Identification of clusters of individuals relevant to temporomandibular disorders and other chronic pain conditions: the OPPERA study
- PMID: 26928952
- PMCID: PMC4949303
- DOI: 10.1097/j.pain.0000000000000518
Identification of clusters of individuals relevant to temporomandibular disorders and other chronic pain conditions: the OPPERA study
Abstract
The classification of most chronic pain disorders gives emphasis to anatomical location of the pain to distinguish one disorder from the other (eg, back pain vs temporomandibular disorder [TMD]) or to define subtypes (eg, TMD myalgia vs arthralgia). However, anatomical criteria overlook etiology, potentially hampering treatment decisions. This study identified clusters of individuals using a comprehensive array of biopsychosocial measures. Data were collected from a case-control study of 1031 chronic TMD cases and 3247 TMD-free controls. Three subgroups were identified using supervised cluster analysis (referred to as the adaptive, pain-sensitive, and global symptoms clusters). Compared with the adaptive cluster, participants in the pain-sensitive cluster showed heightened sensitivity to experimental pain, and participants in the global symptoms cluster showed both greater pain sensitivity and greater psychological distress. Cluster membership was strongly associated with chronic TMD: 91.5% of TMD cases belonged to the pain-sensitive and global symptoms clusters, whereas 41.2% of controls belonged to the adaptive cluster. Temporomandibular disorder cases in the pain-sensitive and global symptoms clusters also showed greater pain intensity, jaw functional limitation, and more comorbid pain conditions. Similar results were obtained when the same methodology was applied to a smaller case-control study consisting of 199 chronic TMD cases and 201 TMD-free controls. During a median 3-year follow-up period of TMD-free individuals, participants in the global symptoms cluster had greater risk of developing first-onset TMD (hazard ratio = 2.8) compared with participants in the other 2 clusters. Cross-cohort predictive modeling was used to demonstrate the reliability of the clusters.
Conflict of interest statement
Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.
The authors have no conflicts of interest to declare.
R. Fillingim, G. Slade, and S. Smith are consultants and equity stock holders, and L. Diatchenko and W. Maixner are cofounders and equity stock holder in Algynomics, Inc, a company providing research services in personalized pain medication and diagnostics.
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