Publication

Clinical predictors and algorithm for the genetic diagnosis of pheochromocytoma patients

Journal Paper/Review - Oct 13, 2009

Units
PubMed
Doi

Citation
Erlic Z, Fottner C, Forrer F, Plöckinger U, Petersenn S, Zabolotny D, Kollukch O, Yaremchuk S, Januszewicz A, Walz M, Eng C, Neumann H, Klose S, Opocher G, Rybicki L, Peçzkowska M, Golcher H, Kann P, Brauckhoff M, Müssig K, Muresan M, Schäffler A, Reisch N, Schott M, Fassnacht M, European-American Pheochromocytoma Study Group. Clinical predictors and algorithm for the genetic diagnosis of pheochromocytoma patients. Clin Cancer Res 2009; 15:6378-85.
Type
Journal Paper/Review (English)
Journal
Clin Cancer Res 2009; 15
Publication Date
Oct 13, 2009
Issn Print
1078-0432
Pages
6378-85
Brief description/objective

PURPOSE
Six pheochromocytoma susceptibility genes causing distinct syndromes have been identified; approximately one of three of all pheochromocytoma patients carry a predisposing germline mutation. When four major genes (VHL, RET, SDHB, SDHD) are analyzed in a clinical laboratory, costs are approximately $3,400 per patient. The aim of the study is to systematically obtain a robust algorithm to identify who should be genetically tested, and to determine the order in which genes should be tested.

EXPERIMENTAL DESIGN
DNA from 989 apparently nonsyndromic patients were scanned for germline mutations in the genes VHL, RET, SDHB, SDHC, and SDHD. Clinical parameters were analyzed as potential predictors for finding mutations by multiple logistic regression, validated by bootstrapping. Cost reduction was calculated between prioritized gene testing compared with that for all genes.

RESULTS
Of 989 apparently nonsyndromic pheochromocytoma cases, 187 (19%) harbored germline mutations. Predictors for presence of mutation are age <45 years, multiple pheochromocytoma, extra-adrenal location, and previous head and neck paraganglioma. If we used the presence of any one predictor as indicative of proceeding with gene testing, then 342 (34.6%) patients would be excluded, and only 8 carriers (4.3%) would be missed. We were also able to statistically model the priority of genes to be tested given certain clinical features. E.g., for patients with prior head and neck paraganglioma, the priority would be SDHD>SDHB>RET>VHL. Using the clinical predictor algorithm to prioritize gene testing and order, a 44.7% cost reduction in diagnostic process can be achieved.

CONCLUSIONS
Clinical parameters can predict for mutation carriers and help prioritize gene testing to reduce costs in nonsyndromic pheochromocytoma presentations.