Forecasting Migraine Attacks and the Utility of Identifying Triggers.

Abstract

This review synthesizes the utility of measuring migraine triggers for the purpose of forecasting future headache attacks. The nature of forecasting models, headache triggers as inputs to such models, and how these trigger exposures can be measured for forecasting are reviewed. A critical evaluation of the existing forecasting models in the context of their potential application for preemptive treatment is considered. A substantial pool of candidate trigger factors could be considered in the creation of forecasting models. However, because mechanistic information about causal factors that precede a migraine attack is not well understood, and such factors are difficult to measure, empirical models that are based on trigger factors that are merely associated with the onset of headache activity are likely to be the focus of forecasting efforts in the near future. Of such factors, stress has considerable empirical support and has been used to successfully forecast future headache attacks within individuals over time. However, at present, existing models possess only modest levels of discrimination and lack strong resolution in generated predictions. Current headache forecasting models represent an important first step in accurately predicting future headache activity. However, to utilize these models in a preemptive treatment paradigm where the risk of headache is treated prior to the actual experience of pain, these models must achieve greater precision with good calibration and generate predictions that are clinically actionable by individuals in their real-time home environments.