### Abstract

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 language | English |
---|---|

Pages (from-to) | 160-166 |

Number of pages | 7 |

Journal | British journal of psychiatry open |

Volume | 4 |

Issue number | 4 |

DOIs | |

Publication status | Published - 1 Jul 2018 |

### Keywords

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

### Cite this

*British journal of psychiatry open*,

*4*(4), 160-166. https://doi.org/10.1192/bjo.2018.21

}

*British journal of psychiatry open*, vol. 4, no. 4, pp. 160-166. https://doi.org/10.1192/bjo.2018.21

**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.

Research output: Contribution to journal › Article › Research › peer-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 - 2018/7/1

Y1 - 2018/7/1

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 - cost-effectiveness

KW - DASS-21 K-10

KW - EQ-5D-5L

KW - mapping

KW - Statistical methodology

UR - http://www.scopus.com/inward/record.url?scp=85053284828&partnerID=8YFLogxK

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 -