Introduction
Prostate cancer is the most diagnosed non-skin cancer and second leading cancer-related cause of mortality in Australian men (1). Approximately 3,568 deaths due to prostate cancer were reported in 2020 (1). Between 4.6 and 17 percent of patients with prostate cancer have mutations in germline DNA-repair genes (Reference Giri, Hyatt and Gomella2;Reference Nicolosi, Ledet and Yang3). The prevalence of pathogenic variants is substantially higher in metastatic prostate cancer (11.8 percent) (Reference Pritchard, Mateo and Walsh4) compared to local prostate cancer (4.6 percent) (5). In addition, more than half of mutations in metastatic prostate cancer are in the BRCA genes (BRCA2: 44 percent, BRCA1: 7 percent) (Reference Pritchard, Mateo and Walsh4).
Prostate cancer patients with BRCA mutations have a more aggressive form of disease with higher risk of nodal involvement, distant metastasis, and poor overall survival (Reference Castro, Goh and Olmos6;Reference Gallagher, Gaudet and Pal7). Despite the grim prognosis, poly-adenosine diphosphate ribose polymerase (PARP) inhibitors have shown promising results in the treatment of metastatic castration resistant prostate cancer (mCRPC). These drugs are selective for homologous DNA repair mutations (Reference Rose, Burgess, O’Byrne, Richard and Bolderson8). The PARP inhibitors olaparib (Reference de Bono, Mateo and Fizazi9) and rucaparib (Reference Abida, Patnaik and Campbell10) are FDA approved and recommended for BRCA positive mCRPC patients who had prior treatment with novel hormonal agents (NHAs) such as abiraterone or enzalutamide or taxanes (e.g., docetaxel and cabazitaxel). Rucaparib, however, is not TGA approved for use in Australia (11).
Three studies (Reference Li, Lin and Zhong12-Reference Xu, Cai and Zhuang14) have examined the cost-effectiveness of PARP therapy in mCRPC and there is considerable variation in the reported results. The study by Su et al. (Reference Su, Wu and Shi13) showed that olaparib was cost-effective; however, the results from the other two studies (Reference Li, Lin and Zhong12;Reference Xu, Cai and Zhuang14) suggested that treatment with olaparib was not value for money. All three studies (Reference Li, Lin and Zhong12-Reference Xu, Cai and Zhuang14) considered the cost of testing but did not account for the codependent nature of olaparib therapy (i.e., overlooked the fact that treatment decision with the drug was conditional on testing results). Additionally, some of the studies used a partitioned modeling approach which has several limitations including, the inability to account for transitions between health states, reliance on proxy measures to define health states, failure to account for the dependence of survival on effects from other treatments, and an overall tendency for poor predictability beyond the trial period (Reference Woods, Sideris, Palmer, Latimer and Soares15). Also, the study by Xu et al. (Reference Xu, Cai and Zhuang14) indicated that the cost-effectiveness of olaparib could vary based on the country or setting. In summary, existing studies (Reference Li, Lin and Zhong12-Reference Xu, Cai and Zhuang14) relied heavily on data from the PROfound trial (Reference de Bono, Mateo and Fizazi9), used partitioned modeling (Reference Su, Wu and Shi13) and did not consider the companion nature or dependence of treatment decisions on genetic testing. Given these shortcomings, we aim to evaluate the cost-effectiveness of olaparib therapy in mCRPC compared to the standard care alternative (Reference George, Sartor and Miller16) from an Australian health system perspective, after considering the codependent nature of the technologies (BRCA testing and olaparib treatment) and utilizing a state transition modeling approach.
Materials and methods
Model description
The model evaluated the cost-effectiveness of germline testing for BRCA variants (BRCA1 and BRCA2) to inform olaparib treatment in a hypothetical cohort of men with mCRPC, who had disease progression while receiving first-line treatment with a NHA, abiraterone or enzalutamide. Disease progression in the cohort signifies, biochemical (i.e., three consecutive rises of prostate specific antigen, 1 week apart with a 50 percent increase over the nadir or a prostate specific antigen level > 2 ng/ml) or radiological progression (i.e., appearance of two or more bone lesions) while having castrate levels of testosterone (i.e., levels <50 ng/dl or 1.7 nmol/l). A decision tree of germline BRCA testing versus no testing followed by a Markov multi-health state transition model was developed using TreeAge Pro (TreeAge Software, Williamstown, MA, USA) (17).
