From Predictive Coding to Preventive Processing: Forecast-Triggered Pre-Emptive Treatment of Migraine
Abstract
Migraine pharmacotherapy still divides into two temporal strategies: continuous prevention, taken every day against attacks that occupy a minority of days, and acute treatment, taken after pain has begun. The PRODROME trial opened a third window: ubrogepant taken during the prodrome left 46% of treated prodromal events free of moderate or severe headache within 24 h, against 29% with placebo. Access to that window currently runs through the patientʹs ability to recognise their own prodrome reliably, which was an entry criterion of the trial rather than a general property of migraine. I argue that this dependence need not be permanent. On an active-inference reading, the prodrome is the physiological trace of a failing allostatic regulation loop; it perturbs autonomic output in ways that wrist-worn sensors record every night, and individualised machine-learning models have begun, modestly, to forecast next-day attacks f rom t hose r ecordings. C oupling calibrated forecasts to short-acting CGRP receptor antagonists would turn prevention from a standing pharmacological state into a triggered event. This paper sets out the computational rationale for such preventive processing, weighs the wearable and pharmacoepidemiological evidence, including the parts that resist the argument, and specifies the regimen-randomised trial on which the proposal should be judged.
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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.
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