Clustering-based stratification of fibromyalgia subtypes: A comparative analysis of medicated and non-medicated cohorts from two academic centers.

Fibromyalgia (FM) exhibits substantial clinical heterogeneity, yet reproducible symptom phenotypes with relevance for treatment personalization remain poorly defined. This study examined whether distinct FM phenotypes emerge consistently across medicated and unmedicated individuals. We analyzed 558 adults meeting the 2016 ACR criteria recruited from two academic centers. Participants completed standardized assessments of pain, central sensitization, depressive symptoms, sleep disturbance, and physical and emotional function. Multidomain variables were standardized and evaluated using hierarchical clustering, k-means algorithms, principal component analysis, and heatmap visualization. Phenotype stability was compared between those not receiving centrally acting medications at the time of assessment and those receiving centrally acting agents. A consistent three-cluster solution emerged. Cluster 1 represented a low-severity phenotype with relatively preserved function. Cluster 2 demonstrated prominent affective-sleep dysregulation with moderate pain and sensitization. Cluster 3 reflected a high-severity/global impairment phenotype across all symptom domains. Importantly, these phenotypes appeared in both medicated and unmedicated subgroups, indicating that similar symptom phenotypes were observed in participants receiving and not receiving centrally acting medications at the time of assessment. Fibromyalgia is characterized by three reproducible, clinically interpretable phenotypes that demonstrate substantial similarity across medication-status These findings support a precision-based framework for FM classification and provide a foundation for phenotype-guided therapeutic and mechanistic research.