The structure of the model is presented in Figure 1. All hypothetical patients in the cohort are eligible for germline testing (18). The BRCA positive patients receive treatment with the PARP inhibitor olaparib. Upon treatment patients were expected to be in one of three health states: progression-free, progressed disease or dead. Patients who progressed while on olaparib were assumed to receive subsequent treatment with docetaxel for a maximum of four cycles, and supportive care thereafter. The ceiling of 4 months for docetaxel was established from typical patterns of treatment with the drug in mCRPC patients (Reference Pollard, Moskowitz, Diefenbach and Hall19;Reference Tannock, de Wit and Berry20). The choice for olaparib (as second-line treatment in BRCA positive patients) and docetaxel (third-line treatment) was based on practice recommendations in patients with mCRPC (18;Reference Parker, Castro and Fizazi21). The BRCA negative patients, as well as all patients in the no testing pathway were assumed to receive second-line treatment with a second NHA, that is, patients with prior treatment with abiraterone receive enzalutamide and vice versa (Reference Parker, Castro and Fizazi21). The proportion of patients receiving second-line enzalutamide (45 percent) or abiraterone (55 percent) was derived from the PROfound trial (Reference de Bono, Mateo and Fizazi9). Similar to BRCA positive patients with disease progression while on olaparib, patients on NHA in the comparator (i.e., no germline testing), were assumed to receive further treatment with docetaxel followed by supportive care. For simplification (i.e., similarity to the BRCA negative arm), the decision tree for the comparator has not been included in Figure 1. Please refer to Supplementary Material for a more detailed overview. The Markov health states (progression-free, progressed, and dead) for patients are similar in both the BRCA testing and no testing pathways and have been provided in the top-left corner of Figure 1.
Figure 1. Schematic of the model.
Model inputs
A summary of the parameters used in the model is provided in Table 1. The prevalence of BRCA variants in metastatic prostate cancer is variable (6–14 percent) (Reference Pritchard, Mateo and Walsh4;Reference Robinson, Van Allen and Wu22). For our base case analysis, we chose a BRCA positive probability of 10 percent, based on a Medical Services Advisory Committee (MSAC) of Australia evaluation (23). The probabilities for disease progression while receiving olaparib were derived from a subset of BRCA positive patients receiving the drug in the PROfound trial (Reference de Bono, Mateo and Fizazi9). Given the maturity of the overall survival data (Reference Hussain, Mateo and Fizazi24), we did not perform extrapolation using alternative parametric distributions and instead used the exponential distribution to estimate transition probabilities (S[t] = e -λt ; S = survival at time, t; λ = average number of events in time, t) (17). Disease progression with NHA in variant negative patients was modeled based on the study by Shore et al. (Reference Shore, Laliberté and Ionescu-Ittu25). Carriers of BRCA variants typically have more aggressive disease progression (Reference Castro, Goh and Olmos6). Therefore, despite the same treatment (i.e., second-line NHA), for all patients in the no testing strategy, we assumed faster disease progression in patients who harbor BRCA variants and as such used progression rates with NHA reported for this subset of the cohort from the PROfound trial (median = 3.0 months) (Reference de Bono, Mateo and Fizazi9). Background mortality rates were obtained from the Australian Bureau of Statistics (26). Mortality in patients on salvage therapy with docetaxel and supportive care was assumed to be similar across the two arms and was obtained from the study by Miyake et al. (Reference Miyake, Sato and Watanabe27). The frequencies of serious adverse events (grade ≥ 3) in patients receiving treatment with NHA or olaparib was obtained from the PROfound trial (Reference de Bono, Mateo and Fizazi9), while results from the TAX 327 trial (Reference Tannock, de Wit and Berry20) were used for adverse events associated with docetaxel.
Table 1. Summary of parameters used in the model
* Converted to 2021 AU$ where necessary using the Campbell and Cochrane Economics Methods Group (CCEMG) cost converter (37).
