Simulation optimization of PSA-threshold based prostate cancer screening policies

Daniel Underwood (), Jingyu Zhang (), Brian Denton, Nilay Shah () and Brant Inman ()

Health Care Management Science, 2012, vol. 15, issue 4, 293-309

Abstract: We describe a simulation optimization method to design PSA screening policies based on expected quality adjusted life years (QALYs). Our method integrates a simulation model in a genetic algorithm which uses a probabilistic method for selection of the best policy. We present computational results about the efficiency of our algorithm. The best policy generated by our algorithm is compared to previously recommended screening policies. Using the policies determined by our model, we present evidence that patients should be screened more aggressively but for a shorter length of time than previously published guidelines recommend. Copyright Springer Science+Business Media, LLC 2012

Keywords: Prostate cancer screening; Simulation optimization; Genetic algorithm; Ranking and selection (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10729-012-9195-x

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