Gac Sanit. 2018 Nov 12. pii: S0213-9111(18)30214-0. doi: 10.1016/j.gaceta.2018.07.012. [Epub ahead of print]
Probabilistic cost-utility analysis and expected value of perfect information for the Oncotype multigenic test: a discrete event simulation model.
Ibarrondo O1, Álvarez-López I2, Freundlich F3, Arrospide A4, Galve-Calvo E5, Gutiérrez-Toribio M6, Plazaola A7, Mar J4.
To carry out a cost-utility analysis of the application of the Oncotype genomic test to inform the decision to use or not to use chemotherapy in the Basque Country (Spain).
The cost-utility study was carried out using a discrete event simulation model representing the natural history of breast cancer. The decision of treatment with chemotherapy based on Oncotype was compared with the standard of treatment based on clinical-pathological criteria. The model included clinical data from Basque hospitals and the literature and was processed by deterministic and probabilistic analysis to calculate the incremental cost-effectiveness ratio (ICER), the cost-effectiveness plane, the acceptability curve and the expected value of perfect information. The study adopted both a health and societal perspective.
From a health perspective, the deterministic analysis estimated an ICER for Oncotype of 17,453 euros/quality-adjusted life year (QALY), discount included, and 9,613 euros/QALY without the discount. Eighty five percent (85%) of the simulations were below the efficiency threshold for Spain. The parametric variability associated with the Oncotype results was the main uncertainty factor in the decision.
Oncotype is a cost-effective intervention from a health system perspective since each QALY gained costs less than 25,000 euros. From a societal perspective, it is dominant since it provides greater health and is accompanied by cost savings.
Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.
Acceptability curve; Cost-effectiveness; Coste-efectividad; Curva de aceptabilidad; Discrete event simulation; Expected value of perfect information; Genomic test; Oncotype Dx; Simulación de eventos discretos; Test genómico; Valor esperado de la información perfecta
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