Abstract

Background: Decision makers require preference based utilities to allocate healthcare resources when often only non-preference based health related quality of life (HRQoL) data is available. This study was an attempt to bridge this gap using a “mapping” exercise between IBDQ and EQ-5D. Objectives: To generate preference based utilities for IBD patients based on their HRQoL assessed using IBDQ. Methods: Spanish IBD patients completing the Spanish version of IBDQ and EQ-5D were randomly allocated to the analysis sample and validation sample. EQ-5D scores were estimated using the Spanish tariffs. A stepwise forward OLS regression consisting of a combination of important patient characteristics and significant IBDQ domains was used to estimate algorithms to derive EQ-5D utilities. Adjusted R-square and root mean-squared error (RMSE) were used to select the most appropriate algorithm. The preferred algorithm was validated for predictive ability using the validation sample. Similar exercise was carried out to generate an algorithm using the VAS values of EQ-5D. Results: The sample (n = 424) consisted of IBD patients with a mean age of 35 years and median disease duration of 4.33 years. 57% of patients were in remission and 15% patients had previous surgery. Disease severity (Harvey-Bradshaw/Rachmilewitz index) was correlated with IBDQ (r = -0.75) and EQ-5D (r = -0.58). The preferred algorithm for EQ-5D tariff values included three domains; the systemic symptoms, functional impairment and emotional function. Adjusted R-square was 58.2% and RMSE was 0.1264. In the validation analysis, the algorithm explained 48.6% of the variation in EQ-5D utilities. Table. Conclusion: This regression approach enables clinicians and decision makers to estimate preference based utilities from IBDQ in IBD patients. The algorithm appears to be fairly robust based on the explanatory power of the algorithm and validation results. Tabled 1 EQ-5D tariff EQ-5D VAS Constant 0.22934 5.8046 Global Score - 11.9942 Systemic symptoms 0.04957 - Functional impairment 0.04010 - Emotional function 0.01849 - Adj R sq RMSE Adj R sq RMSE Analysis sample (n = 324) 58.2% 0.1264 55.9% 14.001 Validation sample (n = 100) 48.6% 0.1420 51.44% 12.62 Open table in a new tab

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