Multicenter evaluation of the PASS score as a negative predictive tool and the impact of inter-observer variability in pheochromocytoma and paraganglioma risk stratification

Journal of Pathology and Translational Medicine · Published 2026-02-23 · DOI 10.4132/jptm.2025.11.05

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Abstract

Background The Pheochromocytoma of the Adrenal Gland Scaled Score (PASS) is widely used for risk stratification in pheochromocytoma and paraganglioma (PPGL), but its clinical utility is limited by inter-observer variability of its parameters and inconsistent predictive performance. Methods We conducted a multicenter retrospective study of 1,518 patients with PPGL from five tertiary referral centers in Korea. Prognostic utility of PASS system was assessed using logistic regression, Kaplan-Meier analysis, and receiver operating characteristic (ROC) curve analysis. Inter-observer variability was inferred by comparing area under the ROC curve (AUCs) across institutions. Simplified PASS systems were developed based on multivariable analysis of key histopathological parameters. Results The PASS system was a significant predictor of adverse events and recurrence-free survival. Although the PASS system demonstrated only modest discriminative ability (AUC, 0.673), it showed a high negative predictive value (NPV, 0.885), supporting its usefulness as a screening tool for benign behavior. However, there was significant inter-institutional variability in PASS performance (AUC; range, 0.513 to 0.727; p < .05). The 3-factor Simple PASS, which incorporates necrosis, spindling, and mitotic figures, exhibited less inter-observer variation. The 4-factor Simple PASS, which adds vascular invasion to the 3-factor model, also showed reduced inter-observer variability and improved AUC and NPV compared to the original PASS system. Conclusions In this multicenter cohort, the PASS system demonstrated high NPV and screening potential, but significant inter-observer variability remains a challenge. Simplification of the PASS system and enhanced pathologist training may improve reproducibility and clinical utility in PPGL risk stratification.

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Publication details

Year
2026

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