Costs
Costs for germline genetic testing (28), pre-and-post-test genetic counseling (29) were obtained from the Medicare Benefits Schedule (items 73304, 132). Treatment costs for the NHAs (abiraterone: 1,000 mg/day along with prednisone 5 mg/twice daily, AU$ 115/dose; enzalutamide: 160 mg/day, AU$ 126/dose), olaparib (300 mg/twice daily, AU$ 237 per dose), and docetaxel (75 mg/m2 every 3 weeks along with prednisone 5 mg/day, AU$ 161 per month) were obtained from the Pharmaceutical Benefits Scheme (items 11206T, 1935W, 10174L, and 10148D) (30-34). Costs for treatment of grade III adverse events were obtained from studies by Barqawi et al. (Reference Barqawi, Borrego, Roberts and Abraham35) and Roeland et al. (Reference Roeland, Nipp and Ruddy36) and converted to 2021 Australian dollars using the Campbell and Cochrane Economics Methods Group (CCEMG) cost converter (37).
Utilities
The utility weights for the progression-free state while receiving NHA (0.76; CI: 0.69–0.78) was based on findings for mCRPC patients receiving abiraterone therapy in the study by Clarke et al. (Reference Clarke, Hunter and Gabrio38). We assumed similar utility for olaparib treatment. Utility weights for docetaxel (0.69; CI: 0.59–0.80) and post-docetaxel (supportive care in the current model) (0.37; CI: 0.33–0.41) were obtained from studies by Lloyd et al. (Reference Lloyd, Kerr, Penton and Knerer39) and Barqawi et al. (Reference Barqawi, Borrego, Roberts and Abraham35). Disutility weights of grade III adverse events (anemia, fatigue, vomiting, and back pain) were obtained from studies by Barqawi et al. (Reference Barqawi, Borrego, Roberts and Abraham35) and Hall et al. (Reference Hall, de Freitas and Kerr40). The values for utility weights in the aforementioned studies were derived from patient responses to the EuroQoL-5D (41;Reference Al-Batran, Hozaeel and Tauchert42).
Analysis
The cost-effectiveness analysis was performed from the Australian health system perspective. We used monthly cycles to estimate the costs and outcomes were expressed in quality-adjusted life-years (QALYs) gained over a 5-year time horizon, typical of the mCRPC population (Reference Aly, Leval and Schain43-Reference Modonutti, Majdalany and Corsi45). The incremental cost effectiveness ratio (ICER) was calculated and in line with Australian guidelines (46), costs and outcomes were discounted at an annual discount rate of 5 percent.
Decision uncertainty was characterized using probabilistic sensitivity analysis. Parameters were assigned plausible distributions, and a set of input parameter values were drawn by random sampling (10,000 iterations) from each distribution. Probabilistic sensitivity analysis outcomes were used to estimate value of information including the Expected Value of Perfect Information (EVPI) using the nonparametric regression approach (Reference Strong, Oakley and Brennan47;Reference Tuffaha, Strong, Gordon and Scuffham48). Additionally, several one-way sensitivity analyses adjusting for the spread of model parameters were performed. The range of probable values for each parameter was derived from reported values in the original resource article and where information was not available, we assumed a 20 percent change from base-case value. Apart from the base-case analysis which uses expected summary statistics for model parameters (Table 1), we also performed scenario analyses for varying BRCA prevalence (6.2 percent (Reference Pritchard, Mateo and Walsh4), 14.0 percent (Reference Robinson, Van Allen and Wu22)), uptake of germline testing (Reference Hamilton, Symecko and Spielman49;Reference Scheinberg, Goodwin and Ip50) and also explored the price threshold of olaparib to arrive at cost-effective findings. In the absence of an official cut-off for WTP in Australia, the National Institute of Health and Clinical Excellence (NICE) threshold for appraisal of life-extending, end of life treatments was used to serve as a guideline for a cost-effectiveness ceiling and the WTP was evaluated at AU$ 100,000/QALY (51).
The conceptual/face validity of the model was confirmed by experts, that is, practicing clinical oncologists. Validity of the computerized model was affirmed by the coauthors (H.T. and P.S.) who are experienced health economists. Additionally, Markov traces of the health states for BRCA positive patients, BRCA carriers and BRCA negative/noncarriers across the time horizon have been provided in Supplementary S2–S4.
