thirds of respondents with AMO reported <15 MHDs and therefore did not meet the criteria for MOH. Those with AMO had greater disease burden and increased ED/UC utilization relative to people with migraine but not AMO.

Structural aberrations of the brain associated with migraine: A narrative review

OBJECTIVE

To summarize major results from imaging studies investigating brain structure in migraine.

BACKGROUND

Neuroimaging studies, using several different imaging and analysis techniques, have demonstrated aberrations in brain structure associated with migraine. This narrative review summarizes key imaging findings and relates imaging findings with clinical features of migraine.

METHODS

We searched PubMed for English language articles using the key words "neuroimaging" AND/OR "MRI" combined with "migraine" through August 20, 2020. The titles and abstracts of resulting articles were reviewed for their possible inclusion in this manuscript, followed by examination of the full texts and reference lists of relevant articles.

RESULTS

Migraine is associated with structural brain aberrations within regions that participate in pain processing, the processing of other sensory stimuli, multisensory integration, and in white matter fiber tracts. Furthermore, migraine is associated with magnetic resonance imaging T2/fluid-attenuated inversion recovery white matter hyperintensities. Some structural aberrations are correlated with the severity and clinical features of migraine, whereas others are not. These findings suggest that some structural abnormalities are associated with or amplified by recurrent migraine attacks, whereas others are intrinsic to the migraine brain.

CONCLUSIONS

Migraine is associated with aberrant brain structure. Structural neuroimaging studies contribute to understanding migraine pathophysiology and identification of brain regions associated with migraine and its individual symptoms. Additional work is needed to determine the extent to which structural aberrations are a result of recurrent migraine attacks, and perhaps reversible with effective treatment or migraine resolution, versus being intrinsic traits of the migraine brain.

Timing and durability of response to erenumab in patients with chronic migraine

Background

Erenumab is a human anti‐calcitonin gene‐related peptide receptor monoclonal antibody approved for migraine prevention. We sought to further assess the temporal patterns of response to erenumab in patients with chronic migraine (CM), specifically the onset and sustainability of monthly migraine day (MMD) response.

Methods

This is a post hoc analysis of a 12‐week, randomized, double‐blind, placebo‐controlled study of erenumab for migraine prevention in patients with CM (≥15 headache days/month, including ≥8 migraine days/month). Onset and sustainability were assessed according to MMD reduction from baseline, with the following response categories: responders (≥50% reduction), partial responders (≥30% and <50%), or nonresponders (<30%).

Results

Among the erenumab 140 mg group (n = 187), 54.0% (101/187) achieved a response at any month during the study with a median time to onset of monthly response of 1 month. This improvement was maintained in most patients with continued treatment. An initial response was achieved at Month 1 by 28.3% (53/187) of patients; 69.8% (37/53) of whom maintained a response at Months 2 and 3. Although many patients responded early, some patients required longer treatment to achieve a response; 79.4% (27/34) of initial partial responders and 21.0% (21/100) of initial nonresponders subsequently achieved a response. Similar findings were observed for the erenumab 70mg group (n = 188).

Conclusion

A majority of erenumab‐treated patients with CM who achieved an initial response at Month 1 sustained this benefit. Many patients responded later with continued treatment. Our data support recommendations to assess outcomes after ≥3 months of preventive treatment with erenumab in CM.

Altered speech patterns in subjects with post-traumatic headache due to mild traumatic brain injury

Background/objective

Changes in speech can be detected objectively before and during migraine attacks. The goal of this study was to interrogate whether speech changes can be detected in subjects with post-traumatic headache (PTH) attributed to mild traumatic brain injury (mTBI) and whether there are within-subject changes in speech during headaches compared to the headache-free state.

Methods

Using a series of speech elicitation tasks uploaded via a mobile application, PTH subjects and healthy controls (HC) provided speech samples once every 3 days, over a period of 12 weeks. The following speech parameters were assessed: vowel space area, vowel articulation precision, consonant articulation precision, average pitch, pitch variance, speaking rate and pause rate. Speech samples of subjects with PTH were compared to HC. To assess speech changes associated with PTH, speech samples of subjects during headache were compared to speech samples when subjects were headache-free. All analyses were conducted using a mixed-effect model design.

Results

Longitudinal speech samples were collected from nineteen subjects with PTH (mean age = 42.5, SD = 13.7) who were an average of 14 days (SD = 32.2) from their mTBI at the time of enrollment and thirty-one HC (mean age = 38.7, SD = 12.5). Regardless of headache presence or absence, PTH subjects had longer pause rates and reductions in vowel and consonant articulation precision relative to HC. On days when speech was collected during a headache, there were longer pause rates, slower sentence speaking rates and less precise consonant articulation compared to the speech production of HC. During headache, PTH subjects had slower speaking rates yet more precise vowel articulation compared to when they were headache-free.

Conclusions

Compared to HC, subjects with acute PTH demonstrate altered speech as measured by objective features of speech production. For individuals with PTH, speech production may have been more effortful resulting in slower speaking rates and more precise vowel articulation during headache vs. when they were headache-free, suggesting that speech alterations were related to PTH and not solely due to the underlying mTBI.