Background The importance of assessing health-related quality of life (HRQoL) by patient reported outcomes (PRO) in gout-related research and practice is increasingly recognized. The Gout Impact Scale (GIS) of the Gout Assessment Questionnaire 2.0 (GAQ2.0) has recently been validated in the Caucasian setting (1).

Objectives To determine the validity and reliability of GIS in a multi-ethnic Asian population.

Methods 114 patients with gout in a tertiary hospital in Singapore completed the GAQ2.0, which contains the 24-item GIS. Construct validity was evaluated using both exploratory and confirmatory factor analyses (EFA and CFA). We hypothesized that patients who rated themselves as having more severe gout or experiencing gout flare would have higher GIS scores (i.e. greater impact) compared to patients with less severe gout or in intercritical phase (known-groups validity). In addition, we hypothesized that correlation with RAND-36 physical functioning (PF) scores would be poor, given that GIS is largely a measure of gout impact on mental and social well-being (based on content evaluation). Internal consistency was evaluated using Cronbach’s alpha.

Results 110 patients provided complete data for analyses. Mean (SD) age was 54.3 (16.77), 88.6% men and 67.5% Chinese, 28.1% Malays and 1.6% Indians. CFA based on the original GIS factor structure did not converge. EFA originally revealed 7 factors but these were reduced to 5 factors after removing 6 items that loaded onto multiple factors. The 5 factors are: Gout-specific Distress, Side Effects of Gout Medications, Belief in Gout Medications, Impact of Active Gout on Work and Social Activities, Impact of Chronic Gout on Work and Social Activities. The 5 factors may be further condensed into a single factor allowing for the computation of a single total score reflecting Overall Impact of Gout. In CFA of the modified 18-item GIS (henceforth referred to as mGIS), model fit statistics (Comparative Fit Index, CFI and Tucker Lewis Index, TLI) exceeded 0.9. Patients who rated themselves as having more severe gout (n = 89) reported significantly higher mGIS total score compared to those with less severe gout (mean (SD) score: 58.18(15.71) vs 46.49(13.34), p=0.0014). Similarly, mGIS total score was higher in patients experiencing gout flare (n=23) than those in intercritical phase but the difference did not reach statistical significance (mean (SD) total score: 60.71(14.75) vs 54.51(16.04), p=0.0962), possibly because of small number of patients with flare. Correlation between mGIS and PF is poor (Pearson’s correlation: -0.06). Internal consistency exceeded 0.7 in 4 of 5 factors.

Conclusions The mGIS is a valid and reliable PRO for assessing gout-specific psychosocial well-being in a multi-ethnic Asian population. Internal consistency for the Belief in Gout Medications factor can be improved by writing new item(s). For mGIS to be a comprehensive gout-specific measure of HRQoL (physical, mental and social well-being), new items on physical functioning are needed.

References

1. Hirsch JD et al. Evaluation of an instrument assessing influence of Gout on health-related quality of life. The Journal of rheumatology 2008;35(12):2406

Disclosure of Interest None Declared