Experimental pain phenotyping in community-dwelling individuals with knee osteoarthritis

Josue S. Cardoso, Joseph L. Riley, Toni Glover, Kimberly T. Sibille, Emily J. Bartley, Burel R. Goodin, Hailey W. Bulls, Matthew Herbert, Adriana S. Addison, Roland Staud, David T. Redden, Laurence A. Bradley, Roger B. Fillingim, Yenisel Cruz-Almeida

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

Pain among individuals with knee osteoarthritis (OA) is associated with significant disability in older adults, and recent evidence demonstrates enhanced experimental pain sensitivity. Although previous research showed considerable heterogeneity in the OA clinical pain presentation, less is known regarding the variability in responses to experimental pain. The present study included individuals with knee OA (n 292) who participated in the Understanding Pain and Limitations in Osteoarthritic Disease study and completed demographic and psychological questionnaires followed by a multimodal quantitative sensory testing (QST) session. Quantitative sensory testing measures were subjected to variable reduction procedures to derive pain sensitivity index scores, which in turn were entered into a cluster analysis. Five clusters were significantly different across all pain sensitivity index variables (P < 0.001) and were characterized by: (1) low pain sensitivity to pressure pain (N 39); (2) average pain sensitivity across most modalities (N 88); (3) high temporal summation of punctate pain (N 38); (4) high cold pain sensitivity (N 80); and (5) high sensitivity to heat pain and temporal summation of heat pain (N 41). Clusters differed significantly by race, gender, somatic reactivity, and catastrophizing (P < 0.05). Our findings support the notion that there are distinct subgroups or phenotypes based on experimental pain sensitivity in community-dwelling older adults with knee OA, expanding previous findings of similar cluster characterizations in healthy adults. Future research is needed to further understand the pathophysiological mechanisms underlying pain within these subgroups, which may be of added value in tailoring effective treatments for people with OA.

Original languageEnglish
Pages (from-to)2104-2114
Number of pages11
JournalPain
Volume157
Issue number9
DOIs
StatePublished - Sep 1 2016

Keywords

  • Experimental pain phenotypes
  • Hierarchical clustering
  • Pain phenotypes
  • Principal component analysis
  • QST

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