The current state of acute treatment for migraine in adults in the United States

Migraine is a common and disabling disorder with substantial personal, social, and economic burden that affects 37 million people in the United States. Risk factors for migraine include age, sex, and genetics. The goal of acute treatment of migraine attacks is to stop the pain and associated symptoms of the migraine attack and return the patient to normal function. The acute treatment landscape for migraine has recently expanded beyond the standard nonsteroidal anti-inflammatory drugs, analgesics, triptans, ergotamines, and combination therapies, to include neuromodulation devices, and recently approved calcitonin gene-related peptide receptor antagonists and a serotonin (5-HT_1F) receptor agonist. Unmet acute treatment needs still exist due to lack of efficacy, unwanted side effects, or contraindication to treatment. Effective treatment of migraine requires the clinician to assess the patient, make an accurate diagnosis, and then offer appropriate therapy based on the patient's medical history, comorbidities, and preferences, as well as published clinical evidence. The objective of this narrative review is to familiarize primary care clinicians with the variety of acute treatment options available in the United States today based on clinical trial findings, meta-analyses, evidence-based guidelines, and professional society consensus statements.

Effects of Lasmiditan on Cardiovascular Parameters and Pharmacokinetics in Healthy Subjects Receiving Oral Doses of Propranolol

Lasmiditan (LY573144/COL‐144) is a high‐affinity, centrally penetrant, selective 5‐HT_1F receptor agonist currently under investigation for acute treatment of migraine. Although lasmiditan is not known to induce vasoconstriction, it remains important to understand its effect on cardiovascular parameters because it is likely to be coadministered with β‐adrenergic receptor antagonists used for migraine prophylaxis, such as propranolol. This phase 1, single‐center, open‐label, fixed‐sequence study evaluated the cardiovascular and pharmacokinetic effects of 200 mg lasmiditan in 44 healthy subjects receiving repeated oral doses of twice‐daily 80 mg propranolol under fasting conditions. Coadministration caused statistically significant decreases in mean hourly heart rate relative to propranolol alone, but the maximum magnitude of this effect was –6.5 bpm and recovered to predose levels by 3 to 4 hours before stabilizing. Additionally, short‐lived (≤2.5 hours) statistically significant increases in systolic blood pressure (8.3 mm Hg) and diastolic blood pressure (6.4 mm Hg) were observed following coadministration. Consistent with the largely nonoverlapping metabolic pathways of lasmiditan and propranolol, exposure to either drug was not affected by coadministration. Overall, compared with administration of either drug alone, coadministration was generally well tolerated.

Empirically Defining Trajectories of Late-Life Cognitive and Functional Decline

BACKGROUND

Alzheimer's disease (AD) is associated with variable cognitive and functional decline, and it is difficult to predict who will develop the disease and how they will progress.

OBJECTIVE

This exploratory study aimed to define latent classes from participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database who had similar growth patterns of both cognitive and functional change using Growth Mixture Modeling (GMM), identify characteristics associated with those trajectories, and develop a decision tree using clinical predictors to determine which trajectory, as determined by GMM, individuals will most likely follow.

METHODS

We used ADNI early mild cognitive impairment (EMCI), late MCI (LMCI), AD dementia, and healthy control (HC) participants with known amyloid-β status and follow-up assessments on the Alzheimer's Disease Assessment Scale - Cognitive Subscale or the Functional Activities Questionnaire (FAQ) up to 24 months postbaseline. GMM defined trajectories. Classification and Regression Tree (CART) used certain baseline variables to predict likely trajectory path.

RESULTS

GMM identified three trajectory classes (C): C1 (n = 162, 13.6%) highest baseline impairment and steepest pattern of cognitive/functional decline; C3 (n = 819, 68.7%) lowest baseline impairment and minimal change on both; C2 (n = 211, 17.7%) intermediate pattern, worsening on both, but less steep than C1. C3 had fewer amyloid- or apolipoprotein-E ɛ4 (APOE4) positive and more healthy controls (HC) or EMCI cases. CART analysis identified two decision nodes using the FAQ to predict likely class with 82.3% estimated accuracy.

