Cost-Effectiveness of Targeted Genetic Testing for Breast and Ovarian Cancer: A Systematic Review.

ABSTRACT

BACKGROUND: Targeted genetic testing is a tool to identify women at increased risk of gynaecological cancer. OBJECTIVE: This systematic review evaluates the results and quality of cost-effectiveness modeling studies that assessed targeted genetic-based screen-and-treat strategies to prevent breast and ovarian cancer. METHODS: Using MEDLINE and databases of the Centre for Reviews and Dissemination, we searched for health economic modeling evaluations of targeted genetic-based screen-and-treat strategies to prevent inheritable breast and ovarian cancer (until August 2020). The incremental cost-effectiveness ratios (ICERs) were compared. Methodological variations were addressed by evaluating the model conceptualizations, the modeling techniques, parameter estimation and uncertainty, and transparency and validation of the models. Additionally, the reporting quality of each study was assessed. RESULTS: Eighteen studies met our inclusion criteria. From a payer perspective, the ICERs of (1) BRCA screening for high-risk women without cancer ranged from dominating the no test strategy to an ICER of $21 700/quality-adjusted life years (QALY). In studies that evaluated (2) BRCA cascade screening (ie, screening of women with cancer plus their unaffected relatives) compared with no test, the ICERs were between $6500/QALY and $50 200/QALY. Compared with BRCA alone, (3) multigene testing in women without cancer had an ICER of $51 800/QALY (one study), while for (4) multigene-cascade screening the ICERs were $15 600/QALY, $56.500/QALY, and $69 600/QALY for women in the United Kingdom, Norway, and the United States, respectively (2 studies). More recently published studies showed a higher methodological and reporting quality. CONCLUSIONS: Targeted BRCA or multiple gene screening is likely to be cost-effective. Methodological variations could be decreased by the development of a reference model, which may serve as a tool for validation of present and future cost-effectiveness models.