Case Study: QALYs

NoneIntroduction and Learning Objectives

By the end of this session, participants will be able to:

  1. Define and parameterize key inputs (e.g., probabilities, outcomes, and costs) within the Amua software.

  2. Evaluate model outcomes, such as expected quality-adjusted life expectancy (QALE), for alternative clinical strategies.

Decision Trees

Add QALY Dimension

We now want to add a new outcome dimension: QALYs (Quality-Adjusted Life Years). QALYs are a measure of disease burden, where 1 = perfect health and 0 = death.

Instructions:

  1. In Amua, go to Model → Properties → Analysis tab.

  2. Add a new dimension:

    • Dimension: QALE

    • Symbol: Q

    • Decimals: 2

  3. Click Refresh

  4. For QALYs make sure the objective is maximizing

  5. We can now return to the tree and enter QALE values at each terminal node

Clinical State QALE Notes
QALE_Untreated 3.21 Large amounts of time at low quality of life
QALE_SickTreated 14.54 Short amounts of time sick and in treatment
QALE_Healthy 20 Full Health
QALE_HealthyTreated 19.432 Very short amount of time in treatment

You can apply these QALE values to terminal nodes in Amua accordingly. Your tree should like this:

Now, you’re ready to perform a cost-effectiveness analysis with QALYs as the outcome!

Click Run Model and check out the CEA Results report.

Markov Models

Add a DALY Dimension

We now want to add a new outcome dimension: DALYs (Disability-Adjusted Life Years). DALYs are a measure of disease burden, where 0 = perfect health and 1 = death per year lost. For this model, we will add Years of Life Lost. To discount these from the start of time and the time of occurrence we will use the built in discounting (from start time) and add discounting from the time of death.

To save time, we will go through the No Treat branch. A full answer key will be included at the end

A: Important Parameters

Quality of Life Adjustments

Name Value Description
u_healthy 1.0 Quality-of-life (QoL) weight for healthy state.
u_sick 0.842 Quality-of-life (QoL) weight for sick health state.
u_sick_treated 0.87 Quality-of-life (QoL) weight for sick health state if treated.
u_dead 0 Quality-of-life (QoL) weight for death health states.

Add QALYs

A: Add A DALY Outcome

  1. In Amua, go to Model → Properties → Analysis tab.

  2. Add a new dimension:

    • Dimension: DALYs

    • Symbol: D

    • Decimals: 2

  3. Click Refresh

  4. Because DALY is a gap measure, change the objective to minimize DALYs (analogous to maximizing QALYs)

Add Outcome

  • Go to Model Properties select the Analysis tab.

  • Click the blue plus sign (Custom Icon) to add a new outcome. Add DALYs.

  • Click the refresh button

  • Change the “Analysis Type” to Cost-Effectiveness Analysis (CEA).

  • Set the Cost, Effect, Baseline Strategy and Willingness-to-pay (WTP). Ensure that the Effect Objective is still set to minimize.

  • Go to the Markov tab and add in the discount rate for DALYs. (3.0)

  • Next, in the model itself, define the cycle-specific payoffs based on the values in the tables above.

    • Every place in the model where there is a value for YLD or YLL, we will put that in DALYs so that it sums them all together.
      • For Example: Under sick where it now has($) c_sick; (YLD) dw_sick ; (YLL) 0, we will have ($) c_sick; (YLD) dw_sick ; (YLL) 0 ; (DALY) dw_sick

Check and run the model to get the CEA for DALYs

Strategy Cost DALY ICER Note
Treat None 40,286.24 4.98 Baseline
Treat All 51,548.10 2.78 5121.1089

Solution File: ADD FILE

What if there are multiple disability weights in one state?

For Example: You may get a disability weight for being sick and for a reaction to medication.

There are multiple ways to handle this: Joint Utility Methods Slides