Advances in the diagnosis and the management of primary hyperparathyroidism

Insights into Hyperparathyroidism-Jaw Tumour Syndrome: From Endocrine Acumen to the Spectrum of CDC73 Gene and Parafibromin-Deficient Tumours

A total of 1 out of 10 patients with primary hyperparathyroidism (PHP) presents an underlying genetic form, such as multiple endocrine neoplasia types 1, 2A, etc., as well as hyperparathyroidism-jaw tumour syndrome (HJT). We aimed to summarise the recent data, thus raising more awareness regarding HJT, from the clinical perspective of PHP in association with the challenges and pitfalls of CDC73 genetic testing and parafibromin staining. This narrative review included a sample-focused analysis from the past decade according to a PubMed search. We identified 17 original human studies (≥4 patients per article). The mean age at disease onset was between 20.8 and 39.5 years, while the largest study found that 71% of patients had HJT recognised before the age of 30. Males and females seemed to be equally affected, in contrast with sporadic PHP. PHP represented the central manifestation of HJT, occurring as the first manifestation in up to 85% of HJT cases. A biochemistry panel found a mean serum calcium level above the level of 12 mg/dL in PHP. PTH was elevated in HJT as well, with average values of at least 236.6 pg/mL. The most frequent pathological type in PHP was a parathyroid adenoma, but the incidence of a parathyroid carcinoma was much higher than in non-HJT cases (15% of all parathyroid tumours), with the diagnosis being established between the age of 15 and 37.5. In some families up to 85% of carriers suffered from a parathyroid carcinoma thus indicating that certain CDC73 pathogenic variants may harbour a higher risk. An important issue in HJT was represented by the parafibromin profile in the parathyroid tumours since in HJT both parathyroid adenomas and carcinomas might display a deficient immunoreactivity. Another frequent manifestation in HJT was ossifying fibromas of the jaw (affecting 5.4% to 50% of patients; the largest study found a prevalence of 15.4%). HJT was associated with a wide variety of kidney lesion (mostly: kidney cysts, with a prevalence of up to 75%, and renal tumours involved in 19% of patients). The risk of uterine lesions seemed increased in HJT, especially with concern to leiomyomas, adenofibromas, and adenomyosis. The underlying pathogenic mechanisms and the involvement of CDC73 pathogenic variants and parafibromin expression are yet to be explored. Currently, the heterogeneous expression of parafibromin status and, the wide spectrum of CDC73 mutations including the variety of clinical presentations in HJT, make it difficult to predict the phenotype based on the genotype. The central role of HJT-PHP is, however, the main clinical element, while the elevated risk of parathyroid carcinoma requires a special awareness.

Degraded Bone Microarchitecture in Women with PHPT-Significant Predictor of Fracture Probability

Introduction

Patients with primary hyperparathyroidism (PHPT) experience bone mineral density (BMD) loss and trabecular bone score (TBS) alteration, which current guidelines recommend assessing. Considering TBS alongside BMD for a 10-year fracture risk assessment (FRAX) may improve PHPT management.

Design

Retrospective, cross-sectional study composed of 49 Caucasian females (62 ± 10.6 years, 27.7 ± 0.87 kg/m²) with PHPT and 132 matched control subjects (61.3 ± 10.5 years, 27.5 ± 0.49 kg/m²) evaluated in 3 years. We assessed lumbar spine (LS) and femoral neck (FN) BMD, T and Z scores (GE Healthcare Lunar Osteodensitometer) and TBS (iNsight 1.8), major osteoporotic fracture (MOF), and hip FRAX.

Results

Patients with PHPT had statistically lower mean values for lumbar spine bone mineral density (LS BMD) (0.95 ± 0.25 vs 1.01 ± 0.14 g/cm², P = .01), LS T-scores (-2 ± 0.2 vs -1.4 ± 0.1 SD, P = .009), LS Z scores (-0.9 ± 0.19 vs -0.1 ± 0.11 SD, P = .009), femoral neck bone mineral density (FN BMD) (0.79 ± 0.02 vs 0.83 ± 0.01 g/cm², P = .02), FN T-scores (-1.8 ± 0.13 vs -1.5 ± 0.07 SD, P = .017), FN Z scores (-0.51 ± 0.87 vs -0.1 ± 0.82 SD, P = .006), and TBS (0.95 ± 0.25 vs 1.01 ± 0.14 g/cm², P = .01) compared with control subjects. 22.4% of patients with PHPT had degraded microarchitecture (TBS < 1.2) vs. 7.6% in control group (χ² = 0.008). PHPT proved to be a covariate with unique contribution (P = .031) alongside LS BMD (P = .040) in a linear regression model [R ² = 0.532, F(4,16) = 4.543] for TBS < 1.2. TBS adjustment elevated MOF FRAX both for PHPT (4.35  ± 0.6% vs 5.25% ± 0.73%, P < .001) and control groups (4.5  ± 0.24% vs 4.7% ± 0.26%, P < .001) compared with BMD-bases FRAX, but also increased differently between the 2 study groups (1.1-folds for PHPT patients and 1.04 for control subjects, P = .034).

Conclusion

Compared with control, TBS-adjusted FRAX provides significantly higher MOF risk than BMD-based FRAX in PHPT women.

A visual deep learning model to predict abnormal versus normal parathyroid glands using intraoperative autofluorescence signals

BACKGROUND

Previous work demonstrated that abnormal versus normal parathyroid glands (PGs) exhibit different patterns of autofluorescence, with former appearing darker and more heterogenous. Our objective was to develop a visual artificial intelligence model using intraoperative autofluorescence signals to predict whether a PG is abnormal (hypersecreting and/or hypercellular) or normal before excision during surgical exploration for primary hyperparathyroidism.

METHODS

A total of 906 intraoperative parathyroid autofluorescence images of 303 patients undergoing parathyroidectomy/thyroidectomy were used to develop model. Autofluorescence image of each PG was uploaded into the visual artificial intelligence platform as abnormal or normal. For deep learning, randomly chosen 80% of data was used for training, 10% for testing, 10% for validation. The area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), recall (sensitivity), and precision (positive predictive value) of the model were calculated.

RESULTS

AUROC and AUPRC of the model to predict normal and abnormal PGs were 0.90 and 0.93, respectively. Recall and precision of the model were 89% each.

CONCLUSION

Visual artificial intelligence platforms may be used to compare the autofluorescence signal of a given parathyroid gland against a large database. This may be a new adjunctive tool for intraoperative assessment of parathyroid glands during surgical exploration for primary hyperparathyroidism.

An Atypical Presentation of Primary Hyperparathyroidism With Multiple Spontaneous Tendon Ruptures: A Case Report and Literature Review on the Management of Primary Hyperparathyroidism

Primary hyperparathyroidism (PHPT) is a common endocrine condition, increasingly presenting asymptomatically and detected on routine laboratory examination in developed countries. Multiple spontaneous tendon ruptures as the initial presentation of PHPT is extremely rare. We present the case of a 28-year-old male diagnosed with severe hypercalcemia secondary to PHPT after presenting with complications of multiple spontaneous tendon ruptures,and discuss the management issues in PHPT for this patient.