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Establishment and evaluation of a novel biomarker‐based nomogram for malignant phaeochromocytomas and paragangliomas
Author(s) -
Zhong Xu,
Ye Lei,
Su TingWei,
Xie Jing,
Zhou Weiwei,
Jiang Yiran,
Jiang Lei,
Ning Guang,
Wang Weiqing
Publication year - 2017
Publication title -
clinical endocrinology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.055
H-Index - 147
eISSN - 1365-2265
pISSN - 0300-0664
DOI - 10.1111/cen.13357
Subject(s) - nomogram , medicine , paraganglioma , oncology , receiver operating characteristic , logistic regression , confidence interval , area under the curve , biomarker , metastasis , malignancy , sdhb , pathology , radiology , cancer , biology , mutation , germline mutation , gene , biochemistry
Summary Objective No single histological or molecular marker is diagnostic for malignant phaeochromocytomas and paragangliomas ( PPGL s). This study aimed to establish and evaluate a prognostic nomogram to improve the prediction of metastatic probability in individual PPGL patients. Methods Three hundred and 47 consecutive PPGL patients from January 2002 through December 2014 were randomly divided into a training set (n=208) and a validation set (n=139). A multivariate logistic regression analysis of selected prognostic features was performed, and a nomogram to predict metastasis was constructed. Discrimination and calibration were employed to evaluate the performance of the nomogram. Clinical usefulness was calculated using decision curve analysis. Results The overall metastatic rate was 10.6%. Primary tumour size, primary tumour location, vascular invasion, ERBB ‐2 overexpression, SDHB mutation and catecholamine type were associated with malignancy in the logistic analysis and were included in the nomogram. The nomogram showed an area under the receiver operating characteristic curve ( AUC ) of 0.872 (95% confidence interval [ CI ], 0.819‐0.914) in the training set. The validation set showed good discrimination, with an AUC of 0.870 (95% CI , 0.803‐0.921). The nomogram was well calibrated, with no significant difference between the predicted and the observed probabilities (Hosmer‐Lemeshow test: P =.510 for the training set; .314 for the validation set). Decision curve analysis revealed that molecular markers ( ERBB ‐2 overexpression and SDHB mutation) could increase the clinical benefit of the nomogram. Conclusion Our results support the use of the present biomarker‐based nomogram, which has good discriminative ability, to predict the metastatic probability of PPGL s.