GIS is a validated HRQOL instrument for gout [7
]. With a renewed interest in the development of new therapeutics in gout, assessment of HRQOL using validated measures will become increasingly important. We show that a change of 5–8 points (0–100 scale) for the four different GIS scales is the MID for improvement in an RCT of patients with gout. This estimate is similar to other HRQOL measures scored on a 0–100 scale. For example, Kosinski et al
] found that 5–10 points constituted MID estimates for short form (SF)-36 scales in patients with active RA. Also, a 10-point change in patient-reported outcome on a 0–100
mm visual analogue scale is considered an MID estimate for improvement [11
MID estimates provide a benchmark for the future design of gout clinical trials by helping researchers and clinicians understand whether HRQOL-score differences between two treatment groups are meaningful, or if changes within one group over time are meaningful [10
]. For example, an average change of 3 points on the Gout Concern Overall scale (0–100 scale) may be statistically significant for a new treatment in a gout clinic trial, but may not be perceived as beneficial by the subjects. Thus, differences in scores smaller than the MID are considered unimportant, regardless of whether statistical significance is reached. MID can also be useful for determining sample size for future studies [22
]. It is important to note that MID estimates are applicable at the group level and not at the individual level. Other statistical tests have been recommended to assess statistical significance at an individual level [11
Although we show that a change of 5–8 points in GIS scales is the MID, this should not be interpreted that a change of <5 points is not clinically important as there is an inherent uncertainty around MID estimates. Previous studies have reported this uncertainty around the MID estimates [12
]; hence, experts recommend using several anchors. In addition, they suggest gathering data from both observational and clinical trials to gather confidence in MID estimates [12
], as it is unlikely that a single MID estimate is applicable to all patient populations: future studies should address MID estimates of GIS in other gout cohorts.
We corroborated our data by calculating ES and SEM. ES provides a uniform platform for different HRQOL instruments and explores the extent to which MID estimates are similar or vary across instruments [19
]. Our study is in alignment with other studies that have shown that an ES 0.20–0.50 corresponds to the MID for a patient-reported outcome measure [12
]. SEM is a distribution method and complements the anchor-based MID estimates. Previously, researchers have found a close correspondence between the anchor-based approach and a criterion of one SEM [25
]. In our case, we found similar MID estimates for Gout Concern Overall and Well-Being Impact scales between anchor- and distribution-based methods. For Unmet Gout Treatment Need and Gout Concern during Attack, MID estimates using anchor-based were 2–4 points lower than the SEM method indicated. Since anchor-based methods were our primary methodology [12
], we present our MID estimates calculated using anchor-based methods acknowledging the variability around it (as presented in the previous paragraph).
Our study has several strengths. First, our MID estimates are based on a sample of patients participating in an RCT in which gout symptoms, and thus impact on HRQOL, changed. Secondly, we prospectively incorporated anchors with an a priori aim to calculate MID estimates. Thirdly, our estimates were similar using the anchor- and distribution-based approaches, giving confidence in our estimates.
Our study had some limitations as well. Our MID estimates are based on a small number of patients; specifically, those experiencing only minimal improvement between Weeks 4 and 8 of a clinical trial with only total 73 patients. For the current analysis, we found lower correlations than recommended by experts partly caused by a relatively small sample size. This may have led to increased variability observed in MID estimates [12
]. The low correlation coefficients found in our study do not invalidate the MID estimates per se
, but should be considered preliminary and further validated in the future. In conclusion, the MID estimates for GIS scales are between 5 and 8 points using anchor- and distribution-based methods. This information can facilitate interpretation of GIS in future gout trials and day-to-day clinical practice and care.