Methods for Performing Survival Curve Quality-of-Life Assessments.
Many medical decisions involve an implied choice between alternative survival curves, typically with differing quality of life. Common preference assessment methods neglect this structure, creating some risk of distortions.



Survival curve quality-of-life assessments (SQLA) were developed from Gompertz survival curves fitting the general population's survival. An algorithm was developed to generate relative discount rate-utility (DRU) functions from a standard survival curve and health state and an equally attractive alternative curve and state. A least means squared distance algorithm was developed to describe how nearly 3 or more DRU functions intersect. These techniques were implemented in a program called X-Trade and tested.



SQLA scenarios can portray realistic treatment choices. A side effect scenario portrays one prototypical choice, to extend life while experiencing some loss, such as an amputation. A risky treatment scenario portrays procedures with an initial mortality risk. A time trade scenario mimics conventional time tradeoffs. Each SQLA scenario yields DRU functions with distinctive shapes, such as sigmoid curves or vertical lines. One SQLA can imply a discount rate or utility if the other value is known and both values are temporally stable. Two SQLA exercises imply a unique discount rate and utility if the inferred DRU functions intersect. Three or more SQLA results can quantify uncertainty or inconsistency in discount rate and utility estimates. Pilot studies suggested that many subjects could learn to interpret survival curves and do SQLA.



SQLA confuse some people. Compared with SQLA, standard gambles quantify very low utilities more easily, and time tradeoffs are simpler for high utilities. When discount rates approach zero, time tradeoffs are as informative and easier to do than SQLA.



SQLA may complement conventional utility assessment methods.
Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA (WS, IDF)
Walton
W
Sumner
American Board of Family Medicine, Inc., Lexington, KY, USA (ED, MDH)
Eric
E
Ding
Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA (WS, IDF)
Irene D
ID
Fischer
American Board of Family Medicine, Inc., Lexington, KY, USA (ED, MDH)|Department of Family and Community Medicine, University of Kentucky College of Medicine, Lexington, KY, USA (MDH).
Michael D
MD
Hagen
D000465:Algorithms; D002755:Choice Behavior; D003362:Cost-Benefit Analysis; D006304:Health Status; D006801:Humans; D057240:Patient Preference; D011788:Quality of Life / Q000523:psychology*; D016019:Survival Analysis; D013997:Time Factors; D035501:Uncertainty
discount rate; quality of life; survival curve; utility assessment