A nomogram for predicting the presence of germline mutations in pheochromocytomas and paragangliomas

Purpose: Up to 40% of patients with pheochromocytomas or paragangliomas (PPGLs) carry a germline mutation. This study aimed to build a nomogram using clinical information to predict the probability of germline mutation in PPGLs. Methods: The data were collected from 563 patients who were diagnosed with PPGLs between 2002 and 2015. Clinical and pathologic features were assessed with a multivariable logistic regression analysis to predict the presence of germline mutations. A nomogram to predict the probability of germline mutation was constructed with R software. Discrimination and calibration were employed to evaluate the performance of the nomogram. Results: By multivariate analysis, age at manifestation, bilateral, or multifocal tumors and family history were identified as independent predictors of the presence of any germline mutation. The nomogram was then developed using these three variables. The nomogram showed an area under the receiver operating characteristic curve (AUC) of 0. 841 (95% confidence interval [CI], 0.809–0.871). The calibration plot indicated that the nomogram-predicted probabilities compared very well with the actual probabilities (Hosmer–Lemeshow test: P = 0.888). Conclusion: The nomogram is a valuable predictive tool for the presence of germline mutations in patients with PPGLs.