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• W2034125309 abstract "New diagnostic procedures and prognostic markers are continually being developed for a wide range of medical complaints. Medical institutions are therefore regularly faced with the decision as to whether to replace an existing procedure with a new one. The decision to adopt a new method is primarily based on diagnostic/predictive accuracy and cost-effectiveness, but this trade-off is not usually considered in a formal decision-theoretic way. The decision process for diagnostic procedures is complicated by the fact that diagnostic decisions are typically based on thresholding one or more continuous variables. Therefore, a formal decision process should account for uncertainty in the optimal threshold value for each diagnostic procedure. We here propose a Bayesian decision approach based on maximizing expected utility (incorporating accuracy and costs) with respect to diagnostic procedure and threshold level simultaneously. The Bayesian decision approach is illustrated via an application comparing the utility of different bone mineral density (BMD) measurements for determining the need for preventative treatment of osteoporotic hip fracture in elderly patients." @default.
• W2034125309 created "2016-06-24" @default.
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• W2034125309 date "2011-01-01" @default.
• W2034125309 modified "2023-10-01" @default.
• W2034125309 title "Bayesian decision analysis for choosing between diagnostic/prognostic prediction procedures" @default.
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• W2034125309 doi "https://doi.org/10.4310/sii.2011.v4.n1.a4" @default.
• W2034125309 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3520495" @default.
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