AAN 2023 | Analysis of acute migraine medications: bridging the gap between research & real-world experiences

Chia-Chun Chiang, MD, Mayo Clinic, Rochester, MN, presented a groundbreaking study that involved a simultaneous comparison of 25 acute migraine medications using a big data approach. The primary goal of the study was to gain insights from real-world patient-reported outcomes, complementing the data obtained from clinical studies and randomized controlled trials. Migraine is a prevalent neurological disorder affecting more than 1 billion patients globally. By analyzing a vast amount of patient-reported data, the study aimed to provide valuable information that can supplement treatment recommendations outlined in clinical guidelines, such as those from the American Headache Society and the American Academy of Neurology. Dr Chiang highlights results of the study,which are not only consistent with the treatment recommendations derived from clinical guidelines but also aligned with previous publications on randomized controlled trials and meta-analyses. This consistency between the big data analysis and existing research further strengthens the credibility and reliability of the findings. The implications of these findings for clinical practice are significant. The study’s results offer valuable real-world insights into the effectiveness and comparative efficacy of various acute migraine medications. This information can serve as a complement to existing treatment guidelines and assist healthcare professionals in making informed decisions when prescribing medications for their patients. By utilizing a big data approach, Dr Chiang’s study contributes to bridging the gap between clinical research and real-world patient experiences. It highlights the importance of incorporating patient-reported outcomes and leveraging big data analysis to enhance our understanding of migraine treatment and improve clinical practice. This interview took place at the American Academy of Neurology Annual Meeting 2023 in Boston, MA.

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