Validation and Evaluation of 5 Scoring Systems for Predicting Metastatic Risk in Pheochromocytoma and Paraganglioma.

Abstract

Currently, 5 scoring systems have been proposed in the literature for predicting metastatic risk in pheochromocytoma and paraganglioma (PPGL): Pheochromocytoma of the Adrenal Gland Scaled Score (PASS), Grading System for Adrenal Pheochromocytoma and Paraganglioma (GAPP), Composite Pheochromocytoma/paraganglioma Prognostic Score (COPPS), Age, Size, Extra-adrenal location, Secretion type (ASES) score, and Size, Genetic, Age, and PASS (SGAP) model. To validate and evaluate these 5 scoring systems, we conducted a retrospective review of cases diagnosed as PPGL at the Department of Pathology, West China Hospital of Sichuan University, between January 2012 and December 2019. A total of 185 PPGL cases were included, comprising 35 cases with metastasis and 150 cases remained metastasis-free for over 8 years after surgery. The criteria of the 5 scoring systems were used for scoring and risk classification. The predictive performance of the 5 scoring systems was validated, compared, and evaluated using concordance index (C-index) and decision curve analysis (DCA). The C-indices for PASS, GAPP, and SGAP were 0.600, 0.547, and 0.547, respectively, indicating low discriminative ability. In contrast, COPPS and ASES had C-indices of 0.740 and 0.706, respectively, indicating better discriminative performance. DCA also showed that the predictive capability of COPPS was superior to that of ASES, with both outperformed PASS, while PASS had better predictive ability than GAPP and SGAP. Our analysis indicated that pathology-based scoring systems cannot accurately predict metastatic risk of PPGL. Establishing a precise prediction system requires integrating clinical, pathologic, and molecular information, using a scientific methodology for predictive factor selection and weight assessment.