Primary hyperparathyroidism with normal baseline intraoperative parathyroid hormone: A challenging population

Area of Science:

• Endocrinology
• Surgical Oncology
• Parathyroid Disease Management

Background:

• Primary hyperparathyroidism (PHPT) management can be complex in patients with normal baseline intraoperative parathyroid hormone (IOPTH) levels.
• This specific patient subgroup presents unique diagnostic and therapeutic challenges.
• Accurate prediction of surgical cure is crucial for optimal patient outcomes.

Purpose of the Study:

• To compare the predictive accuracy of a standard IOPTH algorithm, a predictive software model, and surgeon judgment in PHPT patients with normal baseline IOPTH.
• To evaluate the effectiveness of different methods in predicting surgical cure for PHPT.
• To identify the most reliable method for assessing cure in challenging PHPT cases.

Main Methods:

• Retrospective review of consecutive patients undergoing parathyroidectomy for PHPT.
• Analysis of 114 patients with normal baseline IOPTH (≤69 pg/mL).
• Comparison of cure prediction accuracy using a 50% decline IOPTH algorithm, computer software, and surgeon judgment.

Main Results:

• Of 114 patients with normal baseline IOPTH, 99.1% achieved surgical cure.
• The 50% decline algorithm correctly predicted cure in 75.4% of cases.
• Computer software predicted cure in 77.2% of cases, while surgeon judgment was accurate in 99.1% of cases.
• A high incidence of multigland disease (58.8%) was observed in this cohort.

Conclusions:

• Standard IOPTH algorithms and software models are insufficient for predicting cure in PHPT patients with normal baseline IOPTH.
• Surgeon judgment, combined with operative findings, is the most accurate method for assessing cure in this population.
• Optimal management of PHPT in patients with normal baseline IOPTH requires integrating clinical expertise with biochemical and surgical data.