Finally, a Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist of the key items in the study was also performed and is available online.
Results
The results of the base-case analyses have been presented in Table 2. Compared to the standard care pathway, BRCA testing-guided olaparib treatment was associated with an additional cost of AU$ 7,841 and a gain of 0.06 QALYs. The resulting incremental cost-effectiveness ratio (ICER) of AU$ 143,613 per QALY for the BRCA testing pathway was substantially higher than the WTP threshold, suggesting that olaparib therapy was not cost-effective at its public price. At AU$ 100,000 WTP threshold, the probability that BRCA testing guided treatment is cost-effective was 1.7 percent. The cost-effectiveness acceptability curves, demonstrating the likelihood of germline testing being cost-effective, have been provided in Figure 2. The EVPI per person was AU$ 6.45 which is AU$ 138,255 for the population affected by the decision over 5 years, assuming the annual incidence of mCRPC is 4,286 patients each year. (52). The parameter contributing most to uncertainty was olaparib cost, with a population expected value of partially perfect information (EVPPI) of AU$ 88,169. The one-way sensitivity analysis (Figure 3) demonstrates that cost of olaparib, PFS during olaparib treatment, PFS with NHA in potential BRCA positive patients receiving standard care, the utility weights for NHA/olaparib treatment and the probability of being BRCA positive upon testing were the top five parameters influencing the ICER. The costs of adverse events (grade ≥ 3 or higher) in the cancer setting are substantial (Reference Wong, Yim and Kim53), yet they did not have a substantial impact on the results. There was a considerable shift in base case estimates over the range of plausible values for some variables (e.g., cost of olaparib), yet the ICERs remained higher than the WTP thresholds.
Table 2. Results of cost-effectiveness analysis
* Willingness to pay (WTP): AU$ 100,000/QALY.
Abbreviations: PSA, probabilistic sensitivity analysis; QALYs, quality-adjusted life-years; Rx, treatment.
Figure 2. Cost-effectiveness acceptability curves for BRCA testing-guided therapy versus standard care in the base case model.
Figure 3. Tornado diagram of one-way sensitivity analyses of olaparib versus standard care in the base case analysis.
Supplementary analyses explored the cost-effectiveness of personalized treatment using BRCA prevalence rates of 6.2 percent (Reference Pritchard, Mateo and Walsh4) and 14.0 percent (Reference Robinson, Van Allen and Wu22). Using the lower prevalence rate resulted in an ICER of AU$ 155,211/QALY, while the higher rate led to an ICER of AU$ 138,207/QALY. Uptake of germline testing in prostate cancer is usually high (90–95 percent) (Reference Hamilton, Symecko and Spielman49;Reference Scheinberg, Goodwin and Ip50) and was therefore not considered in our base case analysis. However, if we were to the use the lower statistic among the two studies (Reference Hamilton, Symecko and Spielman49;Reference Scheinberg, Goodwin and Ip50) (i.e., assume a 10 percent decline in BRCA testing), the resulting ICER of AU$ 144,990/QALY, was a marginal increase from our base case findings (ICER: AU$ 143,613/QALY).
We also examined the effects of applying additional discounts on olaparib pricing. As illustrated in Figure S5 in the Supplementary Material and Table 1, a 30 percent discount on olaparib cost was required to achieve an ICER below 100,000 (AU$ 93,646/QALY).
Discussion
The economics of codependent technologies such as genetic testing to identify patients that respond effectively to personalized medication is an emerging field of research (54;Reference Merlin, Farah and Schubert55). In the current study, we examined the cost-effectiveness of germline BRCA test guided treatment with the PARP inhibitor olaparib in mCRPC patients compared to the standard care alternative without germline testing. Our results suggest that olaparib therapy could be beneficial with an increase of 0.06 QALYs over the comparator but was not cost-effective (ICER: AU$ 143,613/QALY; WTP: AU$ 100,000/QALY), unless the price of the drug was further discounted by 30 percent (i.e., from AU$ 6,631/month to $ 4,642/month).
