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Title: | Reflections on the concept of optimality of single decision point treatment regimes | Authors: | Tran, Trung Dung Abad, Ariel Alonso VERBEKE, Geert MOLENBERGHS, Geert Van Mechelen, Iven |
Issue Date: | 2023 | Publisher: | WILEY | Source: | BIOMETRICAL JOURNAL, (Art N° 2200285) | Abstract: | In many areas, applied researchers as well as practitioners have to choose between different solutions for a problem at hand; this calls for optimal decision rules to settle the choices involved. As a key example, one may think of the search for optimal treatment regimes (OTRs) in clinical research, that specify which treatment alternative should be administered to each patient under study. Motivated by the fact that the concept of optimality of decision rules in general and treatment regimes in particular has received so far relatively little attention and discussion, we will present a number of reflections on it, starting from the basics of any optimization problem. Specifically, we will analyze the search space and the to be optimized criterion function underlying the search of single decision point OTRs, along with the many choice aspects that show up in their specification. Special attention is paid to formal characteristics and properties as well as to substantive concerns and hypotheses that may guide these choices. We illustrate with a few empirical examples taken from the literature. Finally, we discuss how the presented reflections may help sharpen statistical thinking about optimality of decision rules for treatment assignment and to facilitate the dialogue between the statistical consultant and the applied researcher in search of an OTR. | Notes: | Van Mechelen, I (corresponding author), Quantitat Psychol & Individual Differences, KU Leuven, B-3000 Leuven, Belgium. Iven.VanMechelen@kuleuven.be |
Keywords: | criterion function;optimal treatment regime;precision medicine;search space | Document URI: | http://hdl.handle.net/1942/41668 | ISSN: | 0323-3847 | e-ISSN: | 1521-4036 | DOI: | 10.1002/bimj.202200285 | ISI #: | 001067381200001 | Rights: | 2023 Wiley-VCH GmbH. | Category: | A2 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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