Decision Analysis: Utilities and QALYs

1. Decision Analysis: Utilities and QALYs Miriam Kuppermann, PhD, MPH Professor Departments of Obstetrics, Gynecology & Reproductive Sciences and Epidemiology & Biostatistics January 18, 2007

2. Review—Last Lecture Formulate an explicit question “To clip or not to clip” Make a decision tree

3. Preview—Where We Are Going with this Analysis? Recall Ms. Brooks and her incidental aneurysm -- to clip or not to clip? We want to: Determine her utility: clip, and not clip Compare incremental utility and cost Compare cost-per-unit of utility across private and public uses of funds.

4. Today’s Lecture Utilities and utility measurement Calculating Quality Adjusted Life Years Back to the aneurysm example: To Clip Or Not To Clip? Using utility measurement and cost-utility analysis to change clinical guidelines: Prenatal Genetic Testing

5. What is a Utility? Quantitative measure of the strength of an individual’s preference for a particular health state or outcome. Utilities can be obtained for: Disease states (Stroke, diabetes, depression) Treatment effects (cure, symptom management) Side effects (impotence, dry mouth) Process (undergoing surgery, prenatal diagnostic procedure)

6. Utilities are the Currency of Outcomes Scaled from 0 to 1 Commonly Death = 0 Perfect Health = 1

7. How do we Measure Utilities? Visual Analog Scale Standard Gamble Time Trade-off ----- Conjoint analysis

8. BKA vs. AKA Example Patient in the hospital has infection of the leg Two options: BKA v. medical management BKA – below the knee amputation (1% mortality risk) Medical – 20% chance of infection worsening If worse, AKA – above the knee amputation (10% mortality risk)

9. Visual Analog Scaling Exercise Most Desirable Ideal health 100 98 99 65 55 2 Dead 1 0 Least Desirable

10. Utility Measurement--Standard Gamble Method relies on patients choosing between: 1) a certain outcome 2) a gamble between a better outcome and a worse outcome How it works: Choice 1: You live with an AKA Choice 2: The gamble – you might have a cure; you might die. Goal of method is to find the break-even point. What probability of death would you accept to avoid living with the AKA?

11. Utility Measurement – Standard Gamble

12. Standard Gamble Exercise Which do you prefer? Choice A Choice B Spend the rest of your life with AKA [_]% chance of immediate death 1-[ ]% chance of spending the rest of your life with an intact leg

13. Utility Measurement – Time Trade-off Time Trade-off involves patients choosing between: quality of life vs. length of time alive We want to determine when patients are equivocal between choice: Time A * Utility A = Time B * Utility B e.g. -- If you have a life expectancy of 40 years with a AKA, how much time would you give up to live in your current state? Would you give up 5 years? 3 years? 1 year? 40 years * Utility (AKA) = (40-x) years * 1.0 If you’re willing to give up 5 years, that means the utility of AKA is: = [(40-5)*1/ 40] = 35/40 = 0.875

14. Time Tradeoff Preference Elicitation Which do you prefer? Choice A Choice B Spend the remaining 40 years of your life with AKA Live [ ] more years of life with an intact leg (give up 40-[ ] years of life)

15. Pros and Cons - VAS Advantages: quantitative, easy to understand, visual Disadvantages: may bias values to the middle, seems disconnected from medical reality

16. Pros and Cons – SG Advantages: the incorporation of risk into the model, comparison or choice between different outcomes. Disadvantages: possible nonrealistic choices patients may be asked to make, the difficulty of understanding the question (especially for non-gamblers)

17. Pros and Cons – TTO Advantages: the simplicity of the choice between different outcomes, consideration of long-term outcomes. Disadvantages: fails to incorporate risk, lack of clarity of when time traded occurs, different valuation of time during life, and the theoretical lack of realism of the choice.

18. Utility Measurement – Additional Information Multi-Attribute Health Status Classification System Developed by Health Utilities, Inc. Available at: http://www.healthutilities.com/overview.htm

19. Utilities in Decision Analysis Now that we have methods to estimate utilities, these can be used in the DA However, our outcomes often include both mortality and morbidity Want a way to add in life expectancy Quality Adjusted Life-Years (QALYs)

20. QALYs QALYs are generally considered the standard unit of comparison for outcomes QALYs = time (years) x quality (utils) e.g. 40 years after AKA, util (AKA) = 0.875 = 40 x 0.875 = 35 QALYs

21. QALYs Aneurysm Example We said life expectancy is reduced by 2/3, so instead of 35, it is = 35 * .333 = 11.67 Here, we have assigned a utility of .5 to surgery-induced disability, so QALYs = years * utils = 11.67 * .5 = 5.8

22. QALYs

23. Department of Obstetrics, Gynecology, & Reproductive Sciences Real World Example: Prenatal Genetic Testing

24. Prenatal Tests for Chromosomal Disorders Screening Tests (non-invasive) • Maternal age • 1st trimester nuchal translucency • 1st trimester combined screening • 2nd trimester expanded maternal serum AFP (triple or quad marker) • 1st and 2nd trimester sequential, contingent, or integrated screening Diagnostic Tests (invasive) • Amniocentesis • Chorionic villus sampling (CVS)

