The Neuro-QoL® Utility (NQU) Scoring System...Scoring function Validation Key research personnel...

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

The Neuro-QoL R© Utility (NQU) ScoringSystem

Barry Dewitt, PhD

Carnegie Mellon University

June 5th, 2019

1 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Financial support from Biogen

2 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Key research personnel

Louis Matza (PI, Evidera)

Katie Stewart

Dennis Revicki

Janel Hanmer

David Cella

David Feeny

Deborah Miller

Glenn Phillips

3 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Health-related quality of life (HRQL)

HRQL is multidimensional: physical functioning, cognitivefunctioning, depression, fatigue, dexterity...

Condition-specificGeneric

Figure: Wilson & Cleary (1995).

4 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Health-related quality of life (HRQL)

HRQL is multidimensional: physical functioning, cognitivefunctioning, depression, fatigue, dexterity...

Condition-specificGeneric

Figure: Wilson & Cleary (1995).

4 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Health-related quality of life (HRQL)

HRQL is multidimensional: physical functioning, cognitivefunctioning, depression, fatigue, dexterity...

Condition-specificGeneric

Figure: Wilson & Cleary (1995).

4 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL

We will be focusing on utility-based HRQL measures.

Utility captures preferences for health (usually the public’spreferences).

Summarizes the value of a state of health by a singlenumber, allowing the comparison of all states of health.

Useful for many applications

Economic analyses (e.g., QALYs, cost-effectivenessanalysis)Population health

5 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL

We will be focusing on utility-based HRQL measures.

Utility captures preferences for health (usually the public’spreferences).

Summarizes the value of a state of health by a singlenumber, allowing the comparison of all states of health.

Useful for many applications

Economic analyses (e.g., QALYs, cost-effectivenessanalysis)Population health

5 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL

We will be focusing on utility-based HRQL measures.

Utility captures preferences for health (usually the public’spreferences).

Summarizes the value of a state of health by a singlenumber, allowing the comparison of all states of health.

Useful for many applications

Economic analyses (e.g., QALYs, cost-effectivenessanalysis)Population health

5 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL

We will be focusing on utility-based HRQL measures.

Utility captures preferences for health (usually the public’spreferences).

Summarizes the value of a state of health by a singlenumber, allowing the comparison of all states of health.

Useful for many applications

Economic analyses (e.g., QALYs, cost-effectivenessanalysis)Population health

5 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL

We will be focusing on utility-based HRQL measures.

Utility captures preferences for health (usually the public’spreferences).

Summarizes the value of a state of health by a singlenumber, allowing the comparison of all states of health.

Useful for many applications

Economic analyses (e.g., QALYs, cost-effectivenessanalysis)Population health

5 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL

We will be focusing on utility-based HRQL measures.

Utility captures preferences for health (usually the public’spreferences).

Summarizes the value of a state of health by a singlenumber, allowing the comparison of all states of health.

Useful for many applications

Economic analyses (e.g., QALYs, cost-effectivenessanalysis)Population health

5 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

6 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

��1.0sleep, 1.2pain, cognition, physical functioning, . . .

�

7 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

��1.0sleep, 1.2pain, cognition, physical functioning, . . .

�

Worst utility Best utility (i.e., the value of full health)

10

8 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

��1.0sleep, 1.2pain, cognition, physical functioning, . . .

�

Worst utility Best utility (i.e., the value of full health)

10

9 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

��1.0sleep, 1.2pain, cognition, physical functioning, . . .

�

Worst utility Best utility (i.e., the value of full health)

10

10 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

��1.0sleep, 1.2pain, cognition, physical functioning, . . .

�

Worst utility Best utility (i.e., the value of full health)

10

11 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Summary of a utility-based HRQL measure

“Rarely get enough sleep”

Sleep wellSleep poorly 0

“Never in distressing pain”

No painWorst pain 0

-1.0 1.2

��1.0sleep, 1.2pain, cognition, physical functioning, . . .

�

Worst utility Best utility (i.e., the value of full health)

10

12 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview

The Neuro-QoL R© Utility (NQU) Scoring System is autility-based HRQL measure that uses the Neuro-QoL todescribe states of health.

It allows studies to collect patient-reported outcomes datathrough the Neuro-QoL and automatically have the capabilityto perform preference-based analyses without extra datacollection.

Developed with a particular focus on multiple sclerosis.

13 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview

The Neuro-QoL R© Utility (NQU) Scoring System is autility-based HRQL measure that uses the Neuro-QoL todescribe states of health.

It allows studies to collect patient-reported outcomes datathrough the Neuro-QoL and automatically have the capabilityto perform preference-based analyses without extra datacollection.

