Development of a machine learning (ML) model to predict 3-month response to CGRP monoclonal antibodies in migraine: A pilot evaluation of physician-ML model interaction.

This study focused on predicting how well migraine patients respond to CGRP monoclonal antibodies (CGRP-mAbs). Researchers created a machine learning (ML) model to forecast treatment response after three months. They collected data from 228 patients treated at Dokkyo Medical University. This information was split into two groups: 182 patients for training the model and 46 patients for testing it. The ML model used a technique called Random Forest to analyze 27 different clinical factors. It aimed to predict whether patients would have at least a 50% reduction in migraine days. The study also examined how well the ML model worked alongside doctors' predictions. Findings suggest that using ML tools could enhance doctors' ability to predict treatment outcomes. Overall, this research offers a promising approach to personalize migraine treatment and improve patient care. Clinical relevance: This study indicates that machine learning can enhance predictions of treatment responses for migraine patients, potentially leading to more tailored and effective therapies.