title: Cost effectiveness of personalized treatment in women with early breast cancer: the application of OncotypeDX and Adjuvant! Online to guide adjuvant chemotherapy in Austria.
abstract: A Breast Cancer Outcomes model was developed at the ONCOTYROL research center to evaluate personalized test-treatment strategies in Austria. The goal was to evaluate the cost-effectiveness of a new 21-gene assay (ODX) when used in conjunction with the Adjuvant! Online (AO) decision aid to support personalized decisions about use of adjuvant chemotherapy in early-stage breast cancer patients in Austria. We applied a validated discrete-event-simulation model to a hypothetical cohort of 50 years old women over a lifetime horizon. The test-treatment strategies of interest were defined using three-letter acronyms. The first (second, third) letter indicates whether patients with a low (intermediate, high) risk according to AO were tested using ODX (Y yes, N no). The main outcomes were life-years gained, quality-adjusted life-years (QALYs), costs and cost effectiveness. Robustness of the results was tested in sensitivity analyses. Results were compared to a Canadian analysis conducted by the Toronto Health Economics and Technology Assessment Collaborative (THETA). Five of eight strategies were dominated (i.e., more costly and less effective: NNY, NYN, YNN, YNY, YYN). The base-case analysis shows that YYY (ODX provided to all patients) is the most effective strategy and is cost effective with an incremental cost-effectiveness ratio of 15,700 EUR per QALY gained. These results are sensitive to changes in the probabilities of distant recurrence, age and costs of chemotherapy. The results of the base-case analysis were comparable to the THETA results. Based on our analyses, using ODX in addition to AO is effective and cost effective in all women in Austria. The development of future genetic tests may require alternative or additional test-treatment strategies to be evaluated.
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, A-6060 Hall i.T, Austria ; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.
authors.forename: B
authors.initials: B
authors.lastname: Jahn
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, A-6060 Hall i.T, Austria ; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.
authors.forename: U
authors.initials: U
authors.lastname: Rochau
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, A-6060 Hall i.T, Austria ; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.
authors.forename: C
authors.initials: C
authors.lastname: Kurzthaler
authors.affiliation: Department of Obstetrics and Gynaecology, Medical University Innsbruck, Innsbruck, Austria.
authors.forename: M
authors.initials: M
authors.lastname: Hubalek
authors.affiliation: Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA USA.
authors.forename: R
authors.initials: R
authors.lastname: Miksad
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, A-6060 Hall i.T, Austria ; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.
authors.forename: G
authors.initials: G
authors.lastname: Sroczynski
authors.affiliation: Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, Toronto, ON Canada ; Department of Emergency Medicine, University of Alberta, Edmonton, AB Canada.
authors.forename: M
authors.initials: M
authors.lastname: Paulden
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, A-6060 Hall i.T, Austria ; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria.
authors.forename: M
authors.initials: M
authors.lastname: Kluibenschädl
authors.affiliation: Toronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, Toronto, ON Canada.
authors.forename: M
authors.initials: M
authors.lastname: Krahn
authors.affiliation: Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard Wallnoefer Center 1, A-6060 Hall i.T, Austria ; Division of Public Health Decision Modelling, Health Technology Assessment and Health Economics, ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria ; Center for Health Decision Science, Department of Health Policy and Management, T.H.Chan Harvard School of Public Health, Boston, MA USA ; Institute for Technology Assessment and Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA USA.
authors.forename: U
authors.initials: U
authors.lastname: Siebert
keywords: 21-Gene assay; Adjuvant! Online; Cost effectiveness; Decision-analytic model; Discrete event simulation; Genetic testing