Dataset Information

Development and Internal Validation of a Multivariable Prediction Model for Individual Episodic Migraine Attacks Based on Daily Trigger Exposures.

ABSTRACT:

Objective

To develop and internally validate a multivariable predictive model for days with new-onset migraine headaches based on patient self-prediction and exposure to common trigger factors.

Background

Accurate real-time forecasting of one's daily risk of migraine attack could help episodic migraine patients to target preventive medications for susceptible time periods and help decrease the burden of disease. Little is known about the predictive utility of common migraine trigger factors.

Methods

We recruited adults with episodic migraine through online forums to participate in a 90-day prospective daily-diary cohort study conducted through a custom research application for iPhone. Every evening, participants answered questions about migraine occurrence and potential predictors including stress, sleep, caffeine and alcohol consumption, menstruation, and self-prediction. We developed and estimated multivariable multilevel logistic regression models for the risk of a new-onset migraine day vs a healthy day and internally validated the models using repeated cross-validation.

Results

We had 178 participants complete the study and qualify for the primary analysis which included 1870 migraine events. We found that a decrease in caffeine consumption, higher self-predicted probability of headache, a higher level of stress, and times within 2 days of the onset of menstruation were positively associated with next-day migraine risk. The multivariable model predicted migraine risk only slightly better than chance (within-person C-statistic: 0.56, 95% CI: 0.54, 0.58).

Conclusions

In this study, episodic migraine attacks were not predictable based on self-prediction or on self-reported exposure to common trigger factors. Improvements in accuracy and breadth of data collection are needed to build clinically useful migraine prediction models.

SUBMITTER: Holsteen KK

PROVIDER: S-EPMC9645460 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

Development and Internal Validation of a Multivariable Prediction Model for Individual Episodic Migraine Attacks Based on Daily Trigger Exposures.

Holsteen Katherine K KK Hittle Michael M Barad Meredith M Nelson Lorene M LM

Headache 20201006 10

<h4>Objective</h4>To develop and internally validate a multivariable predictive model for days with new-onset migraine headaches based on patient self-prediction and exposure to common trigger factors.<h4>Background</h4>Accurate real-time forecasting of one's daily risk of migraine attack could help episodic migraine patients to target preventive medications for susceptible time periods and help decrease the burden of disease. Little is known about the predictive utility of common migraine trigg ...[more]

PMID: 33022773

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Project description:IntroductionBenign recurrent vertigo (BRV), Menière's disease (MD), and vestibular migraine (VM) show many similarities with regard to the course of vertigo attacks and clinical features. In this paper, we elaborate on the decreasing frequency of vertigo attacks observed in a previous study from our group by exploring changes in the duration and trigger factors of vertigo attacks in patients with BRV, MD, or VM.MethodsFor this 3-year prospective cohort study in our tertiary referral center we recruited patients with a confirmed diagnosis of BRV, MD, or VM by a neurologist and otorhinolaryngologist in our center in 2015-2016. A study-specific questionnaire was used to assess the usual duration of vertigo attacks and their potential triggers every 6 months. Main outcome measures were changes in duration and trigger factors of vertigo attacks in the subgroups of patients with persisting attacks, which were analyzed using repeated measures logistic regression models.Results121 patients were included (BRV: n = 44; MD: n = 43; VM: n = 34) of whom 117 completed the 3-year follow-up period and 57 (48.7%) kept reporting vertigo attacks at one more follow-up measurements. None of the diagnosis groups showed statistically significant shortening of attack duration at the subsequent annual follow-up measurements compared to baseline. At baseline, stress and fatigue being reported as triggers for attacks differed significantly between the three groups (stress: BRV 40.9%, MD 62.8%, VM 76.5%, p = 0.005; fatigue: BRV 31.0%, MD 48.8%, VM 68.8%, p = 0.003). In the VM group, a consistent reduction of stress and fatigue as triggers was observed up until the 24- and the 30-month follow-up measurements, respectively, with odds ratios (ORs) ranging from 0.15 to 0.33 (all p < 0.05). In the MD group, a consistent reduction of head movements as trigger was observed from the 24-month measurement onward (ORs ranging from 0.07 to 0.11, all p < 0.05).ConclusionOur study showed no reduction in vertigo attack duration over time in patients with BRV, MD, and VM who remain to have vertigo attacks. In VM and MD patients with persisting vertigo attacks stress, fatigue and head movements became less predominant triggers for vertigo attacks.

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Dataset Information

Development and Internal Validation of a Multivariable Prediction Model for Individual Episodic Migraine Attacks Based on Daily Trigger Exposures.

Objective

Background

Methods

Results

Conclusions

Publications

Development and Internal Validation of a Multivariable Prediction Model for Individual Episodic Migraine Attacks Based on Daily Trigger Exposures.

Similar Datasets

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