Abstract
OBJECTIVES: Fibrotic interstitial lung disease (ILD) includes a large group of conditions that lead to scarring of the lungs. The lack of available 5-level EuroQol 5D (EQ5D) data has limited the ability to conduct economic evaluations in ILD. The purpose of this study was to develop and validate a mapping algorithm that predicts EQ5D utilities from commonly collected pulmonary function measurements (forced vital capacity [FVC] and diffusing capacity of the lung for carbon monoxide [DLCO]) in fibrotic ILDs. METHODS: EQ5D utility and pulmonary function measurements from the Canadian Registry for Pulmonary Fibrosis were included. Ordinary least squares (OLS), beta regression, two-part, and tobit models were used to map EQ5D utilities from FVC or DLCO. Model performance was assessed by comparing the predicted and observed utilities. Subgroup analyses were also conducted to test how well models performed across different patient characteristics. The models were then externally validated in the Australian Idiopathic Pulmonary Fibrosis Registry. RESULTS: The OLS model performed as well as other more complex models (root mean squared error: 0.17 for FVC and 0.16 for DLCO). As with the other models, the OLS algorithm performed well across the different subgroups (except for EQ5D utilities < 0.5) and in the external validation cohort. CONCLUSION: We developed a mapping algorithm that predicts EQ5D utilities from FVC and DLCO, with the intent that this algorithm can be applied to clinical trial populations and real-world cohorts that have not prioritized collection of health-related utilities. The mapping algorithm can be used in future economic evaluations of potential ILD therapies.