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

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.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. 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 interestNone.

SUBMITTER: Gamst-Klaussen T

PROVIDER: S-EPMC6034447 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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

Gamst-Klaussen Thor T Lamu Admassu N AN Chen Gang G Olsen Jan Abel JA

BJPsych open 20180701 4

<h4>Background</h4>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.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) ...[more]

PMID: 29897028

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Project description:BackgroundEQ5D is a generic measure of health. It provides a single index value for health status that can be used in the clinical and economic evaluation of healthcare. Oxford Knee Score (OKS) is a joint-specific outcome measure tool designed to assess symptoms and function in osteoarthritis patients after joint replacement surgery. Though widely used, it has the disadvantage of lacking health index value. To fill the gap between functional and generic questionnaires with economic value, we linked generic EQ-5D-5L to the specific OKS to give a single index value for health status in KOA patients.Questions/purposesDeveloping and evaluating an algorithm to estimate EuroQoL generic health utility scores (EQ-5D-5L) from the disease-specific OKS using data from patients with knee osteoarthritis (KO).Patients and methodsThis is a cross-sectional study of 571 patients with KO. We used four distinct mapping algorithms: Cumulative Probability for Ordinal Data, Penalized Ordinal Regression, CART (Classification and Regression Trees), and Ordinal random forest. We compared the resultant models' degrees of accuracy.ResultsMobility was best predicted by penalized regression with pre-processed predictors, usual activities by random forest, pain/discomfort by cumulative probability with pre-processed predictors, self-care by random forest with RFE (recursive feature elimination) predictors, and anxiety/depression by CART with RFE predictors. Model accuracy was lowest with anxiety/depression and highest with mobility and usual activities. Using available country value sets, the average MAE was 0.098 ± 0.022, ranging from 0.063 to 0.142; and the average MSE was 0.020 ± 0.008 ranging from 0.008 to 0.042.ConclusionsThe current study derived accurate mapping techniques from OKS to the domains of EQ-5D-5L, allowing for the computation of QALYs in economic evaluations. A machine learning-based strategy offers a viable mapping alternative that merits further exploration.

Project description:This is a prospective study to establish prediction models that map the refined Scoliosis Research Society 22-item (SRS-22r) onto EuroQoL-5 dimension 5-level (EQ-5D-5L) utility scores in adolescent idiopathic scoliosis (AIS) patients. Comparison of treatment outcomes in AIS can be determined by cost-utility analysis. However, the mainstay spine-specific health-related quality of life outcome measure, the SRS-22r questionnaire does not provide utility assessment. In this study, AIS patients were prospectively recruited to complete both the EQ-5D-5L and SRS-22r questionnaires by trained interviewers. Ordinary least squares regression was undertaken to develop mapping models, which the validity and robustness were assessed by using the 10-fold cross-validation procedure. EQ-5D-5L utility scores were regressed on demographics, Cobb angle, curve types, treatment modalities, and five domains of the SRS-22r questionnaire. Three models were developed using stepwise selection method. EQ-5D-5L scores were regressed on 1) main effects of SRS-22r subscale scores, 2) as per 1 plus squared and interaction terms, and 3) as per 2 plus demographic and clinical characteristics. Model goodness-of-fit was assessed using R-square, adjusted R-square, and information criteria; whereas the predictive performance was evaluated using root mean square error (RMSE), mean absolute error (MAE), and the proportion of absolute error within the threshold of 0.05 and 0.10. A total of 227 AIS patients with mean age of 15.6 years were recruited. The EQ-5D-5L scores were predicted by four domains of SRS-22r (main effects of 'Function', 'Pain', 'Appearance' and 'Mental Health', and squared term of 'Function' and 'Pain'), and Cobb angle in Model 3 with the best goodness-of-fit (R-square/adjusted R-square: 62.1%/60.9%). Three models demonstrated an acceptance predictive performance in error analysis applying 10-fold cross-validation to three models where RMSE and MAE were between 0.063-0.065 and between 0.039-0.044, respectively. Model 3 was therefore recommended out of three mapping models established in this paper. To our knowledge, this is the first study to map a spine-specific health-related quality of life measure onto EQ-5D-5L for AIS patients. With the consideration and incorporation of demographic and clinical characteristics, over 60% variance explained by mapping model 3 enabled the satisfactory prediction of EQ-5D-5L utility scores from existing SRS-22r data for health economic appraisal of different treatment options.

Project description:BackgroundThe majority of patient reported outcome measures (PROMs) don't have population norms in Romania. This is the case with the EQ-5D as well. Therefore, we aimed to estimate population norms for the Romanian versions of the EQ-5D-5L, EQ-5D-3L, their indexes, and the EQ-VAS.MethodsA cross-sectional survey was conducted in all regions of Romania from November 2018 to November 2019. A three-stage probability sampling procedure stratified by region and settlement size was used to select a representative sample. Interviews were computer-assisted and conducted in respondents' homes by trained interviewers. Health status was assessed with the EQ-5D-5L, the EQ-5D-3L and the EQ VAS. Descriptive statistics were used to estimate population norms by age groups and sex for the EQ-5D-5L, the EQ-5D-3L, their indexes and the EQ VAS. Population norms were weighted using survey weights. Indexes for the EQ-5D questionnaires were estimated using the recently developed Romanian value sets.ResultsData from 1,649 interviews was analysed in the present study. Survey weights were used so that sex and place of residence ratios for the weighted sample matched the Romanian general population distribution. Participants' mean age was 47.4 years (SE = 1.157) and 50.3% of them reported being in good health. The dimension for which people reported the highest number of problems for both questionnaires was the pain/discomfort dimension. Men aged 35 plus reported fewer problems with pain/discomfort than women for both the EQ-5D-5L and EQ-5D-3L. Health decreased with age as shown by the decrease from age group 18-24 to age group 75 plus in the indexes of both questionnaires: from 0.977 (SE = 0.005) to 0.765 (SE = 0.017) for EQ-5D-5L and from 0.981 (SE = 0.005) to 0.784 (SE = 0.019) for EQ-5D-3L. There was 29.9 points drop in the EQ VAS score between the youngest and oldest group.ConclusionsPopulation norms for the Romanian versions of the EQ-5D-5L, EQ-5D-3L, their indexes, and the EQ VAS are now available. These can now be used as reference values by healthcare professionals, researchers and decision-makers leading to a further development of health-related quality of life research in Romania.

Dataset Information

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

Publications

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

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