Cost Comparison of Genetic Testing Strategies in Women With Epithelial Ovarian Cancer.

Journal Article

The advent of multigene panels has increased genetic testing options for women with epithelial ovarian cancer (EOC). We designed a decision model to compare costs and probabilities of identifying a deleterious mutation or variant of uncertain significance (VUS) using different genetic testing strategies.A decision model was developed to compare costs and outcomes of two testing strategies for women with EOC: multigene testing (MGT) versus single-gene testing for BRCA1/2. Outcomes were mean cost and number of deleterious mutations and VUSs identified. Model inputs were obtained from published genetic testing data in EOC. One-way sensitivity analyses and Monte Carlo probabilistic sensitivity analyses were performed.No family history model: MGT cost $1,160 more on average than BRCA1/2 testing and identified an additional 3.8 deleterious mutations for every 100 women tested. For each additional deleterious mutation identified, MGT cost $30,812 and identified 5.4 additional VUSs. Family history model: MGT cost $654 more on average and identified an additional 7.0 deleterious mutations for every 100 women tested. For each additional deleterious mutation identified, MGT cost $9,909 and identified 2.6 additional VUSs.MGT was associated with a higher additional cost per deleterious mutation identified and a higher ratio of VUS burden to actionable information in women with no family history as compared with women with a family history. Family history should be considered when determining an initial genetic testing platform in women with EOC.

Duke Authors

Cited Authors

  • Foote, JR; Lopez-Acevedo, M; Buchanan, AH; Secord, AA; Lee, PS; Fountain, C; Myers, ER; Cohn, DE; Reed, SD; Havrilesky, LJ

Published Date

  • January 3, 2017

Published In

Start / End Page

  • JOP2016011866 -

PubMed ID

  • 28045615

Electronic International Standard Serial Number (EISSN)

  • 1935-469X

International Standard Serial Number (ISSN)

  • 1554-7477

Language

  • eng