Mapping AcroQoL scores to EQ-5D to obtain utility values for patients with acromegaly

Abstract

Aims: To estimate a preference-based single index for the disease-specific instrument (AcroQoL) by mapping it onto the EQ-5D to assist in future economic evaluations.

Materials and methods: A sample of 245 acromegaly patients with AcroQoL and EQ-5D scores was obtained from three previously published European studies. The sample was split into two: one sub-sample to construct the model (algorithm construction sample, n = 184), and the other one to confirm it (validation sample, n = 61). Various multiple regression models including two-part model, tobit model, and generalized additive models were tested and/or evaluated for predictive ability, consistency of estimated coefficients, normality of prediction errors, and simplicity.

Results: Across these studies, mean age was 50–60 years and the proportion of males was 36–59%. At overall level the percentage of patients with controlled disease was 37.4%. Mean (SD) scores for AcroQoL Global Score and EQ-5D utility were 62.3 (18.5) and 0.71 (0.28), respectively. The best model for predicting EQ-5D was a generalized regression model that included the Physical Dimension summary score and categories from questions 9 and 14 as independent variables (Adj. R² = 0.56, with mean absolute error of 0.0128 in the confirmatory sample). Observed and predicted utilities were strongly correlated (Spearman r = 0.73, p < .001) and paired t-Student test revealed non-significant differences between means (p > .05). Estimated utility scores showed a minimum error of ≤10% in 45% of patients; however, error increased in patients with an observed utility score under 0.2. The model’s predictive ability was confirmed in the validation cohort.

Limitations and conclusions: A mapping algorithm was developed for mapping of AcroQoL to EQ-5D, using patient level data from three previously published studies, and including validation in the confirmatory sub-sample. Mean (SD) utilities index in this study population was estimated as 0.71 (0.28). Additional research may be needed to test this mapping algorithm in other acromegaly populations.

Keywords:

• Acromegaly
• Utilities
• Mapping
• AcroQoL

Transparency

Declaration of funding

This project was performed with an unrestricted grant from Novartis Oncology. AF, a Novartis Oncology employee when the study was implemented, participated in the study design, preparation and revision of the statistical analysis, and preparation of the manuscript.

Declaration of financial/other interests

AF was an employee of Novartis Oncology when the study was performed. All the other authors declare that they have no competing interests. Peer reviewers on this manuscript have received an honorarium from JME for their review work, but have no other relevant financial relationships to disclose.

Acknowledgments

The authors want to thank Dr Lazaros Andronis, Health Economics Unit, School of Health and Population Sciences, University of Birmingham, UK, and Dr Billingsley Kaambwa, Health Economist, School of Medicine, Flinders University, Australia, for their methodological comments to the project.

Previous presentations

Partial information included in this paper has been previously presented as a poster at the European ISPOR Congress 2017 (Glasgow).