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

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  • Mikyung Kelly Seo

    (Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine
    University of Bergen)

  • Oddbjørn Straume

    (University of Bergen
    Haukeland University Hospital)

  • Lars A. Akslen

    (University of Bergen
    Haukeland University Hospital)

  • John Cairns

    (Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine
    University of Bergen)

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.

Suggested Citation

  • Mikyung Kelly Seo & Oddbjørn Straume & Lars A. Akslen & John Cairns, 2020. "HSP27 Expression as a Novel Predictive Biomarker for Bevacizumab: is it Cost Effective?," PharmacoEconomics - Open, Springer, vol. 4(3), pages 529-539, September.
  • Handle: RePEc:spr:pharmo:v:4:y:2020:i:3:d:10.1007_s41669-019-00193-8
    DOI: 10.1007/s41669-019-00193-8
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    References listed on IDEAS

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    1. Andrew Briggs & Mark Sculpher & Martin Buxton, 1994. "Uncertainty in the economic evaluation of health care technologies: The role of sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 3(2), pages 95-104, March.
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    1. Rita Faria’s journal round-up for 14th September 2020
      by Rita Faria in The Academic Health Economists' Blog on 2020-09-14 11:00:07

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    1. Mikyung Kelly Seo & Mark Strong, 2021. "A Practical Guide to Modeling and Conducting a Cost-Effectiveness Analysis of Companion Biomarker Tests for Targeted Therapies Using R: Tutorial Paper," PharmacoEconomics, Springer, vol. 39(12), pages 1373-1381, December.

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