CONCLUSIONS

Cognitive/functional change followed three trajectories with greater baseline impairment and amyloid and APOE4 positivity associated with greater progression. FAQ may predict trajectory class.

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

AIMS

To assess how hippocampal volume (HV) from volumetric magnetic resonance imaging (vMRI) is related to the amyloid status at different stages of Alzheimer's disease (AD) and its relevance to patient care.

METHODS

We evaluated the ability of HV to predict the florbetapir positron emission tomography (PET) amyloid positive/negative status by group in healthy controls (HC, n = 170) and early/late mild cognitive impairment (EMCI, n = 252; LMCI, n = 136), and AD dementia (n = 75) subjects from the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity (ADNI-GO) and ADNI2. Logistic regression analyses, including elastic net classification modeling with 10-fold cross-validation, were used with age and education as covariates.

RESULTS

HV predicted amyloid status only in LMCI using either logistic regression [area under the curve (AUC) = 0.71, p < 0.001] or elastic net classification modeling [positive predictive value (PPV) = 72.7%]. In EMCI, age (AUC = 0.70, p < 0.0001) and age and/or education (PPV = 63.1%), but not HV, predicted amyloid status.

CONCLUSION

Using clinical neuroimaging, HV predicted amyloid status only in LMCI, suggesting that HV is not a biomarker surrogate for amyloid PET in clinical applications across the full diagnostic spectrum.

Longitudinal Trajectories of Clinical Decline in Amyloid Positive and Negative Populations

BACKGROUND

Brain beta-amyloid status portends different trajectories of clinical decline.

OBJECTIVE

Determine trajectories and predictive baseline variable(s).

DESIGN

Longitudinal, up to 24 months.

SETTING

ADNI sites.

PARTICIPANTS

Healthy control (n=325), early and late mild cognitive impairment (n=279; n=372), and Alzheimer's dementia (n=216) subjects from ADNI-1/GO/2.

MEASUREMENTS

Baseline amyloid status was based on first available CSF Aβ1-42 or, [11C]PiB or [18F]florbetapir (FBP) PET. Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13) and Functional Activities Questionnaire (FAQ) were co-analyzed using Growth Mixture Modeling (GMM) to define latent class trajectories for each amyloid group. Classification and Regression Tree (CART) analysis determined which variables best predicted trajectory class membership using a number of variables available to clinicians.

RESULTS

GMMs found two trajectory classes (C1, C2) each for amyloid-positive (P; n=722) and negative (N; n=470) groups. Most (90%) in the negative group were C2N with mildly impaired baseline ADAS-Cog13, normal FAQ and nonprogression; 10% were C1N with moderately impaired baseline FAQ and ADAS-Cog13 and trajectory of moderately worsening scores on the FAQ. C1P (26%) had more impaired baseline FAQ and ADAS-Cog13 than C2P (74%) and a steeper declining trajectory. CART yielded 4 decision nodes (FAQ <10.5, FAQ <6.5, MMSE ≥26.5, age <75.5) in positive and 1 node (FAQ <6.5) in negative groups, with 91.4% and 92.8% accuracy for class assignments, respectively.

CONCLUSIONS

The trajectory pattern of greater decline in amyloid positive subjects was predicted by greater baseline impairment of cognition and function. While most amyloid-negative subjects had nonprogression irrespective of their diagnosis, a subgroup declined similarly to the gradually declining amyloid-positive group. CART predicted likely trajectory class, with known amyloid status, using variables accessible in a clinical setting, but needs replication.

Relationship between the Montreal Cognitive Assessment and Mini-mental State Examination for assessment of mild cognitive impairment in older adults

BACKGROUND

The Montreal Cognitive Assessment (MoCA) was developed to enable earlier detection of mild cognitive impairment (MCI) relative to familiar multi-domain tests like the Mini-Mental State Exam (MMSE). Clinicians need to better understand the relationship between MoCA and MMSE scores.

