The Role of Baseline Bone Mineral Density in Predicting Skeletal Recovery Following Parathyroidectomy in Patients with Primary Hyperparathyroidism

Aim: Primary hyperparathyroidism (PHPT) adversely affects skeletal health, primarily through increased bone resorption. Parathyroidectomy (PTx) is the definitive treatment, but the extent of skeletal recovery and its predictive factors are not fully understood. This study aimed to assess the impact of PTx on bone mineral density (BMD) and to identify predictors of postoperative skeletal improvement. Methods: This retrospective cohort study included 65 patients with PHPT who underwent successful PTx at a single tertiary center between January 2018 and January 2024. We collected demographic, clinical, and biochemical data. BMD and T-scores were measured at the lumbar spine, femoral neck, total hip, and distal one-third radius using dual-energy X-ray absorptiometry (DXA) at baseline and 12 months postoperatively. Percentage changes in BMD were calculated. Correlations between BMD changes and preoperative demographic, biochemical, and DXA parameters were analyzed. Results: Significant improvements in BMD and T-score were observed at all sites one year after PTx, with the greatest increases in the lumbar spine and femoral neck (mean BMD increases of 10.33% and 10.43%, respectively; p < 0.001). Lower baseline BMD and T-score, especially at the one-third radius, were associated with greater postoperative gains. Adenoma size and PTH levels showed weak positive correlations with BMD changes, while 25-hydroxyvitamin D and phosphorus levels were inversely correlated in certain regions. Conclusions: PTx results in significant skeletal recovery in PHPT, with the most pronounced gains observed at trabecular-rich sites. Preoperative skeletal status, specifically at the one-third radius, serves as a valuable predictor of overall postoperative recovery. These findings support the importance of PTx in patients with PHPT and low bone mass and highlight the value of baseline skeletal status in predicting postoperative outcomes