Developed with a particular focus on multiple sclerosis.

13 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview

The Neuro-QoL R© Utility (NQU) Scoring System is autility-based HRQL measure that uses the Neuro-QoL todescribe states of health.

It allows studies to collect patient-reported outcomes datathrough the Neuro-QoL and automatically have the capabilityto perform preference-based analyses without extra datacollection.

Developed with a particular focus on multiple sclerosis.

13 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview, cont’d

Most utility-based HRQL measures describe health usingclassical test theory-based instruments. The NQU benefitsfrom the psychometric advances of the Neuro-QoL.

The PROMIS R©-Preference (PROPr) project produced a genericutility score for health states described by PROMIS domains.

The NQU project follows a similar methodology to PROPr.

14 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview, cont’d

Most utility-based HRQL measures describe health usingclassical test theory-based instruments. The NQU benefitsfrom the psychometric advances of the Neuro-QoL.

The PROMIS R©-Preference (PROPr) project produced a genericutility score for health states described by PROMIS domains.

The NQU project follows a similar methodology to PROPr.

14 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview, cont’d

Most utility-based HRQL measures describe health usingclassical test theory-based instruments. The NQU benefitsfrom the psychometric advances of the Neuro-QoL.

The PROMIS R©-Preference (PROPr) project produced a genericutility score for health states described by PROMIS domains.

The NQU project follows a similar methodology to PROPr.

14 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU Overview, cont’d

Most utility-based HRQL measures describe health usingclassical test theory-based instruments. The NQU benefitsfrom the psychometric advances of the Neuro-QoL.

The PROMIS R©-Preference (PROPr) project produced a genericutility score for health states described by PROMIS domains.

The NQU project follows a similar methodology to PROPr.

14 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU development: A bird’s-eye view

Neuro-QoL domain selection

Survey development, sample recruitment, and datacollection

Calculation of the scoring function

Validation

15 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU development: A bird’s-eye view

Neuro-QoL domain selection

Survey development, sample recruitment, and datacollection

Calculation of the scoring function

Validation

15 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU development: A bird’s-eye view

Neuro-QoL domain selection

Survey development, sample recruitment, and datacollection

Calculation of the scoring function

Validation

15 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU development: A bird’s-eye view

Neuro-QoL domain selection

Survey development, sample recruitment, and datacollection

Calculation of the scoring function

Validation

15 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

NQU development: A bird’s-eye view

Neuro-QoL domain selection

Survey development, sample recruitment, and datacollection

Calculation of the scoring function

Validation

15 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Neuro-QoL domain selection: Focus on MS

Six Neuro-QoL domains were selected:

depression (mood)

fatigue

ability to participate in social roles and activities (socialroles)

cognitive function (thinking)

upper extremity function (upper limbs)

lower extremity function (lower limbs)

16 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Survey development: Preference elicitation

17 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Sample recruitment and data collection

In-person administration in the UK.

Two groups: general population (n = 203) and MSpatients (n = 62)

Survey included:

Preference elicitationsNeuro-QoLLegacy measures (EQ-5D, HUI)PDDS (for MS group)Clinical characteristicsDemographic characteristics

18 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL in practice

Health status: Describe health states as

Θ = (θmood , θfatigue , θsocial , θthinking , θupperlimb, θlowerlimb),

where θdomain is a score on one of the chosen Neuro-QoLdomains.

⇒ Attach a utility value u(Θ) to Θ, for every possible Θ.

19 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL in practice

Health status: Describe health states as

Θ = (θmood , θfatigue , θsocial , θthinking , θupperlimb, θlowerlimb),

where θdomain is a score on one of the chosen Neuro-QoLdomains.

⇒ Attach a utility value u(Θ) to Θ, for every possible Θ.

19 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Utility-based HRQL in practice

Health status: Describe health states as

Θ = (θmood , θfatigue , θsocial , θthinking , θupperlimb, θlowerlimb),

where θdomain is a score on one of the chosen Neuro-QoLdomains.

⇒ Attach a utility value u(Θ) to Θ, for every possible Θ.

19 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Single-attribute utility functions

−3.0 −2.5 −2.0 −1.5 −1.0 −0.5 0.0 0.5

0.0

0.2

0.4

0.6

0.8

1.0

Social

theta

utili

ty

20 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Multi-attribute summary score

The NQU scoring function is defined via a multiplicative model:

NQU(Θ) = 1− c

C

[ ∏

d∈domains

(1 + C · cd (1− ud (θd)))− 1

],

where

Θ = (θmood , θfatigue , θsocial , θthinking , θupperlimb, θlowerlimb)

is a health state formed from Neuro-QoL measurements, andc ,C , cd are constants.

