A 3-year follow-up study of outcomes associated with patterns of traditional acute and preventive migraine treatment: An administrative claims-based cohort study in the United States.

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® MarketScan® 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 (~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.

Treatment patterns of galcanezumab versus standard of care preventive migraine medications over 24 months: a US retrospective claims study.

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: ∼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.

Only few patients (3 − 13%) with migraine, who qualify for preventive treatment, are using them. Conventional preventive treatments have not been developed specifically for migraine treatment, and more than half of the patients stop using them prematurely. Calcitonin gene-related peptide monoclonal antibodies such as galcanezumab, fremanezumab, and erenumab are newer treatments that provide migraine-specific preventive treatment. Prior studies have compared 6- to 12-month migraine medication use by patients starting galcanezumab versus those starting traditional standard of care (SOC) migraine preventive medications. We compared long-term (24-month) migraine medication use in patients starting galcanezumab versus those starting SOC migraine preventive medications to confirm if the results are sustained over a longer period. Over 24 months, patients who used galcanezumab followed the prescribed treatment regimen to a greater extent compared with those who used SOC medications (48% vs. 38%, respectively). Additionally, patients using galcanezumab continued treatment for a longer time compared with those using SOC. Over 24 months, about 85% of patients stopped taking SOC medications, while around 80% of patients stopped taking galcanezumab. Our findings indicate that patients with migraine are more likely to continue using galcanezumab as a preventive treatment for a longer period compared with SOC medications. This study helps identify gaps in the preventive treatment of migraine and provides insights on how they are not being used enough.

Effect size varies based on calculation method and may affect interpretation of treatment effect: an illustration using randomised clinical trials in osteoarthritis.

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.

Health care resource utilization and direct costs incurred over 24 months after initiating galcanezumab or standard-of-care preventive migraine treatments in the United States.

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.

Inter-Reader Consistency and Exclusionary Findings During Radiographic Screening for Phase 3 Trials of Tanezumab in Patients With Osteoarthritis.

Objective: Describe the radiograph-based screening program and frequencies of ineligibility in 3 large, international, randomized, double-blind, phase 3 studies of subcutaneous tanezumab in patients with osteoarthritis (OA). Design: Standardized bilateral shoulder, hip, and knee screening radiographs were obtained by trained imaging technologists and centrally read by 1 of 5 musculoskeletal radiology experts trained using a program-specific imaging atlas. Inter-reader consistency was tracked with test cases blindly inserted into the reader queue. Readers attended quarterly calibration meetings. Protocol-specified radiographic exclusion criteria included rapidly progressive OA (RPOA) or risk factors for RPOA (including severe malalignment of the knee, subchondral insufficiency fracture, atrophic OA, and osteonecrosis). Patients reporting disproportionate pain to radiographic evidence of OA in the hip or knee (without other pathology) were ineligible under a nonradiographic exclusion criterion. Results: At >480 international sites, 23,079 patients entered screening and 13,797 were radiographically assessed. Across 6 sets of quarterly testing, pairwise central reader agreement on radiographic eligibility was 72-87% (kappa: 0.41-0.71) and on radiographic OA grading 77-84% (kappa: 0.68-0.75). Among the 5,773/13,797 (41.8%) patients who met exclusionary criteria, 27% had disproportionate pain to radiographic findings (~10% of knee/hip radiographs). RPOA or risk factors for RPOA were each identified in <5% of patients (usually 1 joint) and <3% of knee/hip/shoulders. Conclusions: The phase 3 tanezumab screening program demonstrated the utility of radiographs to screen patients entering NGF inhibitor trials. A high degree of reader concordance was achieved. RPOA and risk factors for RPOA were not commonly observed. NCT02697773, NCT02709486, NCT02528188.

Effect size varies based on calculation method and may affect interpretation of treatment effect: an illustration using randomised clinical trials in osteoarthritis

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.