Objective: This study aimed to explore whether phenotypic characteristics of patients with chronic widespread pain (CWP) and fibromyalgia (FM) can be aggregated into definable clusters that may help to tailor treatments.
Method: Baseline variables (sex, age, education, marital/employment status, pain duration, prior CWP/FM diagnosis, concomitant rheumatic disease, analgesics, tender point count, and disease variables derived from standardized questionnaires) collected from 1099 patients (93.4% females, mean age 44.6 years) with a confirmed CWP or FM diagnosis were evaluated by hierarchical cluster analysis. The number of clusters was based on coefficients in the agglomeration schedule, supported by dendrograms and silhouette plots. Simple and multiple regression analyses using all variables as independent predictors were used to assess the likelihood of cluster assignment, reported as odds ratios (ORs) with 95% confidence intervals (CIs).
Results: Only one cluster emerged (Cluster 1: 455 patients). Participants in this cluster were characterized as working (OR 66.67, 95% CI 7.14 to 500.00), with a medium-term/higher education (OR 16.80, 95% CI 1.94 to 145.41), married/cohabiting (OR 14.29, 95% CI 1.26 to 166.67), and using mild analgesics (OR 25.64, 95% CI 0.58 to > 999.99). The odds of being an individual in Cluster 1 were lower when having a worse score on the PDQ (score ≥ 18) (OR < 0.001, 95% CI < 0.001 to 0.02).
Conclusion: We identified one cluster, where participants were characterized by a potentially favourable clinical profile. More studies are needed to evaluate whether these characteristics could be used to guide the management of patients with CWP and FM.