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- W2183402023 abstract "To find biosignatures of treatment response, clinicians are interested in identifying patient features at baseline that predict dierential response to different treatment. The treatments could be drug and placebo, or dierent drugs. These dierential predictors may be termed “moderators of treatment eect”, because the dierences between the ecacies of the treatments depend on the levels of those predictors. It is common in clinical research to model the outcome as a linear function of the predictor and to test for significance of the interaction between treatment and the predictors in order to find moderators of treatment eect. Also, typically, moderators are identified either one by one, using one model for each potential predictor, or from a large model which includes all potential predictors and their 2way interactions with treatment, but not interactions between the potential predictors. However, neither of these modeling strategies aids in the determination of combinations of patient characteristics that could be used to select patients who have high probability to respond to a given drug. In this talk we present flexible methods that extend the existing approaches for identification of dierential predictors of treatment response in two directions:" @default.
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- W2183402023 date "2013-01-01" @default.
- W2183402023 modified "2023-09-27" @default.
- W2183402023 title "Modeling Strategies for Developing Treatment Response Indices" @default.
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