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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Gavan, Sean P.
University of Manchester
in Cooperation with on an Cooperation-Score of 37%
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article
Cost-effectiveness analyses of genetic and genomic diagnostic technologies
Abstract
Developments in next-generation sequencing technologies have driven the clinical application of diagnostic tests that interrogate the whole genome, which offer the chance to diagnose rare inherited diseases or inform the targeting of therapies. New genomic diagnostic tests will compete with traditional approaches to diagnosis, including the genetic testing ofsingle genes, and other clinical strategies for the available finite healthcare budget. In this context, decision analytic model-based cost-effectiveness analysis is a usefulmethod to help evaluate the costs versus benefits of introducing new healthcare interventions such as genomic diagnostic tests. This Review presents key methodological, technical, practical and organizational challenges that must be considered by decision-makers responsible for the allocation of healthcare resources to provide robust and timely information about the relative cost-effectiveness of the increasing numbers of emerging genomic tests.