Identification of Symptoms Phenotypes of Hand Osteoarthritis using Hierarchical Clustering: Results from the <scp>DIGICOD</scp> Cohort - Sorbonne Université Access content directly
Journal Articles Arthritis Care & Research = Arthritis Care and Research Year : 2022

Identification of Symptoms Phenotypes of Hand Osteoarthritis using Hierarchical Clustering: Results from the DIGICOD Cohort

Félicie Costantino
Jérémie Sellam
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Abstract

Objectives: We aimed to delineate phenotypes in hand osteoarthritis (HOA) based on cardinal symptoms (pain, functional limitation, stiffness, aesthetic discomfort). Methods: With data from the DIGItal COhort Design (DIGICOD), we performed hierarchical agglomerative clustering analysis based on Australian/Canadian HOA index sub-scores (AUSCAN) for pain, physical function, stiffness, and visual analogue scale for aesthetic discomfort. Kruskal-Wallis and Post-Hoc analyses were used to assess differences between clusters. Results: Among 389 patients, we identified five clusters: cluster 1 (N=88) and cluster 2 (N=91) featured low and mild symptoms; cluster 3 (N=80) isolated aesthetic discomfort; cluster 4 (N=42) a high level of pain, stiffness, and functional limitation; and cluster 5 (N=88) the same features as cluster 4 but with high aesthetic discomfort. For clusters 4 and 5, AUSCAN pain was > 41/100 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. Conclusions: 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.
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hal-03843031 , version 1 (07-11-2022)

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Marie Binvignat, Gabriel Pires, Nicolas Tchitchek, Félicie Costantino, Alice Courties, et al.. Identification of Symptoms Phenotypes of Hand Osteoarthritis using Hierarchical Clustering: Results from the DIGICOD Cohort. Arthritis Care & Research = Arthritis Care and Research, In press, ⟨10.1002/acr.25047⟩. ⟨hal-03843031⟩
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