Shift from chronic to episodic migraine frequency in a long-term phase 3 study of galcanezumab
Abstract
Background: Chronic migraine (CM) is a highly disabling form of migraine in which patients have ≥ 15 headache days per month, of which at least 8 have the features of migraine. Galcanezumab is a monoclonal antibody to calcitonin gene-related peptide which is approved for the preventive treatment of migraine. Ability to convert patients from chronic migraine frequency to episodic migraine (EM) frequency is a clinically relevant and desirable outcome when prescribing preventive treatments to patients with CM.
Methods: Patients aged 18-65 years with an ICHD-3β diagnosis of CM were randomized 2:1:1 to receive monthly injections of placebo (N = 558), galcanezumab 120 mg with a 240-mg loading dose (N = 278), or galcanezumab 240 mg (N = 277) during a 3-month double-blind period of the phase 3 REGAIN trial. Patients could subsequently enter a 9-month open-label extension in which they received galcanezumab 120 mg or 240 mg/month per investigator's discretion. In this post-hoc analysis, we assessed the percentages of patients who shifted to EM (< 8 migraine headache days or < 15 headache days/month), low frequency EM (LFEM; <8 migraine headache days/month), and very low frequency EM (VLFEM; <4 migraine headache days/month) for at least 3 consecutive months. Double-blind percentage comparisons versus placebo represent modeled estimates from raw rates.
Results: At baseline, patients had a mean of 19.4 migraine headache days per month (SD = 4.5) and 21.4 headache days per month (SD =…
How strong is the evidence?
Evidence Hub reads this as a randomized trial, done in people. Its evidence level is 2 of 5 (High · randomized trial). Randomized trials of a reasonable size are the strongest single-study design. Reported size: 558 participants or records.
Read the paper
Related studies
- Calcium Ions in the Physiology and Pathology of the Central Nervous System
- AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene
- In Silico drug repurposing pipeline using deep learning and structure based approaches in epilepsy
- Targeting serotonin receptors with phytochemicals – an in-silico study
- In silico exploration of anti-prostate cancer compounds from differential expressed genes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.