SCOTTSDALE, Arizona — A simple prediction tool assessing an individual’s level of daily stress represents a novel approach for forecasting migraine headache and possibly providing an important means of prevention, researchers say.
“Our forecasting research represents a step forward in using information about triggers to formally predict the onset of a migraine attack,” first author, Timothy T. Houle, PhD, from the Department of Anesthesiology, Critical Care and Pain Medicine at Massachusetts General Hospital, Boston, told Medscape Medical News.
Though still preliminary, a forecasting tool could have a multitude of benefits, the authors added.
“The use of a forecasting model could be used to enhance pharmacological treatment opportunities, reduce anxiety about the unpredictability of attacks, increase locus of control beliefs, and lead to increased self-efficacy assessments about the self-management of migraine attacks,” they write.
The study, published in August in Headache, was discussed in a session of the year’s best studies in headache research, presented here at the American Headache Society (AHS) 2017 Scottsdale Headache Symposium.
While a variety of triggers, ranging from certain foods and alcohol to menstrual hormones, weather conditions, or stress, have been associated with episodic as well as chronic migraine headaches, none have been identified as having the capacity to actually forecast future headaches.
“Despite the widespread belief in certain triggers, there is not clear and convincing evidence that these triggers actually do cause headaches for most people or that avoiding them actually reduces the chances of a headache,” Dr Houle said.
To determine whether the frequency or intensity of the common trigger of daily stress could indeed help forecast migraines, Dr Houle and his team conducted the longitudinal Headache Predication Study (HAPRED), involving 100 individuals in the Winston-Salem, North Carolina, area who had migraine headache, with or without aura, from September 2009 to May 2014.
The patients were asked to complete electronic diary data, including their current headache state and levels of stress, by using several aspects of the Daily Stress Inventory.
The 95 patients included in the analysis reported experiencing headache attacks on 1613 of 4195 days (38.5%) in electronic diary data; patients kept individual diaries for an average of 49 days each.
The average level of affective distress reported was low to moderate, with moderate levels of headache-related disability.
The model showed that the frequency of stressful events or the perceived intensity of the events effectively predicted headache with high accuracy (an area under the curve of 0.73 in a training sample and 0.65 in a leave-one-out validation sample).
Importantly, the diaries showed that the days before headache reliably had greater levels of stress compared with days with no headache.
Previous research has suggested that identification of key premonitory headache symptoms could allow for the provision of treatment before the actual onset of pain, but the new study suggests the opportunity to take preventive measures even sooner, the authors said.
“The current study supports the feasibility of preemptory treatment and even enhances the potential window of opportunity for treatment given that unlike the [previous study], participants in the HAPRED study were forecasted to be at risk for a future headache before any premonitory symptoms actually began (assuming that perceived stress is not a premonitory symptom of a coming migraine attack),” they said.
While the forecasting model showed clinically significant utility across a large sample of individual headache patients over an extended period, the model should be viewed as a preliminary step in a headache forecasting tool, Dr Houle said.
“Before we can use the model clinically, we need to validate it on additional samples of people who might have different headache patterns and exposure to stress,” he said.
“All prediction models are associated with uncertainty and we need to better understand the degree of uncertainty in these predictions when applied to the general population of people.”
In an editorial published along with the study, Richard B. Lipton, MD, and colleagues from the Department of Neurology and the Montefiore Headache Center, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, said that in moving ahead with the prediction model, numerous complexities of headache manifestation need to be considered.
For instance, “[d]eviation from mean stress may be a better predictor than absolute level of stress,” they said. “Trigger factors may have cumulative effects; the probability of headache could increase over multiple days of high stress.”
In addition, an interaction of trigger factors could lead to an attack.
“For example, the effect of stress might be greater during menses or after drinking a glass of wine,” the editorial authors noted.
“Vulnerability to trigger factors could vary over time as the threshold for migraine attacks rises and falls based upon a combination of exogenous and endogenous variables.
“To address these complexities, we need large longitudinal data sets with prospective data collection, long-term follow-up periods, and sophisticated modeling approaches.”
The study meanwhile should help set those wheels in motion, they added.
“With their forecasting models, Houle et al have set the stage for short-term prediction of headaches in persons with migraine as a potential foundation for short-term preventive therapies,” they said.
“To realize the potential of these approaches, we must refine the art of headache forecasting and then test targeted interventions in carefully selected patients.”
The study received grant support from the National Institutes of Health/National Institute for Neurological Disorders and Stroke. Dr Houle has disclosed no relevant financial relationships. Dr Lipton’s and the editorial authors’ disclosures are available with the editorial.
American Headache Society (AHS) 2017 Scottsdale Headache Symposium.
Headache. Published online July 11, 2017. Abstract, Editorial
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