Clinical predictors for germline mutations in head and neck paraganglioma patients: cost reduction strategy in genetic diagnostic process as Fall-Out - Neumann, Hartmut P. H.; Erlic, Zoran; Boedeker, Carsten C.; Rybicki, Lisa A.; Robledo, Mercedes; Hermsen, Mario; Schiavi, Francesca; Falcioni, Maurizio; Kwok, Pingling; Bauters, Catherine; Lampe, Karen; Fischer, Markus; et al. (Cancer research, 2009)
Multiple genes and their variants that lend susceptibility to many diseases will play a major role in clinical routine. Genetics-based cost reduction strategies in diagnostic processes are important in the setting of multiple susceptibility genes for a single disease. Head and neck paraganglioma (HNP) is caused by germline mutations of at least three succinate dehydrogenase subunit genes (SDHx). Mutation analysis for all 3 costs ∼US$2,700 per patient. Genetic classification is essential for downstream management of the patient and preemptive management of family members. Utilizing HNP as a model, we wanted to determine predictors to prioritize the most heritable clinical presentations and which gene to begin testing in HNP presentations, to reduce costs of genetic screening. Patients were tested for SDHB, SDHC, and SDHD intragenic mutations and large deletions. Clinical parameters were analyzed as potential predictors for finding germline mutations. Cost reduction was calculated between prioritized gene testing compared with that for all genes. Of 598 patients, 30.6% had SDHx germline mutations: 34.4% in SDHB, 14.2% SDHC, and 51.4% SDHD. Predictors for an SDHx mutation are family history [odds ratio (OR), 37.9], previous pheochromocytoma (OR, 10.9), multiple HNP (OR, 10.6), age ≤40 years (OR, 4.0), and male gender (OR, 3.5). By screening only preselected cases and a stepwise approach, 60% cost reduction can be achieved, with 91.8% sensitivity and 94.5% negative predictive value. Our data give evidence that clinical parameters can predict for mutation and help prioritize gene testing to reduce costs in HNP. Such strategy is cost-saving in the practice of genetics-based personalized health care. [Cancer Res 2009;69(8):3650-6]
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