HSP27 Expression as a Novel Predictive Biomarker for Bevacizumab: is it Cost Effective?

Abstract

Background Despite the extensive use of bevacizumab in a range of oncology indications, the US FDA revoked its approval for breast cancers, and multiple negative trials in several solid malignancies have been reported, so the need for predictive biomarkers has increased. The development of predictive biomarkers for anti-angiogenic bevacizumab therapy has long been pursued but without success. Introduction Heat shock protein (HSP)-27 expression has recently been identified as a predictive biomarker for bevacizumab in treating metastatic melanoma. This study aimed to evaluate the cost effectiveness of HSP27 biomarker testing before administration of bevacizumab. Methods A partitioned survival analysis model with three mutually exclusive health states (progression-free survival, progressed disease, and death) was developed using a Norwegian health system perspective. The proportion of patients in each state was calculated using the area under the Kaplan-Meier curve for progression-free and overall survival derived from trials of bevacizumab and dacarbazine. Three strategies were compared: (1) test-treat with HSP27 biomarker and bevacizumab, (2) treat-all with dacarbazine without HSP27 testing, (3) treat-all with bevacizumab without HSP27 testing. Quality-adjusted life-years (QALYs) and costs were calculated for each strategy and discounted at 4%. A lifetime horizon was applied. Uncertainty analyses were performed. Expected value of perfect information (EVPI) was estimated to assess the potential value of further research to generate more evidence. Results Although the test-treat strategy was cost effective compared with treat-all with dacarbazine, it was not cost effective compared with treat-all with bevacizumab without HSP27 testing. However, EVPI results showed very minimal or no value in conducting further research efforts to reduce uncertainties around current information.Conclusion The results of this study suggested that testing for HSP27 expression before administering bevacizumab is not cost effective compared with treat-all with bevacizumab without testing. It indicates that HSP27 expression is not cost effective as a potential predictive biomarker for bevacizumab. This may not necessarily mean that HSP27 is a bad biomarker for bevacizumab, but it may mean that bevacizumab is much better than dacarbazine regardless of HSP27 expression, so patient stratification according to HSP27 status is meaningless. Or, indeed, it may imply that HSP27 is not sufficiently good at identifying the right patients for bevacizumab.

How are we evaluating the cost-effectiveness of companion biomarkers for targeted cancer therapies? A systematic review

“…Thus, the EEs should incorporate the evidence of the test’s performance (or diagnostic accuracy) that result in a change in the management of subsequent therapeutic service. Also, it was observed from our previous empirical studies that the structure of comparing alternative strategies and choosing comparator strategy in EEs might lead to different cost-effectiveness results of their corresponding test-guided therapies and health outcomes [ 14 , 15 , 18 ].…”

“…This review of current practice with respect to the EE of companion biomarkers focuses on nine methodological areas. These key areas were formulated based on previous studies and existing HTA documentation guides on co-dependent technologies [2,3,[11][12][13][14][15], the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist [16]. We first used the framework of the CHEERS checklist and it provided useful information in formulating the key method areas for this review such as target population, study perspective, comparators, preference-based outcomes, and estimating resource use and costs.…”

“…abstracts) were excluded Study type: economic evaluations including model or trial-based analyses a change in the management of subsequent therapeutic service. Also, it was observed from our previous empirical studies that the structure of comparing alternative strategies and choosing comparator strategy in EEs might lead to different cost-effectiveness results of their corresponding test-guided therapies and health outcomes [14,15,18]. The nine domains framed for the synthesis of this review are following: for these ninemethodological areas.…”

A Practical Guide to Modeling and Conducting a Cost-Effectiveness Analysis of Companion Biomarker Tests for Targeted Therapies Using R: Tutorial Paper

“…The reference case applied in this worked example of the core model is summarized in Table 1 . This core model is developed based on the findings and practical lessons acquired from previous studies on companion diagnostics or co-dependent technologies [ 8 , 10 , 16 , 17 ]. Systematic reviews found that the characteristics of companion biomarker tests were not consistently incorporated in economic evaluations of biomarker-guided therapies and the structure of comparative analyses of the strategy arms was so varied that it may lead to a different conclusion in terms of cost effectiveness [ 8 , 10 , 17 ].…”

“…Instead, they compared biomarker-guided therapy with biomarker testing versus without the testing, while no SOC was considered in the evaluations. Therefore, based on the study findings from previous studies [ 8 , 10 , 16 ], we found that assessing the biomarker-guided therapy against two comparator strategies was the most suitable structure for strategy comparison. Therefore, we constructed three strategies as default comparisons in this core model: (1) patients being tested with a companion biomarker and treated with the corresponding targeted therapy according to their biomarker testing result (hereinafter referred to as the test–treat strategy, i.e.…”