“In this study, we used a generalized linear mixed model, specifically a two-level nested logistic regression model, which is also a machine learning approach.” However, there will undoubtedly be many various sorts of machine learning and AI applications that may be applied with this type of data in the future.”
The arsenal of therapy choices for migraine sufferers has risen significantly over the years, led by new calcitonin gene-related peptide (CGRP) antagonists. A new study examined the patient-reported treatment efficacy of 25 acute migraine medicines using a big-data technique. 10,842,795 migraine episodes were collected for data from 7 types of acetaminophen, nonsteroidal anti-inflammatory medications, triptans, combination analgesics, ergots, anti-emetics, and opioids.
The study, which was presented at the 2023 American Academy of Neurology (AAN) Annual Meeting in Boston, Massachusetts, found that triptans (OR, 4.8), ergots (OR, 3.02), and anti-emetics (OR, 2.67) were the top three groups of drugs with the highest efficacy. The OR of treatment success was examined using a 2-level nested logistic regression model adjusted for concomitant drugs and covariance within the same user, led by Chia-Chun Chiang, MD.
Chiang, an associate professor of neurology at Mayo Clinic Rochester, spoke during the meeting about why she and her colleagues did the study, as well as the implications of the findings. She mentioned that gepants and ditans were left out because of the lesser number of users when the data was retrieved. Furthermore, Chiang discussed the most important data elements migraine doctors should be aware of, as well as how big-data techniques might successfully affect the industry as technology advances.
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