Migraine, one of the most widespread neurological disorders, has proven a difficult beast to tame. The seemingly random occurrence of attacks still thwart prediction. But a new model makes headway toward forecasting when a painful headache might next occur.
Migraine is described as a primary headache disorder and is a common condition. It produces a headache that is moderate to severe, and that is generally one-sided, pulsating, and capable of lasting for hours.
Migraine attacks can be incredibly painful and debilitating, sometimes confining the recipient to a darkened room for their duration. Nausea and other abdominal symptoms can also accompany them.
The condition is estimated to affect around 16 to 23 percent of adults aged 18 or older in the United States. A condition this prevalent has a substantial financial effect on the country. For example, one study estimated the lost productivity in the country, due to missed work, to be $5.6 billion to $17.2 billion per year.
Although risk factors across the population and within individuals have been identified, predicting when and where a migraine might strike has proven difficult. For instance, potential migraine triggers include food ingredients, hormone fluctuations, stress, lack of sleep, and certain foods, such as caffeine and cheese.
However, the chances of each individual’s trigger sparking an event, as well as the time at which it may begin, can vary substantially.
To ensure that preventive drugs have the best chance of nipping a migraine in the bud, they need to be taken before an attack. Although some people report characteristic symptoms before onset, they are nonspecific, and the time between them occurring and the headache beginning may vary, making them little use as a predictor.
Researchers from Massachusetts General Hospital in Boston wanted to see whether they could design a way to more accurately predict when a migraine would strike.
“We know that certain people are at greater risk of having an attack over other people, but within a person, we have not been able to predict increased risk for an attack with any level of accuracy,” explains lead study author Tim Houle, Ph.D.
The team’s recent findings are published this week in the journal Headache.
For their research, Dr. Houle and team recruited 95 people with migraine, with a total of 4,195 days of diary data. The participants experienced a migraine on 1,613 of these days (or 38.5 percent).
The team designed a model that collated data regarding the frequency of stressful events and their perceived intensity. Across the entire study, participants reported low to moderate stress. However, stress was more likely to be greater in the days leading up to a headache.
“This study demonstrates that it is quite possible to forecast the occurrence of a headache attack within an individual headache sufferer.”
Tim Houle, Ph.D.
Although treatment for migraine is still far from perfect, being able to predict when an attack might come means that they can be treated preemptively. Taking drugs before the event occurs can increase the chance that the migraine will be stopped in its tracks before it develops and becomes debilitating.
Dr. Houle and his team are eager to carry out more work to refine their model, saying, “The model we developed in this study is a very good start to helping people forecast the chances they will experience a headache attack, but work is needed to make the prediction models more accurate before they will be of widespread clinical use.”
The article is accompanied by an editorial called “Why migraine forecasting matters,” by Dr. Richard Lipton, Dr. Jelena Pavlovic, and Dr. Dawn C. Buse. The authors note that for preventive therapies to be truly useful, “we must refine the art of headache forecasting and then test targeted interventions in carefully selected patients.”
There will therefore be a wait until migraine prediction models are able to be used by the general population, but inroads have been made. Because migraine affects so many U.S. individuals, any breakthrough has the potential to improve millions of lives.