Comment on: “Cost-Effectiveness of Niraparib Versus Routine Surveillance, Olaparib and Rucaparib for the Maintenance Treatment of Patients with Ovarian Cancer in the United States”

Abstract

We read with interest the article by Guy et al. [1] detailing a cost-effectiveness model comparing niraparib, a poly(ADPribose) polymerase inhibitor (PARPi), to routine surveillance and two other PARPis approved for maintenance treatment of recurrent ovarian cancer, olaparib and rucaparib. The authors concluded from their analysis that niraparib was less expensive and more cost effective than olaparib and rucaparib, and the incremental cost-effectiveness ratio (ICER) fell within an acceptable range compared to routine surveillance. However, we noted several fundamental problems with the lack of comparability of populations, as well as methodological flaws and violations of statistical assumptions within the model. Although we found the authors’ methods flawed overall, in this letter, we comment only on the main problems with the comparison between niraparib and rucaparib. The authors mention that the analysis of niraparib vs. rucaparib is “a naïve side-by-side comparison” of results from the ENGOT-OV16/NOVA study for niraparib [2] and the ARIEL3 study for rucaparib [3]. A naïve indirect comparison or analysis of two treatment groups as if they were from a single trial without adjustment for potential betweentrial variability is not a recommended method of analysis because the homogeneity assumption is nearly impossible to meet [4]. For the homogeneity assumption to be met, the groups being compared should not have been selected with different inclusion/exclusion criteria or undergone data collection via different methodologies [4]. Throughout their paper, the authors violate this assumption, rendering the model and results invalid. First, the niraparib and rucaparib populations analyzed within the cost-effectiveness model are dissimilar. Somatic BRCA -mutant (BRCA mut) patients were included in the “non-germline BRCA (non-gBRCA )” group for the niraparib data [2], but they were classified in the BRCA mut group for the rucaparib data [3]. This dissimilarity leads to bias in assessing efficacy because somatic BRCA mut patients have been shown to respond comparably to gBRCA mut patients (and better than wild-type BRCA patients) in the maintenance and treatment settings of recurrent ovarian cancer [2, 3, 5, 6]. For the non-gBRCA group, the median progression-free survival (mPFS) of 9.3 months based on a blinded independent central review (BICR) was used for niraparib, whereas a weighted average of the wild-type BRCA /genomic high loss of heterozygosity and wild-type BRCA /loss of heterozygosity low mPFS numbers (8.2 months) was used for rucaparib because ARIEL3 did not report a mPFS for nongBRCA patients at the time of the primary analysis. These data have been reported recently for rucaparib [7] and show higher mPFS for the non-gBRCA population (11.1 months for BICR-assessed mPFS and 8.6 months for investigatorassessed mPFS) than that calculated by Guy et al. [1]. Furthermore, the efficacy assessments used for the model are also not comparable. Their model included the BICRassessed mPFS for niraparib gBRCA (21.0 months) [2] vs. investigator-assessed mPFS (16.6 months) for rucaparib [3]. In three phase III studies investigating PARPis for maintenance treatment of recurrent ovarian cancer, mPFS was longer in BICR-assessed than investigator-assessed progression-free survival (PFS) [2, 3, 8]. Moreover, results from these three studies demonstrate that inconsistency in efficacy assessments used in the model by Guy et al. leads to bias in This comment refers to the article available at https ://doi. org/10.1007/s4027 3-018-0745-z.