Real world effectiveness and tolerability of candesartan in the treatment of migraine: a retrospective cohort study
Abstract
To date, two randomized, controlled studies support the use of candesartan for migraine prophylaxis but with limited external validity. We aim to evaluate the effectiveness and tolerability of candesartan in clinical practice and to explore predictors of patient response. Retrospective cohort study including all patients with migraine who received candesartan between April 2008-February 2019. The primary endpoint was the number of monthly headache days during weeks 8–12 of treatment compared to baseline. Additionally, we evaluated the frequency during weeks 20–24. We analysed the percentage of patients with 50% and 75% response rates and the retention rates after three and 6 months of treatment. 120/4121 patients were eligible, aged 45.9 [11.5]; 100 (83.3%) female. Eighty-four patients (70%) had chronic migraine and 53 (42.7%) had medication-overuse headache. The median number of prior prophylactics was 3 (Inter-quartile range 2–5). At baseline, patients had 20.5 ± 8.5 headache days per month, decreasing 4.3 ± 8.4 days by 3 months (weeks 12–16) and by 4.7 ± 8.7 days by 6 months (paired Student’s t-test, p < 0.001). The percentage of patients with a 50% response was 32.5% at 3 months and 31.7% at 6 months, while the retention rate was 85.0% and 58.3%. The number of prior treatments (Odds ratio 0.79, 95% CI 0.64–0.97) and the presence of daily headache (Odds ratio 0.39, 95% CI 0.16–0.97) were associated with a lower probability of response. Candesartan showed beneficial…
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: 4,121 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.