Mapping of EQ-5D

Analysts often need to estimate health state utility values as a function of other outcome measures. Utility values like EQ-5D have several unusual characteristics that make standard statistical methods inappropriate.

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Background

The authors have developed a bespoke approach based on mixture models to directly estimate EQ-5D.

An indirect method, 'response mapping', first estimates the level on each of the five dimensions of the EQ-5D descriptive system and then calculates the expected tariff score. These methods have never previously been compared.

Methods

We use a large observational database of patients diagnosed with Rheumatoid Arthritis (n=100,398 observations).

Direct estimation of UK EQ-5D scores as a function of Health Assessment Questionnaire (HAQ), pain and age was performed using a limited dependent variable mixture model.

Indirect modelling was undertaken using a set of generalised ordered probit models with expected tariff scores calculated mathematically. Linear regression was reported for comparison purposes.

Results

The linear model fits poorly, particularly at the extremes of the distribution. Both the bespoke mixture model and the generalised ordered probit approach offer improvements in fit over the entire range of EQ-5D.

Mean average error is 10% and 5% lower compared to the linear model respectively. Root mean squared error is 3% and 2% lower.

The mixture model demonstrates superior performance to the indirect method across almost the entire range of pain and HAQ.

Limitations

There is limited data from patients in the most extreme HAQ health states.

Conclusions

Modelling of EQ-5D from clinical measures is best performed directly using the bespoke mixture model. This substantially outperforms the indirect method in this example.

Linear models are inappropriate, suffer from systematic bias and generate values outside the feasible range.

DSU publication

M Hernández Alava, A Wailoo, F Wolfe, K Michaud. (2014) A comparison of direct and indirect methods for the estimation of health utilities from clinical outcomes. Medical Decision Making October 2014; 34: 919-930 (first published online 2013)

Other DSU work on mapping / EQ-5D

Economic Mapping of Utilities (EMU) – ALDVMM: A command for fitting Adjusted Limited Dependent Variable Mixture Models to EQ-5D (2015)

TSD10: The use of mapping methods to estimate health state utility values

EQ-5D: The incorporation of health benefits in cost utility analysis using the EQ-5D (November 2010)

Related work on mapping of EQ-5D (not DSU-funded)

B Pennington, S Davis (2014) Mapping from the Health Assessment Questionnaire to the EQ-5D: The impact of different algorithms on cost-effectiveness results. Value in Health 17(8):762-771

A Wailoo, M Hernández, C Philips, S Brophy, S Siebert (2015) Modeling health state utility values in ankylosing spondylitis: Comparisons of direct and indirect methods. Value in Health 18(4): 425-431 Jun 2015

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