A Treatment Sequencing Model to Assess the Clinical and Economic Impact of BRCA Testing Within Prostate Cancer

OBJECTIVES: Testing for BRCA mutations within prostate cancer (PC) enables access to PARP inhibitors, leading to greater health benefits at the expense of higher treatment costs. However, the optimal time to test is not clear. A treatment sequencing model was developed to assess the clinical and economic impact of different testing points and treatment sequences within PC.

METHODS: A de novo health economic model was developed to compare multiple treatment pathways, from a French healthcare perspective. Six mutually exclusive health states were included: ‘locally advanced’ (LA), ‘biochemical recurrence’ (BCR), ‘metastatic hormone-sensitive PC’ (mHSPC), ‘first-line metastatic castration-resistant PC’ (L1 mCRPC), ‘second-line plus (L2+) mCRPC’ and ‘death’. Clinical endpoints from pivotal trials were utilised alongside epidemiological, cost, and health-related quality of life inputs. Outcomes in terms of costs, life years (LY), and budget impact were assessed over a lifetime horizon. Several scenarios were explored: including ‘early testing’, ‘late testing’ and ‘no testing’. Model assumptions were validated by clinical experts.

RESULTS: Testing early (mHSPC) for BRCA mutations led to greater health benefits (15.3 LY) than testing later in the disease (14.3 LY), or not testing at all (13.7 LY). However, total costs were highest when testing early (€346,734) compared to testing late (€209,378) or not testing (€95,733). This was mainly driven by higher treatment costs within mHSPC and mCPRC, with costs within LA and BCR health states remaining the same across scenarios. The total incremental budget impact over a lifetime horizon was €10,243 per patient in the ‘early testing’ versus ‘late testing’ scenario, and €23,799 per patient in the ‘early testing’ versus ‘no testing’ scenario.

CONCLUSIONS: Testing early for BRCA mutations (at diagnosis of metastases) enables greater survival benefits and more treatment options than testing too late or not at all. This should be balanced against the higher costs incurred by healthcare systems.