Precision stratified treatment of primary hyperparathyroidism based on multilevel emerging biomarkers

Primary hyperparathyroidism (PHPT) is a clinically heterogeneous endocrine disorder whose management has historically been guided by biochemical profiles and symptomatic presentation. However, the limitations of conventional diagnostic and therapeutic strategies-including poor sensitivity in detecting subclinical organ damage and an inability to predict disease progression-have underscored the need for a more nuanced, biomarker-driven approach. Recent advances in multi-omics technologies, functional imaging, and artificial intelligence have enabled the emergence of precision medicine paradigms for PHPT. This review synthesizes evidence on the role of multilevel biomarkers-spanning genetic, epigenetic, non-coding RNA, metabolic, and imaging domains-in refining risk stratification and guiding individualized treatment. We further propose an integrated framework that combines dynamic biomarker profiling with multidisciplinary team (MDT)-based decision-making to facilitate personalized intervention pathways-from surgical planning to long-term surveillance. Despite promising developments, clinical translation remains challenged by the lack of standardized biomarker validation and integrative analytical platforms. Future efforts should prioritize collaborative networks and large-scale prospective studies to establish evidence-based guidelines for implementing precision medicine in PHPT.