25. Women < 35 Screening first Invasive testing only if “positive” results Women > 35 Invasive testing offered Screening as an option Guidelines For Prenatal Testing Are Typically Dichotomized By Maternal Age

26. Rationale for Guidelines Need to limit access to invasive testing • Inherent risk of procedure • Limited availability of providers, laboratories Age 35 selected as the threshold • Increasing risk with advancing maternal age • Threshold set where risks equal • Cost/benefit considerations Kuppermann, Nease, Goldberg, Washington. Who should be offered prenatal diagnosis? The 35-year-old question. Am J Public Health 1999; 89:160-3

27. Equal Risk Threshold Risk of Miscarriage = Risk of Down Syndrome Implicit assumption: equally burdensome outcomes (i.e., utility for each is equal) Down-syndrome affected infant Procedure-related miscarriage

28. First Challenge to Guidelines Do women find procedure-related miscarriage and Down-syndrome-affected birth to be equally burdensome?

29. How Do Women Value Testing Outcomes? • 1082 socioeconomically and age-diverse women • English-, Spanish- or Chinese-speaking • Interviewed <20 weeks pregnant • Measured utility for testing outcomes using SG and TTO • Administered demographic/attitudinal questions • Collected data on subsequent testing behavior

30. Simplified Decision Tree for Prenatal Testing

31. Time Tradeoff Preference Elicitation Which do you prefer? Choice A Choice B 40 years of life remaining with affected child 40 years of life remaining with unaffected child (give up 0 years of life)

32. Time Tradeoff Preference Elicitation Which do you prefer? Choice A Choice B 40 years of life remaining with affected child 30 years of life remaining with unaffected child (give up 10 years of life)

33. Calculation of Time Tradeoff Scores reduced life expectancy with unaffected child (30 years) UTTO = __________________________________________ full life expectancy with affected child (40 years) = 0.75

34. On average, women do not equally weight the outcomes of procedure-related miscarriage and Down syndrome-affected birth Median utility for procedure-related miscarriage = 0.86 Median utility for Down-syndrome affected infant = 0.73 P<0.001 by Wilcox sign rank test Kuppermann, Nease, Learman, Gates, Blumberg, Washington. Procedure-related miscarriages and Down syndrome-affected births: implications for prenatal testing based on women’s preferences. Obstet Gynecol 2000; 96:511-6.

35. Preference Difference Score One way to look at the relative value women assign to procedure-related miscarriage and DS-affected birth Pref score misc – Pref score DS Higher score = greater preference for miscarriage over DS

36. Preferences Vary Substantially 200 175 150 125 Number 100 75 50 25 0 0 -1 -.75 -.5 -.25 .25 .5 .75 1 Utility misc - Utility DS

37. First Conclusion • Current guidelines do not adequately reflect the preferences of pregnant women.

38. Second Challenge to Guideline Old paradigm: COST BENEFIT Benefits (in $$ terms) of program should exceed costs. • Costs of offering testing should be offset by savings accrued by averting the birth of Down-syndrome-affected infants New paradigm: COST EFFECTIVENESS No $$ value assigned to outcomes. • Cost of offering testing should be “worth” the gain in quantity and quality of life.

39. How is Cost Effectiveness Measured? ΔC Δ Costs = Δ QALY ΔE QALY = Quality–Adjusted Life Year

40. Cost Effectiveness of Prenatal Diagnosis Harris, Washington, Nease, Kuppermann. Cost utility of prenatal diagnosis and the risk-based threshold. Lancet 2004; 363:276-82.

41. Second Conclusion • Offering invasive testing to women of all ages and risk levels can be cost effective.

42. Recommendations • Guidelines should be changed to enable all women to make informed choices about which prenatal tests, if any, to undergo. • Tools that help women and partners make informed choices should be implemented.

43. Guidelines have been changed! ACOG Practice Bulletin Number 77, Jan 2007, “Screening for Fetal Chromosomal Abnormalities” Should invasive diagnostic testing for anueploidy be available to all women? All women, regardless of age, should have the option of invasive testing . . .Studies that have evaluated women’s preferences have shown that women weigh these potential outcomes [miscarriage, birth of an affected infant] differently . . . Thus, maternal age of 35 years alone should no longer be used as a cutoff to determine who is offered screening versus who is offered invasive testing.”

44. The EPIC Study has been funded! Early Prenatal Testing and Informed Choice Randomized study of an “informed free choice” approach to prenatal testing options which will: • determine which prenatal testing strategies are selected by women who receive complete information and have access to all testing options compared to women receiving usual care; • assess the impactof this approach on knowledge, risk comprehension, and decisional conflict; and • evaluate the cost effectiveness of this approach to providing prenatal testing services compared to usual care.

45. Conclusions Patient preferences matter! Utility assessment can be used to quantify preferences These values can be used to generate QALYs and conduct CUAs Results of these analyses make a difference to policy makers and individual patients Thank you!