Abstract
To estimate the cost-effectiveness of niraparib, a poly (ADP-ribose) polymerase (PARP) inhibitor, compared with routine surveillance (RS) and olaparib for the maintenance treatment of patients with recurrent ovarian cancer. A decision-analytic model estimated the cost per quality-adjusted life-year (QALY) gained for niraparib versus RS and olaparib from a US payer perspective. Recurrent ovarian cancer patients with or without germline BRCA mutation, who were responsive to their last platinum-based chemotherapy regimen, entered the model (non-gBRCAmut, gBRCAmut). The model had three health states; progression-free disease, progressed disease and dead. For both non-gBRCAmut and gBRCAmut populations, mean progression-free survival (PFS) was estimated for niraparib and RS using parametric survival distributions based on ENGOT-OV16/NOVA (Niraparib Phase III trial). For non-gBRCAmut, olaparib PFS was estimated from Study 19 (Olaparib Phase II trial). For gBRCAmut, a cost-minimisation analysis was conducted for niraparib versus olaparib. Due to the immaturity of OS data in ENGOT-OV16/NOVA, mean OS benefit was estimated from the Study 19 RS arm, as double the mean PFS benefit for both niraparib and olaparib. Costs included; drug, subsequent chemotherapy, monitoring, adverse events, and terminal care. Quality-of-life was captured using EQ-5D. A 3.00% discount rate per annum was used. Treatment with niraparib increased costs and QALYs compared to RS, resulting in an incremental cost-effectiveness ratio of $94,186 and $58,804, for non-gBRCAmut and gBRCAmut, respectively. Niraparib dominated olaparib in both populations, with a cost difference of -$60,400 and similar QALYS in gBRCAmut, and a cost difference of -$55,858 and incremental QALYs of 1.437 in non-gBRCAmut. This cost decrease was driven by lower monthly drug costs for niraparib compared with olaparib based on average dose. These estimates indicate that niraparib dominates olaparib and falls within an acceptable cost-effectiveness range versus RS. Mature OS data is required to validate these findings.
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