Researchers Propose Algorithm to Guide Treatment for JIA Affecting the Jaw Joints

Researchers Propose Algorithm to Guide Treatment for JIA Affecting the Jaw Joints

Researchers have developed an algorithm that may help with treatment decisions for people with juvenile arthritis that affects the jaw joints.

The study, “An Algorithm for Management of Dentofacial Deformity Resulting From Juvenile Idiopathic Arthritis: Results of a Multinational Consensus Conference,” was published in the Journal of Oral and Maxillofacial Surgery.

The majority of juvenile arthritis patients have some disease involvement in the temporomandibular joints (TMJs) — the joint near the ears where the jawbone connects to the rest of the skull. Due to the placement and function of this joint, such involvement can cause jaw problems, as well as impair the normal growth of the jaw, head, and face. These conditions are broadly termed dentofacial deformity.

However, symptoms are usually slow to develop to the point that they are noticed. That makes it not uncommon for a diagnosis to be made only once substantial damage has already been done.

There are two general strategies to manage these problems, both involving surgery. The first is to use techniques like splints to try to preserve the joint that is there. The second strategy is to remove the joint entirely and replace it, either with donor tissue or other materials.

To date, there hasn’t been a standardized protocol for how to treat juvenile arthritis patients with TMJ involvement.

To address this, a conference was held by the Temporomandibular Joint Juvenile Arthritis group, a network of researchers and clinicians specializing in this area. Using a combination of expert opinion and a review of the available scientific literature, the scientists constructed an algorithm to aid in the treatment of dentofacial deformity caused by juvenile arthritis.

The algorithm itself is in the form of a flow chart — a series of questions with “paths” to follow based on the answers. For example, the first question asked is whether the dentofacial deformity has progressed in the past year. Depending on the answer, a clinician can follow a “path” containing more questions — such as whether or not the patient’s skeleton is fully developed, whether the degree of facial asymmetry is moderate or severe, etc. — to ultimately reach the end, where a treatment is recommended.

In their paper, the researchers illustrate the algorithm’s use with a series of case studies. For example, one case focuses on a 13-year-old boy, who had no progression over the past year, had a mature skeleton, and had a moderate degree of facial asymmetry. Based on these criteria, the recommended course would be a kind of jaw surgery called orthognathic surgery.

The study’s authors hope the availability of this algorithm will not only improve patient care, but also standardize treatments. That would make data more consistent and, hopefully, easier to study scientifically.

“A standardized algorithm will improve clinical decision making and facilitate outcome research by allowing valid comparisons between published research studies,” they said.

However, the researchers stressed that the algorithm is best used as a “conceptual framework for management decisions rather than as a set of rigid treatment guidelines.” It must be modified as necessary “to meet unique patient scenarios that may not be fully addressed by the branches of the algorithm and must be adapted to the preferences of the patient and treatment team,” they said.

The investigators also “emphasize the importance of multidisciplinary evaluation, management, and long-term follow-up” for the proper care of patients.

Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
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Marisa holds an MS in Cellular and Molecular Pathology from the University of Pittsburgh, where she studied novel genetic drivers of ovarian cancer. She specializes in cancer biology, immunology, and genetics. Marisa began working with BioNews in 2018, and has written about science and health for SelfHacked and the Genetics Society of America. She also writes/composes musicals and coaches the University of Pittsburgh fencing club.
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