Pseudohypoxia and family history are key predictors of severe outcomes in hereditary pheochromocytoma and paraganglioma syndromes.
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OBJECTIVE: Pheochromocytoma and paraganglioma (PPGL) have high genetic predisposition rates. In this multicenter study, we aimed to identify risk-modulating factors for disease development and aggressiveness in patients carrying pathogenic variants (PPGLgPV) related to PPGL genes. METHODS: Observational prospective study including patients with PPGL, family history of PPGL, or suspected PPGL-related hereditary syndrome. Patients underwent clinical and germline PPGLgPV evaluation. Machine-learning analyses were conducted to predict a patient's risk of carrying PPGLgPV, developing PPGL, and developing metastatic or multifocal disease. RESULTS: Of 221 patients (age 33.5 ± 19.9 years, 45.2% males), 143 (64.7%) patients harbored PPGLgPV, and 91 (41.2%) developed PPGL (46 pheochromocytoma, 45 paraganglioma/both, 29 multifocal/metastatic PPGL). Age at diagnosis of <41 years with a positive family history showed a 100% positive predictive value (PPV) for carrying PPGLgPV, compared to an 86% negative predictive value (NPV) when diagnosed at age >40 years with a solitary PPGL. Pseudohypoxia (PH)-related PPGLgPV carriers were younger at PPGL diagnosis and had an increased risk of multifocal/metastatic disease. Elevated catecholamine metabolites and PH-related PPGLgPV had 80% PPV for metastatic/multifocal disease, vs high NPV for non-elevated catecholamine metabolites with negative family history (100%) or non-PH gene alterations (91%). Patients with PV found incidentally had a lower PPGL risk compared with carriers screened due to a family member with PPGL (P = .026). CONCLUSIONS: Machine learning identified combined clinical and genetic characteristics for predicting hereditary PPGL syndromes, and multifocal/metastatic PPGL. This enables personalized risk stratification to guide genetic testing and surveillance in patients with PPGL and their relatives.