Precision stratified treatment of primary hyperparathyroidism (PHPT) based on multilevel emerging biomarkers

Xi Zhu¹qi zhang²Linghui Wang¹shuting xu¹enmei gong¹bin zhou¹yong wu¹zhouting li¹Yanjie Zhao¹shuhui li¹feng cheng¹Lei Zhu^1*

• ¹Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China
• ²Hangzhou Normal University, Hangzhou, China

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.