Our findings are plausible and could be explained by several factors. To begin, our modeling approach is coincidentally similar to the NICE guidance for olaparib for previously treated BRCA mutation-positive hormone relapsed metastatic prostate cancer (56). In our analysis, the price of olaparib (34) was 87.5–91.8 percent higher than the current standard of care options (i.e., the two NHAs, enzalutamide (33) or abiraterone (30) and as indicated by our one-way sensitivity analyses, was associated with the highest variance in ICERs. Additionally, men treated with olaparib demonstrated higher PFS compared to NHA in the standard care pathway and in essence were on the more expensive treatment for a longer duration (Reference de Bono, Mateo and Fizazi9). Although it was assumed that they accrued health benefits as they remained at this stage of treatment, the balance between increased cost of treatment and its health benefits (QALYs), was not sufficient to tip the scale below the WTP threshold. The prevalence of tested pathogenic variants could have also influenced the results (Reference Su, Wu and Shi13). The study by Su et al. (Reference Su, Wu and Shi13) demonstrated that olaparib was cost-saving when administered to men with any one of fifteen pathogenic variants (100 percent of their cohort) but had high ICERs when evaluated in a smaller subset of people positive to three of the fifteen variants (65 percent of their cohort). In summary, cost of olaparib treatment, PFS with olaparib, the health utility of remaining in this stage of treatment and the probability of being variant positive were some of the major factors influencing the cost-effectiveness of olaparib treatment.
There are several differences both in the methodology and magnitude of results from our analyses and the earlier studies (Reference Li, Lin and Zhong12-Reference Xu, Cai and Zhuang14). First, all three previous studies relied heavily on data from the PROfound trial (Reference de Bono, Mateo and Fizazi9), where PFS with olaparib was compared against NHA in men who were variant positive. The co-dependence of olaparib therapy on the results of germline testing was not assessed, that is, the decision tree did not include men who were variant negative or those that received standard care without genetic testing. In contrast, we employed a more appropriate design and considered the cost-effectiveness of treatment pathways based on germline testing compared to a no testing approach. The importance of inclusion of price of genetic testing in appraising cost-effectiveness was emphasized by NICE in its evaluation report of olaparib (NICE TA 887) (56) Section 3.21, “The costs of testing BRCA mutations should be included in the cost-effectiveness estimates.” In Australia, testing to inform the eligibility for olaparib treatment is currently subsidized by the MBS, yet prices continue to remain substantial at AU$ 1,000. Second, there were also differences in the number of variants assessed during testing in our approach and the previous studies. While they (Reference Li, Lin and Zhong12-Reference Xu, Cai and Zhuang14) assessed three or fifteen pathogenic variants, we limited our analyses to germline testing of BRCA1/2, the pathogenic variants listed for subsidized treatment with olaparib in Australia (34). Not all pathogenetic variants associated with prostate cancer have the same mutagenic potential, that is, penetrance and a previous expert panel consensus recommendation has advocated for priority testing of BRCA2/1 and DNA mismatch repair (MMR) genes over other variants (Reference Giri, Knudsen and Kelly57). The PARP inhibitors such as olaparib are also more efficacious in treating patients with homologous double-stranded DNA-repair (Reference Antonarakis, Gomella and Petrylak58), the primary impairment mechanism of cancers associated with BRCA mutations (Reference Roy, Chun and Powell59), further justifying our strategy for BRCA1/2 testing. Third, cross-resistance is known phenomenon between taxanes, NHAs, and PARP inhibitors (Reference Lombard, Liu and Armstrong60;Reference van Soest, van Royen and de Morrée61), and the sequence of treatment among these classes of drugs could have important implications on their effectiveness (Reference Lombard, Liu and Armstrong60;Reference van Soest, van Royen and de Morrée61). The lines of treatment in the economic modeling of previous studies was unclear (Reference Li, Lin and Zhong12;Reference Su, Wu and Shi13). We adopt a more practice-based line of treatment (18;Reference Cornford, van den Bergh and Briers62) likely to minimize the effect of cross-resistance (Reference Maurice Dror, Chi and Khalaf63) (standard care: NHA > NHA > taxane > supportive care; BRCA positive: NHA > PARP > taxane > supportive care) and therefore provide an appropriate and replicable treatment scenario (Reference Shore, Laliberté and Ionescu-Ittu25). Finally, we also explored thresholds at which further subsidization in olaparib pricing would sway results toward cost-effectiveness.
