Abstract
OBJECTIVE: The present study endeavors to identify natural subgroups of migraine patients based on the patterns of non-headache symptoms, utilizing cluster analysis. Subsequently, network analysis was performed to estimate the structure of symptoms and explore the potential pathophysiology of these findings. METHOD: A total of 475 patients who met the diagnostic criteria for migraine were surveyed face-to-face during the period of 2019 to 2022. The survey included collecting demographic and symptom data. Four different solutions were generated by the K-means for mixed large data (KAMILA) clustering algorithm, from which the final cluster solutions were selected based on a series of cluster metrics. Subsequently, we performed network analysis using Bayesian Gaussian graphical models (BGGM) to estimate the symptom structure across subgroups and conducted global and pairwise comparisons between structures. RESULT: Cluster analysis identified two distinct patient groups, and the onset age of migraine proved to be an effective characteristic differentiating the two patient groups. Participants assigned to late-onset group showed a longer course of migraine, higher frequency of monthly headache attacks, and greater tendency toward medication overuse. In contrast, patients in early-onset group exhibited a higher frequency of nausea, vomiting, and phonophobia compared to their counterparts in the other group. The network analysis revealed a different symptom structure between the two groups globally, while the pairwise differences indicated an increasing connection between tinnitus and dizziness, and a decreasing connection between tinnitus and hearing loss in the early-onset group. CONCLUSION: Utilizing clustering and network analysis, we have identified two distinct non-headache symptom structures of migraine patients with early-onset age and late-onset age. Our findings suggest that the vestibular-cochlear symptoms may differ in the context of different onset ages of migraine patients, which may contribute to a better understanding of the pathology of vestibular-cochlear symptoms in migraine.