Correction to: Updates in Genetic Testing Guidelines for Breast Cancer Susceptibility Genes: a Change in the Paradigm

A Correction to this paper has been published: 10.1007/s12609-021-00425-z

Burden of genetic testing in an academic biobank by pathological and family history-based criteria in prostate cancer (PCa).

1576 Background: Approximately 5% of localized PCa and 12% of metastatic PCa are associated with germline mutations in DNA repair genes. The National Comprehensive Cancer Network (NCCN) issued genetic testing guidelines to identify PCa patients (pts) likely to harbor a germline DNA repair mutation. The overall burden of this guideline-based, resource-intensive genetic testing is unknown. Using supervised phenotype-genotype information extraction algorithms, we determined the projected genetic testing burden at a single institution adhering to NCCN PCa genetic testing guidelines. Methods: A PCa cohort of 2127 pts was identified from the Penn Medicine BioBank via ICD 9/10 codes. Phenotypic data were extracted from the Penn Medicine Cancer Registry and electronic health record systems via natural language processing and manual chart review. Pts were classified based on 9 germline genetic testing criteria outlined in the NCCN PCa guidelines (Version 4.2019). Results: 895/2127 pts met at least 1 of the 9 NCCN genetic testing criteria, corresponding to a 42.1% overall genetic testing burden. 35.2% qualified for testing via high-risk localized PCa and 6.4% qualified via metastatic disease. Of the pts with localized PCa (n=2014), 15.1% qualified for genetic testing via high Gleason score, 5.1% via high-risk family history, 3.7% via PSA>20ng/mL, 8.7% via Ashkenazi Jewish descent, and 0.8% via intraductal/ductal histology. Conclusions: In this single-center PCa cohort, germline genetic testing was NCCN-guideline recommended for a larger proportion of pts than would otherwise be expected based on previously published reports. Future studies are needed to validate the sensitivity and specificity of these criteria for identifying germline mutations. Our study also highlights a need for novel methods to improve the efficiency of genetic testing for a large cohort. [Table: see text]