Decision Analysis: Utilities and QALYs

Decision Analysis: Utilities and QALYs Miriam Kuppermann, PhD, MPH Professor Departments of Obstetrics, Gynecology & Reproductive Sciences and Epidemiology & Biostatistics January 17, 2008

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

Review—Last Lecture Formulated an explicit question “To clip or not to clip” (aneurysm ) Made a decision tree Conducted an expected value calculation to determine which course of action would likely yield the highest life expectancy

To Clip or not to Clip? • Can have an impact on life expectancy • Also may affect health-related quality of life: Clipping can cause mild/moderate disability Not clipping can cause anxiety associated with being at risk of aneurysm rupture

Incorporating Quality-of-Life Effects into DA • Measure and apply utilities • Use utilities to quality-adjust life expectancy for decision and cost-effectiveness analysis

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 utilities Use them to generate QALY’s ___ Evaluate incremental QALY’s and cost (CEA/CUA) Compare incremental cost effectiveness ratios (ICER) to other currently accepted medical interventions

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 (diabetes, depression) Treatment effects (cure, symptom management) Side effects (impotence, dry mouth) ___ Process (undergoing surgery, prenatal diagnostic procedure)

Utilities are the Currency we use to Assign a Value Outcomes Scaled from 0 to 1 1 = perfect or ideal health or health in the absence of the condition being studied 0 = dead

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

BKA vs. AKA Example Patient in the hospital has infection of the leg Two options: BKA v. medical management BKA –1% mortality risk Medical management – 20% chance of infection worsening: AKA – above the knee amputation (10% mortality risk) Let’s draw a decision tree

For Which Outcomes do we need to Measure Utilities? • Death? • Risk of worsening? • Living with part of a leg (below the knee) missing? • Living with a bigger part of a leg (above the knee) missing? • Others?

Visual Analog Scaling Full health: intact leg 100 98 99 65 Outcome being evaluated: BKA 55 2 1 Dead 0 Asks respondents to rate the outcome on a 0 to 100 “feeling thermometer.”

Standard Gamble Asks respondents what chance of immediate death they would be wiling to incur to avoid living with the outcome being assessed. Method relies on respondents choosing between: 1) a certain outcome (BKA) 2) a gamble between an ideal outcome (intact leg) and the worst outcome (dead)

Standard Gamble Question

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

Time Tradeoff Asks respondents how many years of their own life they would be willing to give up to spend that life expectancy the without the condition/health state being assessed. Method relies on respondents choosing between: 1) Full life expectancy with the condition/outcome being assessed (BKA) 2) A reduced life expectancy with the the ideal outcome (intact leg)

Time Tradeoff Preference Elicitation Which do you prefer? Choice A Choice B Spend the remaining 40 years of your life with BKA Live 40 more years of life with an intact leg (give up 0 years of life)

Time Tradeoff Preference Elicitation Which do you prefer? Choice A Choice B Spend the remaining 40 years of your life with BKA Live 30 more years of life with an intact leg (give up 10 years of life)

Pros and Cons - VAS Advantages: Easy to understand, visual Disadvantages: Doesn’t require the respondent to think about what they’d be willing to give up, doesn’t explore risk preference, values spread over the range, doesn’t require much engagement

Pros and Cons – SG Advantages: Requires assessor to give something up, incorporates risk attitude Disadvantages: Choices may be difficult to make, most confusion-prone method, lack of engagement or willingness to participate in exercise; values tend to cluster near 1.

Pros and Cons – TTO Advantages: While still asking assessor to give something up, easier choices to consider. Values not so clustered near 1, while still more meaningful than VAS scores. Disadvantages: Fails to incorporate risk, lack of clarity of when time traded occurs, isn’t something that one can choose to give up. (One can take on a risk of death, but not “pay with life years.”)

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

Utilities in Decision Analysis Utilities can be to adjust life expectancy in DA where outcomes include morbidity/quality-of-life effects. Quality Adjusted Life-Years (QALYs)

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

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

QALYs

Department of Obstetrics, Gynecology, & Reproductive Sciences A “Real World” Example Prenatal Testing for Chromosomal Disorders Using utilities and cost-effectiveness analysis in an evidence-based approach to challenging guidelines and effecting change.

Prenatal Tests for Chromosomal Disorders Diagnostic Tests (invasive) • Amniocentesis • Chorionic villus sampling (CVS) 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

Women > 35 Diagnostic testing offered Screening as an option (No testing) Guidelines For Prenatal Testing Have Historically been Dichotomized by Maternal Age Women < 35 • Screening offered/encouraged • Diagnostic testing offered only if “positive” results • (No testing)

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 • 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

Threshold set where risks are equal, but are these equal outcomes? Risk of Miscarriage = Risk of Down Syndrome Implicit assumption: women value these two outcomes equally Procedure-related miscarriage Down-syndrome affected infant

How do Women Feel about Prenatal Testing Outcomes? • Do women value procedure-related miscarriage and Down-syndrome-affected birth equally? • How much value to women place on receiving prenatal testing information? • Do women who are 35 or older or receive positive screening results necessarily want to undergo prenatal diagnosis? • How do women view having an abortion after receiving news of an abnormal karyotype? • How do women view the prospect of raising a child with Down syndrome?

Simplified Decision Tree for Prenatal Testing

Generating Evidence on how Women Value Prenatal Testing Outcomes • 1082 socioeconomically and age-diverse women • English-, Spanish- or Chinese-speaking • Interviewed <20 weeks pregnant • Measured TTO utilities for 11 testing outcomes • Administered demographic/attitudinal questions • Collected data on subsequent testing behavior

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

Time Tradeoff Preference Elicitation Which do you prefer? Choice A Choice B 40 years of life remaining with DS-affected child 30 years of life remaining with unaffected child (give up 10 years of life) Both are the same

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

On average, women do not equally weight the outcomes of procedure-related miscarriage and Down syndrome-affected birth Median value for procedure-related miscarriage = 0.86 Median value 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.

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

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

First Evidence-Based Conclusion • Guidelines do not adequately reflect the distribution of pregnant women’s preferences, and they should be changed to allow for these variations in preferences.

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 • 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

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.

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

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

Recommendation #1 • Guidelines should be changed to enable all women to make informed choices about which prenatal tests, if any, to undergo.

Guidelines Have Been Changed! ACOG Practice Bulletin Number 77, Jan 2007 “Screening for Fetal Chromosomal Abnormalities” Should invasive diagnostic testing for aneuploidy 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.”

Guidelines Have Been Changed! ACOG Practice Bulletin Number 88, Dec 2007“Invasive Prenatal Testing for Aneuploidy” Who should have the option of prenatal diagnosis for fetal chromosomal abnormalities? “Invasive diagnostic testing for aneuploidy should be available to all women, regardless of maternal age . . . The differences between screening and diagnostic testing should be discussed with all women. . . . Studies that have evaluated women’s preferences have shown that women weigh the potential outcomes [of testing decisions] differently. The decision to perform invasive testing should take into account these preferences. . .”

Decision Analysis: Utilities and QALYs