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Assessing cost-utility of predictive biomarkers in oncology: a streamlined approach

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Abstract

Evaluation of cost-utility is critical in assessing the medical utility of predictive or prognostic biomarkers. Current methods involve complex state-transition models, requiring comprehensive data inputs. We propose a simplified decision-analytic tool to explore the relative effect of factors contributing to the cost-utility of a biomarker. We derived a cost-utility metric, the “test incremental cost-effectiveness ratio” (TICER) for biomarker-guided treatment compared to no biomarker use. This method uses data inputs readily accessible through clinical literature. We compared our results with traditional cost-effectiveness analysis of predictive biomarkers for established (HER2-guided trastuzumab, ALK-guided crizotinib, OncotypeDX-guided adjuvant chemotherapy) and emerging (ROS1-guided crizotinib) targeted treatments. We conducted sensitivity analysis to determine which factors had the greatest impact on TICER estimates. Base case TICER for HER2 was $149,600/quality-adjusted life year (QALY), for ALK was $22,200/QALY, and for OncotypeDX was $11,600/QALY, consistent with literature-reported estimates ($180,000/QALY, $202,800/QALY, $8900/QALY, respectively). Base case TICER for ROS1-guided crizotinib was $205,900/QALY. Generally, when treatment cost is considerably greater than biomarker testing costs, TICER is driven by clinical outcomes and health-related quality of life, while biomarker prevalence and treatment cost have a lesser effect. Our simplified decision-analytic approach produces values consistent with existing cost-effectiveness analyses. Our results suggest that biomarker value is mostly driven by the clinical efficacy of the targeted agent. A user-friendly web tool for complete TICER analysis has been made available for open use at http://medicine.yale.edu/lab/pusztai/ticer/.

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Acknowledgements

The authors thank Weiwei Shi, Tingting Jiang, Vikram Wali, James Platt, Tomoko Kurita, Bilge Aktas for technical assistance and constructive discussions.

Funding

This study was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health [TL1TR000141 to A.S.], Associazione Italiana per la Ricerca sul Cancro [MFGA 13428 to G.B.].

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Authors and Affiliations

  1. Yale School of Medicine, New Haven, USA

    Anton Safonov, Cary P. Gross, Divyansh Agarwal, Lajos Pusztai & Christos Hatzis

  2. Yale School of Public Health, New Haven, USA

    Shiyi Wang

  3. Cancer Outcomes Public Policy and Effectiveness Research (COPPER) Center, New Haven, USA

    Shiyi Wang & Cary P. Gross

  4. Yale Cancer Center, Yale University, New Haven, USA

    Cary P. Gross, Lajos Pusztai & Christos Hatzis

  5. San Raffaele Scientific Institute, Milan, Italy

    Giampaolo Bianchini

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  1. Anton Safonov
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Correspondence to Christos Hatzis.

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Safonov, A., Wang, S., Gross, C.P. et al. Assessing cost-utility of predictive biomarkers in oncology: a streamlined approach. Breast Cancer Res Treat 155, 223–234 (2016). https://doi.org/10.1007/s10549-016-3677-3

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  • DOI: https://doi.org/10.1007/s10549-016-3677-3

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