Abstract
Chronic pain (CP) that significantly impacts a person's life, known as high impact chronic pain (HICP), is an important measure of CP consequences. The aims of this study were to propose EuroQol 5 Dimension 5 level index (EQ-5D-5L) cutpoints to identify HICP in a cross-sectional discovery dataset (UK Biobank Experience of Pain survey (EOP)) and to validate in an external dataset (the Multiple Integration and Data Annotation Study (MIDAS)). 83,062 EOP participants with CP were included in this analysis. Optimal cutpoints of the EQ-5D-5L for estimating three different definitions of HICP were generated in EOP, using established cutpoints from the Brief Pain Inventory and the Pain, Enjoyment of Life and General Activity Scale. Performance of the EQ-5D-5L and optimal cutpoints were evaluated in EOP and validated in MIDAS, using standard metrics including area under the curve (AUC), sensitivity and specificity. The EQ-5D-5L had an AUC of between 0.841 and 0.872, depending on the definition of HICP. Optimal cutpoints of the EQ-5D-5L were between 0.810 and 0.858. Sensitivity of the cutpoints was between 73.1% and 79.4% and specificity was between 74.8% and 81.7%. The number of pain locations reported by participants affected performance of the EQ-5D-5L and optimal cutpoints. Validation results from MIDAS supported the use of the EQ-5D-5L as a measure of HICP in people reporting CP. This study demonstrates that the EQ-5D-5L is a valid tool for identifying the impact of CP in population-based studies that lack dedicated pain impact measures, enabling wider surveillance and comparison of CP burden.</p>