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Identification of Symptom Phenotypes of Hand Osteoarthritis Using Hierarchical Clustering: Results From the DIGICOD Cohort
Author(s) -
Binvignat Marie,
Pires Gabriel,
Tchitchek Nicolas,
Costantino Félicie,
Courties Alice,
Klatzmann David,
Butte Atul J.,
Combe Bernard,
Dougados Maxime,
Richette Pascal,
MariottiFerrandiz Encarnita,
Berenbaum Francis,
Sellam Jérémie
Publication year - 2023
Publication title -
arthritis care and research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.032
H-Index - 163
eISSN - 2151-4658
pISSN - 2151-464X
DOI - 10.1002/acr.25047
Subject(s) - cohort , identification (biology) , osteoarthritis , hierarchical clustering , cluster analysis , medicine , phenotype , physical medicine and rehabilitation , computer science , biology , artificial intelligence , genetics , pathology , alternative medicine , botany , gene
Objective We aimed to delineate phenotypes in hand osteoarthritis (HOA) based on cardinal symptoms (pain, functional limitation, stiffness, and aesthetic discomfort). Methods With data from the Digital Cohort Design (DIGICOD), we performed a hierarchical agglomerative clustering analysis based on Australian/Canadian Osteoarthritis Hand Index (AUSCAN) subscores for pain, physical function, stiffness, and visual analog scale for aesthetic discomfort. Kruskal‐Wallis and post hoc analyses were used to assess differences between clusters. Results Among 389 patients, we identified 5 clusters: cluster 1 (n = 88) and cluster 2 (n = 91) featured low and mild symptoms; cluster 3 (n = 80) featured isolated aesthetic discomfort; cluster 4 (n = 42) featured a high level of pain, stiffness, and functional limitation; and cluster 5 (n = 88) had the same features as cluster 4 but with high aesthetic discomfort. For clusters 4 and 5, AUSCAN pain score was >41 of 100, representing only one‐third of our patients. Aesthetic discomfort (clusters 3 and 5) was significantly associated with erosive HOA and a higher number of nodes. The highly symptomatic cluster 5 was associated but not significantly with metabolic syndrome, and body mass index and C‐reactive protein level did not differ among clusters. Symptom intensity was significantly associated with joint destruction as well as with physical and psychological burden. Patients’ main expectations differed among clusters, and function improvement was the most frequent expectation overall. Conclusion The identification of distinct clinical clusters based on HOA cardinal symptoms suggests previously undescribed subtypes of this condition, warranting further study of biological characteristics of such clusters, and opening a path toward phenotype‐based personalized medicine in HOA.