Our findings are not without limitations. Although we have strived to perform the analysis from an Australian health payer perspective, information for some of the parameters in the model was derived from studies based in the U.S. Second, we assumed that all patients were docetaxel naïve at the start of treatment (Reference Cornford, van den Bergh and Briers62). However, the inputs for PFS with olaparib or NHA in potential BRCA positive patients without testing were derived from the PROfound trial (Reference de Bono, Mateo and Fizazi9), where 65 percent of the patients received previous taxane therapy. Third, the comparator for PARP therapy in our analysis was repeat treatment with another NHA. Recent guidance suggests that this offers little benefit and patients with disease progression should ideally be treated with a taxane (docetaxel or cabazitaxel) or receive basic supportive care (56). Fourth, we would like to acknowledge that the health state utilities were captured from multiple studies across different settings and as such may not be completely appropriate for the intended cohort of mCRPC patients. Finally, we acknowledge that olaparib could have received additional subsidies through commercial arrangements. However, due to the unavailability of this special pricing the current evaluation was based on the market price of olaparib. The differences in our assumptions and those from our resource data do lend some uncertainty to our results. Yet we have strived to utilize the most pertinent available information and attribute discrepancies in assumptions among resource data and our test case to the paucity of statistics within the literature.
The PARP inhibitors have significant survival benefits (Reference de Bono, Mateo and Fizazi9;Reference Mateo, Carreira and Sandhu64) and are approved (23;Reference Helleday65) groundbreaking treatments for prostate cancer. Yet, there is a lack of clarity about the ideal target population for their use in the prostate cancer disease spectrum (Reference Antonarakis, Gomella and Petrylak58). The variability in effectiveness based on pathogenic variants (Reference Giri, Knudsen and Kelly57), modeling differences (partitioned versus state transition models) (Reference Woods, Sideris, Palmer, Latimer and Soares15) and the failure to account for the codependent nature of PARP inhibitor therapy based on the results of genetic testing may explain the inconsistencies in findings from previous economic studies (Reference Li, Lin and Zhong12-Reference Xu, Cai and Zhuang14). In the current evaluation, we have assessed the cost-effectiveness of germline testing and olaparib as codependent technologies. Our findings suggest that from an Australian health system perspective, second line treatment with olaparib in mCRPC may be potentially cost-effective if the current market price of the drug is reduced by 30 percent.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0266462324000011.
Data availability statement
Data sharing is not applicable to this article as no datasets were generated during the current study.
Author contribution
S.T. was involved in the conceptual design, performed the statistical analyses, and prepared the first draft of the manuscript. P.A.S. and H.T. contributed to the conceptual design of the study, provided valuable feedback for the statistical analyses and revisions to the manuscript. All the authors read and agreed to the final version of the article.
Funding statement
This research is part of a doctoral thesis by S.T. S.T. is the recipient of a Griffith University Health Group International Postgraduate Scholarship and a Griffith University Postgraduate Research Scholarship (2019–2022). H.T. holds a Priority Impact Research Award – Future Leader funded by Prostate Cancer Foundation of Australia. P.S. is the recipient of a NHMRC Fellowship (Grant No. 1136923), and a chief investigator on the NHMRC Centre for Research Excellence in Prostate Cancer Survivorship (Grant No. 1116334).
Competing interest
The authors report no conflicts of interest related to this manuscript.
Key points
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• Poly-adenosine diphosphate ribose polymerase (PARP) inhibitors, such as olaparib target repair pathways in cancer cells and are breakthrough therapies in the management of metastatic castration resistant prostate cancer (mCRPC). The cost-effectiveness of olaparib, however, is not clear.
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• Economic evaluations of olaparib have overlooked the need for genetic testing to appropriately target treatment. This paper is the first evaluation of codependent technologies (germline testing and olaparib therapy) in mCRPC from Australia.
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• Our evaluation suggests that germline BRCA testing-guided treatment with olaparib in mCRPC may be cost-effective after applying a 30 percent reduction to the existing market price of the drug.
Open access
