Solid recommendations from soft numbers: the test/treatment decision.
The authors review the probability threshold approach to test/treatment decisions developed by Pauker and Kassirer, emphasizing that certain aspects of the nature of medical decisions call for a new approach. The utility threshold approach, while maintaining all the advantages of threshold methods in general, brings improvements. It diminishes the need to accurately assess one of the decision's parameters: the patient's utility for the outcome states. For a simple case of one disease with three outcome states (cured, diseased, dead) and one test, three utility thresholds are derived. The treat/no treat threshold, denoted by u, separates the utility space in two. If the patient's value for the diseased state is greater than u, the analyst can feel confident in recommending the patient forego treatment. Similar interpretations are developed for u1, the no treatment/test utility threshold (the value u must take, given a positive test result, for the patient to be indifferent between foregoing and receiving treatment), and u2, the test/treatment utility threshold (the value u must take, given a negative test result, for the patient to be indifferent between foregoing and receiving treatment.
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Department of Engineering-Economic Systems, Stanford University, California 94305.
Bonduelle
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D003663:Decision Trees; D003933:Diagnosis; D006801:Humans; D011336:Probability; D013812:Therapeutics