Assessment of outcome measures for cost-utility analysis in depression: mapping depression scales onto the EQ-5D-5L

Thor Gamst-Klaussen, Admassu N Lamu, Gang Chen, Jan Abel Olsen

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background
Many clinical studies including mental health interventions do not use a health state utility instrument, which is essential for producing quality-adjusted life years. In the absence of such utility instrument, mapping algorithms can be applied to estimate utilities from a disease-specific instrument.

Aims
We aim to develop mapping algorithms from two widely used depression scales; the Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K-10), onto the most widely used health state utility instrument, the EQ-5D-5L, using eight country-specific value sets.

Method
A total of 917 respondents with self-reported depression were recruited to describe their health on the DASS-21 and the K-10 as well as the new five-level version of the EQ-5D, referred to as the EQ-5D-5L. Six regression models were used: ordinary least squares regression, generalised linear models, beta binomial regression, fractional logistic regression model, MM-estimation and censored least absolute deviation. Root mean square error, mean absolute error and r2 were used as model performance criteria to select the optimal mapping function for each country-specific value set.

Results
Fractional logistic regression model was generally preferred in predicting EQ-5D-5L utilities from both DASS-21 and K-10. The only exception was the Japanese value set, where the beta binomial regression performed best.

Conclusions
Mapping algorithms can adequately predict EQ-5D-5L utilities from scores on DASS-21 and K-10. This enables disease-specific data from clinical trials to be applied for estimating outcomes in terms of quality-adjusted life years for use in economic evaluations.

Declaration of interest
None.
Original languageEnglish
Pages (from-to)160-166
Number of pages7
JournalBritish journal of psychiatry open
Volume4
Issue number4
DOIs
Publication statusPublished - Jul 2018

Keywords

  • statistical methodology
  • cost-effectiveness
  • EQ-5D-5L
  • mapping
  • DASS-21
  • K-10

Cite this

@article{5939c7e046694424967c87c3cb9a254f,
title = "Assessment of outcome measures for cost-utility analysis in depression: mapping depression scales onto the EQ-5D-5L",
abstract = "BackgroundMany clinical studies including mental health interventions do not use a health state utility instrument, which is essential for producing quality-adjusted life years. In the absence of such utility instrument, mapping algorithms can be applied to estimate utilities from a disease-specific instrument.AimsWe aim to develop mapping algorithms from two widely used depression scales; the Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K-10), onto the most widely used health state utility instrument, the EQ-5D-5L, using eight country-specific value sets.MethodA total of 917 respondents with self-reported depression were recruited to describe their health on the DASS-21 and the K-10 as well as the new five-level version of the EQ-5D, referred to as the EQ-5D-5L. Six regression models were used: ordinary least squares regression, generalised linear models, beta binomial regression, fractional logistic regression model, MM-estimation and censored least absolute deviation. Root mean square error, mean absolute error and r2 were used as model performance criteria to select the optimal mapping function for each country-specific value set.ResultsFractional logistic regression model was generally preferred in predicting EQ-5D-5L utilities from both DASS-21 and K-10. The only exception was the Japanese value set, where the beta binomial regression performed best.ConclusionsMapping algorithms can adequately predict EQ-5D-5L utilities from scores on DASS-21 and K-10. This enables disease-specific data from clinical trials to be applied for estimating outcomes in terms of quality-adjusted life years for use in economic evaluations.Declaration of interestNone.",
keywords = "statistical methodology, cost-effectiveness, EQ-5D-5L, mapping, DASS-21, K-10",
author = "Thor Gamst-Klaussen and Lamu, {Admassu N} and Gang Chen and Olsen, {Jan Abel}",
year = "2018",
month = "7",
doi = "10.1192/bjo.2018.21",
language = "English",
volume = "4",
pages = "160--166",
journal = "British journal of psychiatry open",
issn = "2056-4724",
number = "4",

}

Assessment of outcome measures for cost-utility analysis in depression : mapping depression scales onto the EQ-5D-5L. / Gamst-Klaussen, Thor; Lamu, Admassu N; Chen, Gang; Olsen, Jan Abel.

In: British journal of psychiatry open, Vol. 4, No. 4, 07.2018, p. 160-166.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Assessment of outcome measures for cost-utility analysis in depression

T2 - mapping depression scales onto the EQ-5D-5L

AU - Gamst-Klaussen, Thor

AU - Lamu, Admassu N

AU - Chen, Gang

AU - Olsen, Jan Abel

PY - 2018/7

Y1 - 2018/7

N2 - BackgroundMany clinical studies including mental health interventions do not use a health state utility instrument, which is essential for producing quality-adjusted life years. In the absence of such utility instrument, mapping algorithms can be applied to estimate utilities from a disease-specific instrument.AimsWe aim to develop mapping algorithms from two widely used depression scales; the Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K-10), onto the most widely used health state utility instrument, the EQ-5D-5L, using eight country-specific value sets.MethodA total of 917 respondents with self-reported depression were recruited to describe their health on the DASS-21 and the K-10 as well as the new five-level version of the EQ-5D, referred to as the EQ-5D-5L. Six regression models were used: ordinary least squares regression, generalised linear models, beta binomial regression, fractional logistic regression model, MM-estimation and censored least absolute deviation. Root mean square error, mean absolute error and r2 were used as model performance criteria to select the optimal mapping function for each country-specific value set.ResultsFractional logistic regression model was generally preferred in predicting EQ-5D-5L utilities from both DASS-21 and K-10. The only exception was the Japanese value set, where the beta binomial regression performed best.ConclusionsMapping algorithms can adequately predict EQ-5D-5L utilities from scores on DASS-21 and K-10. This enables disease-specific data from clinical trials to be applied for estimating outcomes in terms of quality-adjusted life years for use in economic evaluations.Declaration of interestNone.

AB - BackgroundMany clinical studies including mental health interventions do not use a health state utility instrument, which is essential for producing quality-adjusted life years. In the absence of such utility instrument, mapping algorithms can be applied to estimate utilities from a disease-specific instrument.AimsWe aim to develop mapping algorithms from two widely used depression scales; the Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K-10), onto the most widely used health state utility instrument, the EQ-5D-5L, using eight country-specific value sets.MethodA total of 917 respondents with self-reported depression were recruited to describe their health on the DASS-21 and the K-10 as well as the new five-level version of the EQ-5D, referred to as the EQ-5D-5L. Six regression models were used: ordinary least squares regression, generalised linear models, beta binomial regression, fractional logistic regression model, MM-estimation and censored least absolute deviation. Root mean square error, mean absolute error and r2 were used as model performance criteria to select the optimal mapping function for each country-specific value set.ResultsFractional logistic regression model was generally preferred in predicting EQ-5D-5L utilities from both DASS-21 and K-10. The only exception was the Japanese value set, where the beta binomial regression performed best.ConclusionsMapping algorithms can adequately predict EQ-5D-5L utilities from scores on DASS-21 and K-10. This enables disease-specific data from clinical trials to be applied for estimating outcomes in terms of quality-adjusted life years for use in economic evaluations.Declaration of interestNone.

KW - statistical methodology

KW - cost-effectiveness

KW - EQ-5D-5L

KW - mapping

KW - DASS-21

KW - K-10

U2 - 10.1192/bjo.2018.21

DO - 10.1192/bjo.2018.21

M3 - Article

VL - 4

SP - 160

EP - 166

JO - British journal of psychiatry open

JF - British journal of psychiatry open

SN - 2056-4724

IS - 4

ER -