METHODS

For this cross-sectional study, we analyzed 219 healthy control (HC), 299 MCI, and 100 Alzheimer's disease (AD) dementia cases from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-GO/2 database to evaluate MMSE and MoCA score distributions and select MoCA values to capture early and late MCI cases. Stepwise variable selection in logistic regression evaluated relative value of four test domains for separating MCI from HC. Functional Activities Questionnaire (FAQ) was evaluated as a strategy to separate dementia from MCI. Equi-percentile equating produced a translation grid for MoCA against MMSE scores. Receiver Operating Characteristic (ROC) analyses evaluated lower cutoff scores for capturing the most MCI cases.

RESULTS

Most dementia cases scored abnormally, while MCI and HC score distributions overlapped on each test. Most MCI cases scored ≥ 17 on MoCA (96.3%) and ≥ 24 on MMSE (98.3%). The ceiling effect (28-30 points) for MCI and HC was less using MoCA (18.1%) versus MMSE (71.4%). MoCA and MMSE scores correlated most for dementia (r = 0.86; versus MCI r = 0.60; HC r = 0.43). Equi-percentile equating showed a MoCA score of 18 was equivalent to MMSE of 24. ROC analysis found MoCA ≥ 17 as the cutoff between MCI and dementia that emphasized high sensitivity (92.3%) to capture MCI cases. The core and orientation domains in both tests best distinguished HC from MCI groups, whereas comprehension/executive function and attention/calculation were not helpful. Mean FAQ scores were significantly higher and a greater proportion had abnormal FAQ scores in dementia than MCI and HC.

CONCLUSIONS

MoCA and MMSE were more similar for dementia cases, but MoCA distributes MCI cases across a broader score range with less ceiling effect. A cutoff of ≥ 17 on the MoCA may help capture early and late MCI cases; depending on the level of sensitivity desired, ≥ 18 or 19 could be used. Functional assessment can help exclude dementia cases. MoCA scores are translatable to the MMSE to facilitate comparison.

Florbetapir positron emission tomography and cerebrospinal fluid biomarkers

BACKGROUND

We evaluated the relationship between florbetapir-F18 positron emission tomography (FBP PET) and cerebrospinal fluid (CSF) biomarkers.

METHODS

Alzheimer's Disease Neuroimaging Initiative-Grand Opportunity and Alzheimer's Disease Neuroimaging Initiative 2 (GO/2) healthy control (HC), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia subjects with clinical measures and CSF collected ±90 days of FBP PET data were analyzed using correlation and logistic regression.

RESULTS

In HC and MCI subjects, FBP PET anterior and posterior cingulate and composite standard uptake value ratios correlated with CSF amyloid beta (Aβ1-42) and tau/Aβ1-42 ratios. Using logistic regression, Aβ1-42, total tau (t-tau), phosphorylated tau181P (p-tau), and FBP PET composite each differentiated HC versus AD. Aβ1-42 and t-tau distinguished MCI versus AD, without additional contribution by FBP PET. Total tau and p-tau added discriminative power to FBP PET when classifying HC versus AD.

CONCLUSION

Based on cross-sectional diagnostic groups, both amyloid and tau measures distinguish healthy from demented subjects. Longitudinal analyses are needed.

Association between clinical measures and florbetapir F18 PET neuroimaging in mild or moderate Alzheimer's disease dementia

Clinical diagnosis of Alzheimer's disease (AD) is challenging, with 20% or more of patients misdiagnosed, even by expert clinicians. The authors conducted a retrospective, cross-sectional analysis comparing baseline neuropsychiatric and other clinical characteristics in 199 expert-diagnosed mild and moderate AD dementia patients participating in industry-sponsored clinical trials of an investigational therapy, where 18% lacked florbetapir positron emission tomography (PET) evidence of AD neuropathology. Significant differences were found only for cognition and ApoE ε4 status, but the large degree of score overlap would preclude using these measures to predict AD misdiagnosis. This study highlights the value of amyloid PET when evaluating patients with seemingly typical AD.