Cost-effectiveness analysis of HRD testing for previously treated patients with advanced ovarian cancer in Italy

Introduction: Ovarian cancer (OC) is the eighth most common cancer among women, and homologous recombination deficiency (HRD) is present in approximately 50% of these patients. For this group, poly adenosine diphosphate-ribose polymerase (PARP) inhibitors are more likely to be effective. The aim of the study was to investigate the cost-effectiveness of HRD testing versus BRCA testing (which identifies mutations present only in 25% of patients) in Italy to optimize the treatment management, possibly with PARP inhibitors. Methods: A cost-effectiveness partition survival model was developed to estimate the expected costs and outcomes (life years – LYs, Quality-Adjusted Life Years – QALYs) with lifetime horizon of HRD testing versus BRCA testing alone in women with high-grade serous or endometrioid advanced ovarian cancer. The option to perform the tests in sequence, that is, the BRCA test followed by the HRD test, in patients with BRCA-negative test was also considered, and the model accounted for the National Healthcare Service (NHS) perspective in Italy. The treatments represented the best available options according to the initial test results and according to PARP inhibitors available in Italy. A 3% discount rate was applied. Both deterministic and probabilistic sensitivity analyses were performed to test the robustness of the model results. Results: HRD testing was shown to be a cost-effective strategy compared to BRCA testing (incremental cost-utility ratio=22,610€/QALY) and a cost-saving strategy compared to the sequence of tests. The probabilistic sensitivity analysis showed that the HRD test is cost-effective compared to BRCA testing in 98.5% of model simulations considering a Willingness-To-Pay threshold of 50,000€/QALY. Conclusion: The identification of genetic anomalies in patients with advanced OC is a costly process. Regardless, HRD upfront testing compared to BRCA testing had a cost-effective profile, allowing the efficient use of healthcare resources and better life expectancy and quality of life for patients.