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• W2748867179 abstract "In medical practice, when more than one treatment option is viable, there is little systematic use of individual patient characteristics to estimate which treatment option is most likely to result in a better outcome for the patient. This is due in part because practitioners do not have any easy way to holistically evaluate whether their treatment allocation procedure does better than the standard of care --- a metric we term improvement. Herein, we present easy-to-use open-source software that provides inference for improvement in many scenarios, the R package PTE, Personalized Treatment Evaluator and in the process introduce methodological advances in personalized medicine. In the software, the practitioner inputs (1) data from a single-stage randomized trial with one continuous, incidence or survival endpoint and (2) a functional form of a model for the endpoint constructed from domain knowledge. The bootstrap is then employed on out-of-sample data to provide confidence intervals for the improvement for future patients. One may also test against a null scenario where the hypothesized model's treatment allocations are not more useful than the standard of care. We demonstrate our method's promise on simulated data as well as on data from a randomized trial investigating two treatments for depression." @default.
• W2748867179 created "2017-08-31" @default.
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• W2748867179 date "2014-04-30" @default.
• W2748867179 modified "2023-09-27" @default.
• W2748867179 title "Inference for the Effectiveness of Personalized Medicine with Software" @default.
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• W2748867179 hasPublicationYear "2014" @default.
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