Health-related quality of life in Singapore: Population norms for the EQ-5D-5L and EORTC QLQ-C30

Abstract

Introduction: Comparison of patient health-related quality of life (HRQOL) scores to a reference group is needed to quantify the HRQOL impact of disease or treatment. This study aimed to establish population norms for 2 HRQOL questionnaires—EuroQol 5-dimension 5-level questionnaire (EQ-5D-5L) and European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core Questionnaire 30 (EORTC QLQ-C30) according to age, sex and ethnicity—and to explore relationships between the EQ-5D-5L, EORTC QLQ-C30 and sociodemographic characteristics. We used a representative sample of adult Singapore residents aged 21 years and above. Method: This study used data collected from a cross-sectional household survey in which 600 adult Singaporeans completed questions on sociodemographic characteristics—the EQ-5D-5L and the EORTC QLQ-C30. Multiple linear regression analyses were conducted to explore associations between sociodemographic characteristics, the EQ-5D-5L scores and the EORTC QLQ-C30 scores. Regression-based population norms were computed for each subgroup using a post-stratification method. Results: In multiple linear regression analysis, age was significantly associated with EQ-5D-5L index and visual analogue scale (VAS) scores, while no sociodemographic characteristics were significantly associated with EORTC QLQ-C30 summary scores. The normative EQ-5D-5L index and VAS scores decreased in adults aged 65 years and above, and EQ-5D-5L index scores were slightly lower in females than males and in non-Chinese than Chinese. The normative EORTC QLQ-C30 summary scores were slightly higher in Chinese than in the non-Chinese group and in the 45–64 age group than other age groups. Conclusion: This study provides population norms for the EQ-5D-5L and EORTC QLQ-C30 for the general adult population in Singapore. Future studies of patient populations in Singapore using EQ-5D-5L or QLQ-C30 can use these normative data to interpret the HRQOL data collected.