Generating EQ-5D-3L utility scores from the Dermatology Life Quality Index

Abstract

OBJECTIVES: To develop an algorithm to predict the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L) utility scores from the Dermatology Life Quality Index (DLQI) in psoriasis.

METHODS: This mapping study used data from the British Association of Dermatologists Biologic Interventions Register-a pharmacovigilance register comprising patients with moderate to severe psoriasis on systemic therapies. Conceptual overlap between the EQ-5D-3L and DLQI was assessed using Spearman rank correlation coefficients and exploratory factor analysis. Six regression methods to predict the EQ-5D-3L index (direct mapping) and two regression methods to predict EQ-5D-3L domain responses (response mapping) were tested. Random effects models were explored to account for repeated observations from the same individual. Estimated and actual EQ-5D-3L utility scores were compared using 10-fold cross-validation (in-sample) to evaluate predictive performance. Final models were selected using root mean squared error, mean absolute error, and mean error.

RESULTS: The data set comprised 22,085 observations for which DLQI and EQ-5D-3L were recorded on the same day. A moderate correlation was found between the measures (r = -0.47). Exploratory factor analysis showed that two EQ-5D-3L domains (pain/discomfort and depression/anxiety) were associated with all six DLQI domains. The best-performing model used ordinary least squares with DLQI items, age, and sex as explanatory variables (with squared, cubic, and interaction terms). A tool was produced to allow users to map their data to the EQ-5D-3L, and includes algorithms that require fewer variables (e.g., total DLQI scores).

CONCLUSIONS: This study produced mapping algorithms that can generate EQ-5D-3L utility scores from DLQI data for economic evaluations of health interventions for patients with psoriasis.