21 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Some highlights of the validation analyses

Mean NQU score of the general population sample is 0.94(on a 0-1 scale). Mean NQU score of the MS sample is0.82. Variation is small enough that the difference issignificant (p < 0.01).

Positively correlated (≈ 0.6) with generic legacy measures(EQ-5D and HUI) in the MS sample.

In the general population sample, the EQ-5D and HUIwere more highly correlated than either measure’scorrelation with the NQU.NQU provides different information than generic measures

Lower PDDS scores ⇒ higher NQU scores

22 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Some highlights of the validation analyses

Mean NQU score of the general population sample is 0.94(on a 0-1 scale). Mean NQU score of the MS sample is0.82. Variation is small enough that the difference issignificant (p < 0.01).

Positively correlated (≈ 0.6) with generic legacy measures(EQ-5D and HUI) in the MS sample.

In the general population sample, the EQ-5D and HUIwere more highly correlated than either measure’scorrelation with the NQU.NQU provides different information than generic measures

Lower PDDS scores ⇒ higher NQU scores

22 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Some highlights of the validation analyses

Mean NQU score of the general population sample is 0.94(on a 0-1 scale). Mean NQU score of the MS sample is0.82. Variation is small enough that the difference issignificant (p < 0.01).

Positively correlated (≈ 0.6) with generic legacy measures(EQ-5D and HUI) in the MS sample.

In the general population sample, the EQ-5D and HUIwere more highly correlated than either measure’scorrelation with the NQU.NQU provides different information than generic measures

Lower PDDS scores ⇒ higher NQU scores

22 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Some highlights of the validation analyses

Mean NQU score of the general population sample is 0.94(on a 0-1 scale). Mean NQU score of the MS sample is0.82. Variation is small enough that the difference issignificant (p < 0.01).

Positively correlated (≈ 0.6) with generic legacy measures(EQ-5D and HUI) in the MS sample.

In the general population sample, the EQ-5D and HUIwere more highly correlated than either measure’scorrelation with the NQU.NQU provides different information than generic measures

Lower PDDS scores ⇒ higher NQU scores

22 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Some highlights of the validation analyses

Mean NQU score of the general population sample is 0.94(on a 0-1 scale). Mean NQU score of the MS sample is0.82. Variation is small enough that the difference issignificant (p < 0.01).

Positively correlated (≈ 0.6) with generic legacy measures(EQ-5D and HUI) in the MS sample.

In the general population sample, the EQ-5D and HUIwere more highly correlated than either measure’scorrelation with the NQU.NQU provides different information than generic measures

Lower PDDS scores ⇒ higher NQU scores

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Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Some highlights of the validation analyses

Mean NQU score of the general population sample is 0.94(on a 0-1 scale). Mean NQU score of the MS sample is0.82. Variation is small enough that the difference issignificant (p < 0.01).

Positively correlated (≈ 0.6) with generic legacy measures(EQ-5D and HUI) in the MS sample.

In the general population sample, the EQ-5D and HUIwere more highly correlated than either measure’scorrelation with the NQU.NQU provides different information than generic measures

Lower PDDS scores ⇒ higher NQU scores

22 / 23 Barry Dewitt Neuro-QoL Utility Score

Neuro-QoLUtility Score

Barry Dewitt

Background

Overview

Domainselection

Survey andsample

Scoringfunction

Validation

Wrapping up

A summary score for 6 domains of the Neuro-QoL will soon beavailable, allowing anyone collecting Neuro-QoL data toundertake preference-based analyses, such as comparativeeffectiveness analyses.

Barry DewittDepartment of Engineering & Public PolicyCarnegie Mellon Universityemail: barrydewitt@cmu.edu

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Neuro-QoLUtility Score

Barry Dewitt

Preference elicitation: What’s your utility for agiven health state?

The Standard Gamble (SG)

Choice A

BestWorst

Worst Health

Chance 60%

Best Health

Chance 40%

Choice B

MiddleMiddle Health

Guaranteed

Barry Dewitt (Carnegie Mellon University) Neuro-QoL Utility Score June 5th, 2019 24

Neuro-QoLUtility Score

Barry Dewitt

Example health states

Barry Dewitt (Carnegie Mellon University) Neuro-QoL Utility Score June 5th, 2019 25

Neuro-QoLUtility Score

Barry Dewitt

Barry Dewitt (Carnegie Mellon University) Neuro-QoL Utility Score June 5th, 2019 26

Neuro-QoLUtility Score

Barry Dewitt

Barry Dewitt (Carnegie Mellon University) Neuro-QoL Utility Score June 5th, 2019 27