A regret theory approach to decision curve analysis: A novel method for eliciting decision makers' preferences and decision-making

BMC Medical Informatics and Decision Making

Research Article

Athanasios Tsalatsanis¹  Benjamin Djulbegovic²  Andrew Vickers³  Iztok Hozo⁴ 

[1] Center for Evidence-based Medicine and Health Outcomes Research, University of South Florida, Tampa, FL, USA;Center for Evidence-based Medicine and Health Outcomes Research, University of South Florida, Tampa, FL, USA;H. Lee Moffitt Cancer Center& Research Institute, Tampa, FL, USA;Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, NY, NY, USA;Department of Mathematics, Indiana University Northwest, Gary, IN, USA;

关键词: Decision Maker;    Optimal Decision;    Threshold Probability;    Wrong Decision;    Expect Utility Theory;   

DOI  :  10.1186/1472-6947-10-51

 received in 2010-07-23, accepted in 2010-09-16,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundDecision curve analysis (DCA) has been proposed as an alternative method for evaluation of diagnostic tests, prediction models, and molecular markers. However, DCA is based on expected utility theory, which has been routinely violated by decision makers. Decision-making is governed by intuition (system 1), and analytical, deliberative process (system 2), thus, rational decision-making should reflect both formal principles of rationality and intuition about good decisions. We use the cognitive emotion of regret to serve as a link between systems 1 and 2 and to reformulate DCA.MethodsFirst, we analysed a classic decision tree describing three decision alternatives: treat, do not treat, and treat or no treat based on a predictive model. We then computed the expected regret for each of these alternatives as the difference between the utility of the action taken and the utility of the action that, in retrospect, should have been taken. For any pair of strategies, we measure the difference in net expected regret. Finally, we employ the concept of acceptable regret to identify the circumstances under which a potentially wrong strategy is tolerable to a decision-maker.ResultsWe developed a novel dual visual analog scale to describe the relationship between regret associated with "omissions" (e.g. failure to treat) vs. "commissions" (e.g. treating unnecessary) and decision maker's preferences as expressed in terms of threshold probability. We then proved that the Net Expected Regret Difference, first presented in this paper, is equivalent to net benefits as described in the original DCA. Based on the concept of acceptable regret we identified the circumstances under which a decision maker tolerates a potentially wrong decision and expressed it in terms of probability of disease.ConclusionsWe present a novel method for eliciting decision maker's preferences and an alternative derivation of DCA based on regret theory. Our approach may be intuitively more appealing to a decision-maker, particularly in those clinical situations when the best management option is the one associated with the least amount of regret (e.g. diagnosis and treatment of advanced cancer, etc).

【 授权许可】

Unknown   
© Tsalatsanis et al; licensee BioMed Central Ltd. 2010. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.