A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression

Schematic representation for the steps of the TMJ OA prognosis prediction model’s development. (A) Clinical, imaging, and biological data were collected from the study subjects, at baseline, and utilized to create the OA Prognosis Prediction model. (B) Clinical and imaging data were collected, at follow-up visits, to label the training dataset with the changes of the participants’ health status following 2 to 3 y of conservative management.

Schematic representation for the steps of the TMJ OA prognosis prediction model’s development. (A) Clinical, imaging, and biological data were collected from the study subjects, at baseline, and utilized to create the OA Prognosis Prediction model. 

Schematic representation for the steps of the TMJ OA prognosis prediction model’s development. (A) Clinical, imaging, and biological data were collected from the study subjects, at baseline, and utilized to create the OA Prognosis Prediction model. (B) Clinical and imaging data were collected, at follow-up visits, to label the training dataset with the changes of the participants’ health status following 2 to 3 y of conservative management.

(B) Clinical and imaging data were collected, at follow-up visits, to label the training dataset with the changes of the participants’ health status following 2 to 3 y of conservative management.

What is it?

Temporomandibular joint osteoarthritis (TMJ OA) is a common condition causing jaw pain and difficulty moving the jaw.

What problem does it aim to solve?

The study aimed to improve prediction of how TMJ OA progresses and how patients respond to treatment.

How does it work?

Researchers followed 106 patients, with 74 of them getting checked after 2 to 3 years of non-surgical treatment. This study identified a comprehensive set of clinical, quantitative imaging, and biological biomarkers for precise prediction of TMJ OA disease progression. Researchers developed an open-source tool based on a robust method called Ensemble via Hierarchical Predictions through Nested cross-validation (EHPN), which surpassed the performance of the 48 models tested. The EHPN model achieved an F1 score of 0.82, indicating strong performance and reliability with new, unseen data, and minimizing false positives and negatives.

What are the real-world implications?

The use of the EHPN model may revolutionize the standards of care, providing clinicians with an accurate tool for anticipating the future status of TMJ OA patients, thereby enhancing their decision-making process.

What are the next steps?

Further refinement of the model.

Source

, Proceedings of the National Academy of Sciences USA 2024  Vol. 121  No. 8  

Authors

Najla Al Turkestani
Department of Restorative Dentistry, Faculty of Dentistry, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Psychiatry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599

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Department of Orthodontics, 91³ÉÈ˵¼º½, Arthur A. Dugoni School of Dentistry, San Francisco, CA 94103

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Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Psychiatry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599

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Department of Psychiatry, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599

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Department of Periodontics & Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Periodontics & Oral Medicine, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Biologic and Materials Sciences & Prosthodontics, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Cariology, Restorative Sciences and Endodontics, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Radiation Oncology, University of Michigan, Ann Arbor, MI 48109
Department of Computational Medicine & Bioinformatics, School of Dentistry, University of Michigan, Ann Arbor, MI 48109

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Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599

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Department of Orthodontics and Pediatric Dentistry, School of Dentistry, University of Michigan, Ann Arbor, MI 48109