Researchers develop ‘simple’ predictive model for migraines

Gauging stress from daily frustrations may help prognosticate future migraine attacks in patients who experience them frequently, according to research recently published in Headache.

A previous study found that only 40.8% of people with chronic migraine present for care; of these, only 24.6% are diagnosed correctly and of those diagnosed, only 44.4% receive appropriate acute care. In addition, WHO data indicate headache disorders are among the 10 most disabling conditions for both genders combined and among the five most disabling for women, according to researchers.

“Despite the common nature of headache disorders, we still do not understand what ‘triggers’ an individual attack,” Timothy T. Houle, PhD, associate professor of anesthesia at Massachusetts General Hospital, and colleagues wrote in the current study. “...There is currently no available evidence that future headache attacks can be forecasted for any individual using any of the candidate headache triggers.

“When refined, this model has the potential to allow preemptive treatment of migraine attacks before the sufferer experiences pain or disability,” researchers added.

Houle and colleagues conducted a longitudinal cohort study using forecasting model development, analyzing 4,626 days of electronic diary data from 95 patients with episodic migraine with or without aura. Individual headache forecasts were derived from the patients’ current headache state and current levels of stress using the Daily Stress Inventory. The primary outcome measure was the presence or absence of any headache attack (head pain greater than 0 on a scale of 0-10) over the next 24-hour period.

Houle and colleagues found that after removing 431 days of missing data, participants in the study experienced a headache attack on 38.5% of the days studied. In addition, on a generalized linear mixed-effects forecast model, both the frequency of stressful events and the intensity of these events fit the data “well,” the researchers said. The predictive utility had an area under the curve of 0.73 (95% CI, 0.71-0.75) in the training sample and an area under the curve of 0.65 (95% CI, 0.6-0.67) in a leave-one-out validation sample.

Researchers also noted that this forecasting model had a Brier score of 0.202 and retained “good calibration” between forecasted probabilities and observed frequencies but had only low levels of resolution.

“The performance of this model was well calibrated, but possessed only modest degrees of resolution (ie, the forecasts centered around the sufferer’s base rate),” Houle and colleagues wrote.

In a related editorial, Richard B. Lipton, MD, director of the Montefiore Headache Center at Albert Einstein College of Medicine, and colleagues said that although the current study’s data are “fascinating,” there are other factors that must be considered before the study’s model can be put into clinical use. These other factors include distinguishing group-level and within-person analysis of predictors; contemplating the range of data that may be useful for attack prediction; and noting that predictors of impending attacks can be measured and modeled in a variety of ways.

“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. To realize the potential of these approaches, we must refine the art of headache forecasting and then test targeted interventions in carefully selected patients.”

Healio Family Medicine recently reported on several new treatment approaches for migraine headaches that are in the pipeline. – by Janel Miller

Reference s :

Dodick, DW, et al. Headache. 2016; DOI: 10.1111/head.12774.

Houle TT, et al. Headache. 2017;doi:10.1111/head.13137.

Lipton RB, Pavlovic JM. Headache. 2017;doi:10.1111/head.13142.

Disclosure: Houle reports no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.