Lesion Expansion in Gnathic Fibrous Dysplasia: Natural History, Indicators of Progression, and Response to Bisphosphonates.

Fibrous dysplasia (FD) is characterized by expansile fibro-osseous lesions that may occur in association with endocrinopathies as part of McCune-Albright syndrome (MAS). Craniofacial FD is a significant source of morbidity and most commonly involves the gnathic bones. There is a critical need to understand the natural history and risk factors for gnathic FD progression to develop preventative trials and identify candidates for intervention. The purpose of this study was to characterize gnathic FD lesion expansion and to identify risk factors associated with lesion growth. Patients with gnathic FD and serial CT imaging were evaluated. Volumetric analyses of CT scans were performed using MIM Encore software. Generalized mixed model analysis was used to account for intra-subject correlation, with FD lesion volume as the dependent variable. In addition to age, effects of MAS-associated endocrinopathies, sex, disease severity, and bisphosphonate treatment were evaluated. A total of 104 total lesions in 52 patients were characterized longitudinally. Median age at initial scan was 8.8 years (range 3.4-18.8), and median age at final scan was 16.8 years (range 6.9-33.4 years). The median number of scans per subject was 4 (range 2-14). FD lesion volume increased with age (2.50 cm /yr, 95% confidence interval [CI] 1.95-3.04, p < 0.001). However, lesion expansion rate decreased over time (-0.05 cm /yr, 95% CI -0.07 to 0.04, p < 0.001). Mandibular lesions tended to expand at a greater rate than maxillary lesions (p < 0.001). Growth hormone excess was associated with accelerated expansion rate (p = 0.002). Other MAS-associated endocrinopathies, pubertal status, sex, weight, lesion density, disease severity, and bisphosphonate treatment were not associated with lesion volume or expansion. Gnathic FD lesion expansion is most rapid in younger children and declines as patients approach adulthood. The availability of quantitative natural history data will guide clinicians in identifying patients who are candidates for medical and surgical interventions and clinical trials for preventative therapies. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.