BackgroundThe outcomes of any chronic illness often depend on patients’ adherence with their treatment. A tool is lacking to assess adherence in gout that is standardized, allows real-time feedback, and is easy to understand.ObjectiveWe set out to evaluate the utility of the 8-item Morisky Medication Adherence Scale (MMAS-8) in monitoring medication adherence in a multiethnic Asian gout cohort on urate-lowering therapy (ULT).MethodsThis cohort study recruited patients with gout where baseline and 6-monthly clinical data, self-report of adherence, and health status by Gout Impact Scale (GIS) and EuroQoL-5 dimension 3 levels were collected. Those who received at least 9 months of ULT were analyzed. Convergent and construct validities of MMAS-8 were evaluated against medication possession ratio (MPR) and known groups, clinical outcomes, and patient-reported outcomes. Internal consistency and test–retest reliability were assessed using Cronbach’s alpha and intraclass correlation coefficient (ICC), respectively.ResultsOf 91 patients, 92.3% were male, 72.5% Chinese with mean age 53.5 years. MMAS-8 (mean 6.17) and MPR (mean 96.3%) were poorly correlated (r=0.069, P=0.521). MMAS-8 did not differ between those who did or did not achieve target serum urate (SU) <360 µmol/L (P=0.852); or among those whose SU improved, stagnated, or worsened during follow-up (P=0.777). Adherence was associated with age (β=0.256, P=0.015) and education level (P=0.011) but not comorbidities, polypharmacy, or flare frequency. Concerns for medication side effects and anxiety or depression were associated with lower MMAS-8 (P<0.005). Internal consistency was acceptable (α=0.725) and test–retest reliability was satisfactory (ICC =0.70, 95% confidence interval [CI] 0.36–0.88).ConclusionMMAS-8 had limited construct validity in assessing medication adherence to ULT in our gout patients. Nevertheless, it identified patients bothered or worried about ULT side effects, and those with underlying anxiety or depression, for whom targeted education and coping support may be useful.

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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. Refe...