BackgroundPeople with migraine report reduced health-related quality of life during ictal and interictal phases. However, most patient-reported outcome measures (PROMs) focus on impact during migraine episodes (ictal) or globally (both ictal and interictal), potentially neglecting interictal burden. This exploratory analysis evaluated correlations between the 4-item Migraine Interictal Burden Scale (MIBS-4) total score and other PROMs in people with migraine.MethodsA post hoc analysis was conducted using participant data from a galcanezumab phase 3, placebo-controlled, 3-month study, followed by a 3-month open-label extension in participants with prior treatment failures. Correlations were assessed between baseline MIBS-4 and disease characteristics, baseline MIBS-4 and demographics, and MIBS-4 and other PROMs/monthly migraine headache days at baseline and at Month (M) 6, using Spearman’s rank correlation coefficient (rs).ResultsA total of 462 participants were included (mean age: 45.8 years); 85.9% were female, 58.2% had episodic migraine and 41.8% had chronic migraine. At baseline, highest correlations with MIBS-4 were observed for Migraine Specific Quality of Life Questionnaire (MSQ)-total score, MSQ-Emotional Function (MSQ-EF), and the Patient Health Questionnaire (PHQ-9) score, which measures depressive symptoms (all p < 0.001). Correlation analysis between MIBS-4 and MSQ-total score revealed moderate correlation at baseline (rs:–0.53) that transitioned to moderate-high at M6 (rs:–0.70). MIBS-4 was moderately correlated with PHQ-9 score at baseline (rs:0.55) and M6 (rs:0.55). The Migraine Disability Assessment score transitioned from moderate-low correlation at baseline (rs:0.41) to moderate at M6 (rs: 0.53) and Generalized Anxiety Disorder score had moderate-low correlation at both time points (rs:0.42–0.47). MIBS-4 had moderate-negligible correlation with monthly migraine headache days at baseline (rs:0.21) and low correlation at Month 6 (rs:0.32).ConclusionInterictal burden, as assessed by MIBS-4, was moderately correlated with PROMs like MSQ, PHQ-9, and MIDAS, but moderate-negligible to low correlation was observed with monthly migraine headache days. These results indicate that interictal burden is a unique construct that is correlated with, but not fully captured by, other measures and should be considered when managing people with migraine.Clinical trial registrationClinicalTrials.gov identifier NCT03559257.

The total burden of migraine includes not only the episodes with headache pain but extends throughout the interictal periods. Interictal symptoms and associated psychological responses may profoundly impact well-being and drive treatment-seeking behavior. A cross-sectional online survey was conducted with participants aged ≥ 18 years, 250 with episodic migraine (EM) and 250 with chronic migraine (CM), having ≥ 4 monthly migraine headache days. All were naïve to galcanezumab or began ≤ 6 months before survey completion. The study evaluated factors associated with the Migraine Interictal Burden Scale (MIBS-4), including social determinants of health and well-being. Multiple linear regression, logistic regression, and random forests (RF) were used to explore predictors of MIBS-4. The majority of participants (90

Abstract Background To illustrate how (standardised) effect sizes (ES) vary based on calculation method and to provide considerations for improved reporting. Methods Data from three trials of tanezumab in subjects with osteoarthritis were analyzed. ES of tanezumab versus comparator for WOMAC Pain (outcome) was defined as least squares difference between means (mixed model for repeated measures analysis) divided by a pooled standard deviation (SD) of outcome scores. Three approaches to computing the SD were evaluated: Baseline (the pooled SD of WOMAC Pain values at baseline [pooled across treatments]); Endpoint (the pooled SD of these values at the time primary endpoints were assessed); and Median (the median pooled SD of these values based on the pooled SDs across available timepoints). Bootstrap analyses were used to compute 95% confidence intervals (CI). Results ES (95% CI) of tanezumab 2.5 mg based on Baseline, Endpoint, and Median SDs in one study were − 0.416 (− 0.796, − 0.060), − 0.195 (− 0.371, − 0.028), and − 0.196 (− 0.373, − 0.028), respectively; negative values indicate pain improvement. This pattern of ES differences (largest with Baseline SD, smallest with Endpoint SD, Median SD similar to Endpoint SD) was consistent across all studies and doses of tanezumab. Conclusion Differences in ES affect interpretation of treatment effect. Therefore, we advocate clearly reporting individual elements of ES in addition to its overall calculation. This is particularly important when ES estimates are used to determine sample sizes for clinical trials, as larger ES will lead to smaller sample sizes and potentially underpowered studies. Trial Registration Clinicaltrials.gov NCT02697773, NCT02709486, and NCT02528188.

