Comparison of secondary outcome measures at day 7 and week 4 follow-up
| Naproxen | Colchicine | OR (95% CI) (p value)* | OR (95% CI) (p value)† | |
| Complete pain resolution, n (%) | ||||
| 7 days | 115 (67.3) | 116 (67.1) | 0.96 (0.60 to 1.54) (p=0.87) | 0.95 (0.60 to 1.48) (p=0.81) |
| 4 weeks | 130 (75.1) | 130 (73.4) | 0.83 (0.51 to 1.36) (p=0.46) | 0.90 (0.56 to 1.44) (p=0.66) |
| Days to complete pain resolution, median (IQR) | 5 (day 4, week 4) | 6 (day 4, week 4) | – | – |
| Patient assessment of global treatment response (completely/much better), n (%) | ||||
| 7 days | 114 (71.3) | 110 (72.4) | 1.11 (0.67 to 1.84) (p=0.69) | 1.03 (0.62 to 1.70) (p=0.91) |
| 4 weeks | 140 (80.9) | 143 (80.8) | 0.88 (0.51 to 1.52) (p=0.64) | 0.96 (0.56 to 1.64)(p=0.87) |
| Recurrence/relapse of gout flare during 4-week follow-up, n (%) | 40 (30.1) | 54 (35.1) | 1.28 (0.78 to 2.13) (p=0.33) | 1.24 (0.77 to 1.99) (p=0.37) |
| Consultation/re-attendance for gout during 4-week follow-up, n (%) | ||||
| Health professional‡ | 30 (22.6) | 41 (26.6) | 1.43 (0.82 to 2.51) (p=0.213) | 1.39 (0.82 to 2.34) (p=0.22) |
| GP | 26 (19.4) | 39 (25.3) | 1.69 (0.93 to 3.05) (p=0.083) | 1.56 (0.89 to 2.72) (p=0.12) |
| Number of times | ||||
| 1 | 14 (58.3) | 27 (69.2) | – | – |
| 2 | 8 (33.3) | 10 (25.6) | ||
| 3 | 2 (8.3) | 2 (5.1) | ||
| Practice nurse | 7 (5.3) | 10 (6.6) | 1.31 (0.47 to 3.64) (p=0.61) | 1.23 (0.45 to 3.32) (p=0.69) |
| Number of times | ||||
| 1 | 5 (71.4) | 9 (90.0) | – | – |
| 2 | 1 (14.3) | 1 (10.0) | ||
| 3 | 1 (14.3) | 0 (0.0) | ||
| Emergency GP | 6 (4.5) | 6 (3.9) | 0.84 (0.26 to 2.68) (p=0.77) | 0.87 (0.30 to 2.57) (p=0.81) |
| Emergency department | 1 (0.8) | 1 (0.7) | – | 1.23 (0.07 to 21.5) (p=0.89) |
| Taken time off work because of gout during 4-week follow-up, n (%) | 11 (8.6) | 8 (5.3) | 0.61 (0.22 to 1.64) (p=0.33) | 0.76 (0.31 to 1.91) (p=0.57) |
| Days, median (IQR) | 4 (2, 12) | 3 (3, 17) | – | – |
OR for colchicine relative to naproxen.
*Analysis of complete case data (adjusted for baseline pain, age and gender).
†Analysis through multiple imputation via chained equations with logistic (binary/ordinal) regression model (adjusted for age, sex and baseline pain) based on full ITT on 50 imputations.
‡Health professional: GP, practice nurse, emergency GP and/or accident and emergency.
GP, general practitioner; ITT, intention-to-treat.