Economic evaluation of [18F]fluorocholine PET/CT in pre operative assessment of hyperfunctional parathyroids in primary hyperparathyroidism: a cost effectiveness analysis.
Background: Primary hyperparathyroidism (PHPT) is characterized by persistent hypercalcemia caused by parathyroid adenomas. Preoperative localization of hyperfunctional parathyroids is crucial to optimize surgical outcomes. Current standard practice combines cervical ultrasound (CU), [99mTc]Tc-sestaMIBI SPECT scintigraphy (MIBI), and [18F]Fluorocholine PET/CT (PET) centered on the cervico-thoracic region. This study evaluates the cost-effectiveness of PET as a stand-alone first-line imaging strategy compared to CU + MIBI + PET and CU + PET strategies in the French healthcare system.
Methods: A Markov model estimated costs and quality-adjusted life years (QALYs) for each imaging strategy. Imaging performance parameters were derived from a cohort of 145 PHPT patients who underwent surgery after all three imaging exams. Costs were calculated from the perspective of the French healthcare system, and utilities were sourced from the literature and validated by experts. Probabilistic and deterministic sensitivity analyses assessed robustness, while a Budget Impact Analysis (BIA) evaluated financial implications of national adoption over three years (2025-2027).
Results: The average costs per patient were €5175 for CU + MIBI + PET, €5406 for CU + PET, and €5320 for PET alone, with corresponding QALYs of 13.80, 13.81, and 13.82. PET alone had an incremental cost-effectiveness ratio (ICER) of €12,650/QALY and an incremental net monetary benefit (iNMB) of 855€ compared to CU + MIBI + PET but offered only marginal QALY gains (+ 0.02), which were not substantially different. Sensitivity analyses revealed PET alone becomes dominant if [99mTc]Tc-MIBI SPECT sensitivity falls below 75.5% or PET costs drop below €632.
Conclusions: [18F]Fluorocholine PET/CT stand-alone could be a cost-effective option and considered as a first line imaging strategy. Imaging strategies should be adapted to local healthcare contexts, reimbursement models, and diagnostic performance to optimize cost-effectiveness and patient care.