Objective: To describe treatment patterns and direct healthcare costs over 3 years following initiation of standard of care acute and preventive migraine medications in patients with migraine in the United States. Background: There are limited data on long-term (>1 year) migraine treatments patterns and associated outcomes. Methods: This was a retrospective, observational cohort study using US claims data from the IBM (R) MarketScan (R) Research Database (January 2010-December 2017). Adults were included if they had a prescription claim for acute migraine treatments (AMT) or preventive migraine treatments (PMT) in the index period (January 2011-December 2014). The AMT cohort was categorized as persistent, cycled, or added-on subgroups; the PMT cohort was categorized PMT-persistent, switched without gaps, or cycled with gaps. Migraine-specific annual direct costs (2017 US$) across AMT and PMT cohort subgroups were summarized at baseline through 3 years from index (follow-up). Results: During the index period, 20,778 and 42,259 patients initiated an AMT and a PMT, respectively. At the 3-year follow-up, migraine-specific direct costs were lower in the persistent subgroup relative to the non-persistent subgroups in both AMT (mean [SD]: $789 [$1741] vs. $2847 [$8149] in the added-on subgroup and $862 [$5426] for the cycled subgroup) and PMT cohorts (mean [SD]: $1817 [$5892] in the persistent subgroup vs. $4257 [$11,392] in the switched without gaps subgroup and $3269 [$18,540] in the cycled with gaps subgroup). Acute medication overuse was lower in the persistent subgroup (1025/6504 [27.2%]) vs. non-persistent subgroups (11,236/58,863 [32.2%] in cycled with gaps subgroup and 1431/6504 [39.4%] in the switched without gaps subgroup). Most patients used multiple acute (19,717/20,778 [94.9%]) or preventive (38,494/42,259 [91.1%]) pharmacological therapies over 3 years following treatment initiation. Gaps in preventive therapy were common; an average gap ranged from 85 to 211 days (similar to 3-7 months). Conclusion: Migraine-specific annual healthcare costs and acute migraine medication overuse remained lowest among patients with persistent AMT and PMT versus non-persistent treatment. Study findings are limited to the US population. Future studies should compare costs and associated outcomes between newer preventive migraine medications in patients with migraine.

BACKGROUND:Health care resource utilization (HCRU) and direct costs incurred over 12 months following initiation of galcanezumab (GMB) or standard-of-care (SOC) preventive migraine treatments have been evaluated. However, a gap in knowledge exists in understanding longer-term HCRU and direct costs. OBJECTIVE:To compare all-cause and migraine-related HCRU and direct costs in patients with migraine initiating GMB or SOC preventive migraine treatments over a 24-month follow-up. METHODS:This retrospective study used Optum deidentified Market Clarity Data. The study included adults diagnosed with migraine, with at least 1 claim for GMB or SOC preventive migraine therapy (September 2018 to March 2020), with continuous enrollment for 12 months before and 24 months after (follow-up) the index date (date of first GMB or SOC claim). Propensity score (PS) matching (1:1) was used to balance cohorts. All-cause and migraine-related HCRU and direct costs for GMB vs SOC cohorts were reported as mean (SD) per patient per year (PPPY) over a 24-month follow-up and compared using a Z-test. Costs were inflated to 2022 US$. RESULTS:After PS matching, 2,307 patient pairs (mean age: 44.4 years; female sex: 87.3%) were identified. Compared with the SOC cohort, the GMB cohort had lower mean (SD) PPPY all-cause office visits (17.9 [17.7] vs 19.1 [18.7]; P = 0.023) and migraine-related office visits (2.6 [3.3] vs 3.0 [4.7]; P = 0.002) at follow-up. No significant differences were observed between cohorts in other all-cause and migraine-related events assessed including outpatient visits, emergency department (ED) visits, inpatient stays, and other medical visits. The mean (SD) costs PPPY were lower in the GMB cohort compared with the SOC cohort for all-cause office visits ($4,321 [7,518] vs $5,033 [7,211]; P < 0.001) at follow-up. However, the GMB cohort had higher mean (SD) PPPY all-cause total costs ($24,704 [30,705] vs $21,902 [28,213]; P = 0.001) and pharmacy costs ($9,507 [12,659] vs $5,623 [12,605]; P < 0.001) compared with the SOC cohort. Mean (SD) costs PPPY were lower in the GMB cohort for migraine-related office visits ($806 [1,690] vs $1,353 [2,805]; P < 0.001) compared with the SOC cohort. However, the GMB cohort had higher mean (SD) PPPY migraine-related total costs ($8,248 [11,486] vs $5,047 [9,749]; P < 0.001) and migraine-related pharmacy costs ($5,394 [3,986] vs $1,761 [4,133]; P < 0.001) compared with the SOC cohort. There were no significant differences between cohorts in all-cause and migraine-related costs for outpatient visits, ED visits, inpatient stays, and other medical visits. CONCLUSIONS:Although total costs were greater for GMB vs SOC following initiation, changes in a few categories of all-cause and migraine-related HCRU and direct costs were lower for GMB over a 24-month follow-up. Additional analysis evaluating indirect health care costs may offer insights into further cost savings incurred with preventive migraine treatment.

