Artikel
Economic evaluation of breast cancer test-treatment strategies using OncotypeDX – preliminary results of a modeling study
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Autoren
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Beate Jahn
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
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Ursula Rochau
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
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Christina Kurzthaler
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
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Marjan Arvandi
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
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Kim Saverno
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Department of Pharmacotherapy, University of Utah, Salt Lake City, Utah, USA
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Felicitas Kühne
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
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Martina Kluibenschädl
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria
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Murray Krahn
- Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, ON, Canada
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Mike Paulden
- Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, ON, Canada
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Uwe Siebert
- Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria; Harvard School of Public Health, Boston, USA/ Harvard Medical School, Boston, USA
| Veröffentlicht: | 11. März 2013 |
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Gliederung
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Objectives: Breast cancer is the most common malignant disease in Western women. At the ONCOTYROL research center, a Breast Cancer Outcomes & Policy model was developed to evaluate the cost effectiveness of personalized test-treatment strategies in the Austrian context. The goal of this study was to evaluate the cost effectiveness of the new 21-gene assay (OncotypeDX) when it is applied in addition to the Adjuvant! Online (AOL) decision aid to supports personalized decisions on adjuvant chemotherapy.
Methods: We simulated a hypothetical cohort of 50 year old women over a lifetime time horizon using a discrete event simulation. The main model outcomes were life-years gained, quality-adjusted life-years (QALYs), costs and cost effectiveness. Based on the new ISPOR-SMDM modelling recommendations, the model was validated using face, internal and cross-model validation. Eight test-treatment strategies were evaluated. Each strategy was defined by three letters. The first letter indicates whether patients with a low risk according to AOL were tested using Oncotype DX (Y-yes; N-no), the second and the third letters provide this information for AOL intermediate and high risk patients, respectively. Robustness of the results was tested in a sensitivity analysis. Results were compared to a Canadian analysis by the Toronto Health Economics and Technology Assessment Collaborative (THETA).
Results: Five out of eight strategies were dominated (i.e., more costly and less effective: NNY, NYN, YNN, YNY, YYN). The base-case analysis shows that only the strategies in which OncotypeDX is provided to patients with an intermediate or high AOL risk (ICER NYY 1,600 EUR/QALY) and where all patients get OncotypeDX (ICER YYY 15,700 EUR/QALY) are cost effective. These results are sensitive to changes in the probabilities of distant recurrence, age, and costs of chemo. These changes lead to further strategies that are not dominated (NYN and NNY). However, the absolute values of the ICER remain lower than 25,000 EUR/QALY in almost all strategies. The base case analysis was comparable to the THETA results.
Conclusions: Our simulation study showed that the genetic test, OncotypeDX, when used in addition to the AOL, is cost effective in two test-treatment strategies (NYY, NNN) in the Austrian context. Our simulation tool provides the flexibility to evaluate combinations of two or more tests and respective treatment. This is important because tests such as OncotypeDX and the AOL decision aid can complement each other.
This work was supported by the COMET Center ONCOTYROL, which is funded by the Austrian Federal Ministries BMVIT/BMWFJ (via FFG) and the Tiroler Zukunftsstiftung/Standortagentur Tirol (SAT).
