An exploratory data-driven approach to classify subgroups of patients with temporomandibular disorders based on pain mechanisms

Temporomandibular disorders (TMDs) are a common musculoskeletal condition, presenting treatment challenges due to their non-specific nature. Categorizing patients with TMDs into clusters based on neurobiological pain mechanisms could provide a promising approach to facilitate targeted treatments. This observational study (1) used a network analysis (NA) to explore the complexity of TMDs by investigating relationships among biopsychosocial variables, and (2) validated potential TMD subgroups based on mechanism-specific pain categories. One hundred and two patients with TMD were included. Biopsychosocial variables covered: general health, psychosocial features, TMD pain, and TMD characteristics. A NA evaluated the associations between variables and determined the role of each feature within the network. Hierarchical clustering was used to identify TMD subgroups. The NA revealed significant correlations primarily within the same feature domains, indicating a strong interplay between symptoms and psychological factors. Cluster analysis identified two subgroups driven by nociceptive and nociplastic pain mechanisms; the nociplastic group exhibited higher levels of anxiety, depression, pain catastrophization, central sensitization, pain duration, and more pain locations, along with poorer sleep quality, quality of life, and health status. In contrast, the nociceptive group exhibited restricted maximal mouth opening (MMO), heightened pain during TMJ palpation and mouth opening, and a greater positive response to manual therapy. Across all features, psychological factors, pain locations, and MMO primarily contributed to the separation of subgroups. By adopting a data-driven approach, these results support the significant role of considering the neurobiological basis of pain to improve patient classification. This knowledge may facilitate clinical reasoning and personalized treatments. PERSPECTIVE: This study used a network analysis to explore the complex biopsychosocial interactions present in people with TMDs, identifying important variables such as the Central Sensitization Inventory and pain-free maximal mouth opening. The findings distinguish potential nociceptive and nociplastic pain subgroups, offering important insights for targeted therapeutic strategies.

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Publication Details

Journal
Journal of Pain
Published
2024-10-25
DOI
https://doi.org/10.1016/j.jpain.2024.104721
Citations
9
Primary Topic
Temporomandibular Joint Disorders
Type
article
Field-Weighted Citation Impact
4.54
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article

An exploratory data-driven approach to classify subgroups of patients with temporomandibular disorders based on pain mechanisms

Giacomo Asquini, Valter Devecchi, Domenico Viscuso, Ambra Michelotti et al.
9 citations
Journal of Pain
Temporomandibular Joint Disorders
4.54
article

An exploratory data-driven approach to classify subgroups of patients with temporomandibular disorders based on pain mechanisms

Giacomo Asquini, Valter Devecchi, Domenico Viscuso, Ambra Michelotti, Deborah Falla, Rosaria Bucci, Bernard X. W. Liew
article en
9 citations

Abstract

Temporomandibular disorders (TMDs) are a common musculoskeletal condition, presenting treatment challenges due to their non-specific nature. Categorizing patients with TMDs into clusters based on neurobiological pain mechanisms could provide a promising approach to facilitate targeted treatments. This observational study (1) used a network analysis (NA) to explore the complexity of TMDs by investigating relationships among biopsychosocial variables, and (2) validated potential TMD subgroups based on mechanism-specific pain categories. One hundred and two patients with TMD were included. Biopsychosocial variables covered: general health, psychosocial features, TMD pain, and TMD characteristics. A NA evaluated the associations between variables and determined the role of each feature within the network. Hierarchical clustering was used to identify TMD subgroups. The NA revealed significant correlations primarily within the same feature domains, indicating a strong interplay between symptoms and psychological factors. Cluster analysis identified two subgroups driven by nociceptive and nociplastic pain mechanisms; the nociplastic group exhibited higher levels of anxiety, depression, pain catastrophization, central sensitization, pain duration, and more pain locations, along with poorer sleep quality, quality of life, and health status. In contrast, the nociceptive group exhibited restricted maximal mouth opening (MMO), heightened pain during TMJ palpation and mouth opening, and a greater positive response to manual therapy. Across all features, psychological factors, pain locations, and MMO primarily contributed to the separation of subgroups. By adopting a data-driven approach, these results support the significant role of considering the neurobiological basis of pain to improve patient classification. This knowledge may facilitate clinical reasoning and personalized treatments. PERSPECTIVE: This study used a network analysis to explore the complex biopsychosocial interactions present in people with TMDs, identifying important variables such as the Central Sensitization Inventory and pain-free maximal mouth opening. The findings distinguish potential nociceptive and nociplastic pain subgroups, offering important insights for targeted therapeutic strategies.

Journal of PainVol. 26
University of Essex (GB), University of Cagliari (IT), University of Naples Federico II (IT), University of Birmingham (GB)
Reduced inequalities
Openalex Percentile: Top 4%
Temporomandibular Joint Disorders
4.54
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