To describe experience with migraine and factors influencing the decision to seek treatment in a cohort of patients in the US initiating galcanezumab for migraine prevention.

To assess interictal burden (IIB) before patients initiate their first calcitonin gene-related peptide (CGRP) monoclonal antibody (mAb) for migraine prevention.

Migraine is under-diagnosed and under-treated. Many people with migraine do not seek medical care, and those who do may initially receive a different diagnosis and/or be dissatisfied with provided care on their journey before treatment with a CGRP-mAb (calcitonin-gene-related-peptide monoclonal antibody). This is a cross-sectional, self-reported, online survey of subjects in Lilly’s Emgality® Patient Support Program in 2022. Questionnaires collected insights into subjects’ prior experiences with migraine and interactions with healthcare professionals before receiving CGRP-mAbs. Of the 250 participants with episodic and 250 with chronic migraine, 90

Objective: To describe long-term (24-month) treatment patterns of patients initiating galcanezumab versus standard of care (SOC) preventive migraine treatments including anticonvulsants, beta-blockers, antidepressants, and onabotulinumtoxinA using administrative claims data. Methods: This retrospective cohort study, which used Optum de-identified Market Clarity data, included adults with migraine with >= 1 claim for galcanezumab or SOC preventive migraine therapy (September 1, 2018 - March 31, 2020) and continuous database enrollment for 12 months before (baseline) and 24 months after (follow-up) the index date (date of first claim). Baseline patient demographics, clinical characteristics, and treatment patterns were analyzed after 24-month follow-up, including adherence (measured as the proportion of days covered [PDC]), persistence, discontinuation (>= 60-day gap), restart, and treatment switch. Propensity score matching (1:1) was used to balance the galcanezumab and SOC cohorts. Results: The study included 2307 matched patient pairs with 24-month follow-up. The mean age across cohorts was 44.5 years (females: similar to 87%). Patients in the galcanezumab versus SOC cohort demonstrated greater treatment adherence (PDC: 48% vs. 38%), with more patients considered adherent (PDC >= 80%: 26.6% vs. 20.7%) and persistent (322.1 vs. 236.4 d) (all p < .001). After 24-month follow-up, fewer galcanezumab-treated patients had discontinued compared with SOC-treated patients (80.1% vs. 84.7%; p < .001), of which 41.3% and 39.6% switched to a non-index medication, respectively. The most prevalent medication patients switched to in both cohorts was erenumab. Significantly greater proportions of patients who initiated galcanezumab versus SOC medications switched to fremanezumab (p < .001) and onabotulinumtoxinA (p = .016). Conclusion: Patients who initiated galcanezumab for migraine prevention had higher treatment adherence and persistence compared with those who initiated SOC medications after 24-month follow-up.

Purpose: Recent studies show that exercise, which is recommended as first-line treatment for the management of knee osteoarthritis (OA), has similar effects to well-designed comparators. This highlights the need to better understand contextual/common factors that may explain treatment effects. Therapeutic alliance, the bond between patient and provider including the collaborative work of agreeing on the goals and task of treatment, may be one such factor. Further, since patient-provider relationship can influence adherence, it is possible the effects of therapeutic alliance on outcomes may be mediated by adherence. Our objective was to examine the effects of therapeutic alliance with change in pain and function after a physical therapist (PT)-delivered exercise intervention in people with knee OA and determine the extent to which this effect may be mediated by adherence (Figure 1).

Prediction of treatment responses is essential to move forward translational science. Our question was to identify patient-based variables that predicted responses to treatments. We conducted secondary analyses on pooled data from two randomized phase III clinical trials (NCT02697773 and NCT02709486) conducted in participants with moderate to severe osteoarthritis randomized to subcutaneous placebo (n = 514) or tanezumab 2.5 mg (n = 514). We used gradient boosted regression trees to identify variables that predicted Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain subscale scores at Week 16 and marginal plots to determine the directional relationship between each variable category and responses to placebo or tanezumab within the models. We also used Virtual Twins models to identify potential subgroups of response to the active treatment vs. placebo. We found that responses to placebo were predicted by baseline WOMAC Physical Function, baseline WOMAC Pain, the radiographic classification of the index joint, and the standard deviation of diary pain scores at baseline. In contrast, baseline WOMAC Pain along with failure of prior medications, duration of disease, and standard deviation of diary pain scores at baseline were predictive of tanezumab responses as expressed by the WOMAC Pain scores at Week 16. Those who responded to tanezumab vs. placebo were identified based on the radiographic classification of the index joint and either age or smoking status. These secondary-data analyses identified distinct and common patient-based variables to predict response to placebo or tanezumab. These findings will inform the design of future clinical trials, helping to move forward clinical pharmacology and translational science.