Estimating Responders to Treatment Using Five Indices of Significant Individual Change
Abstract Background: Identifying how many individuals significantly improve (“responders”) provides important supplementary information beyond group mean change about the effects of treatment options. This supplemental information can enhance interpretation of clinical trials and observation studies. This study provides a comparison of five ways of estimating the significance of individual change.Methods: Secondary analyses of the Impact Stratification Score (ISS) for chronic low back pain which was administered at two timepoints in two samples: 1) three months apart in an observational study of 1,680 patients undergoing chiropractic care; and 2) 6 weeks apart in a randomized trial of 720 active-duty military personnel with low back pain. The ISS is the sum of the PROMIS-29 v2.1 physical function, pain interference and pain intensity scores and has a possible range of 8 (least impact) to 50 (greatest impact). The five methods of evaluating individual change compared were: 1) standard deviation index; 2) standard error of measurement (SEM); 3) standard error of estimate; 4) standard error of prediction; and 5) reliable change index.Results: Internal consistency reliability of the ISS at baseline was 0.90 in Sample 1 and 0.92 in Sample 2. Effect size of change on the ISS was -0.16 in Sample 1 and -0.59 in Sample 2. The denominators for the five methods in Sample 1 (Sample 2) were 7.6 (8.4) for the standard deviation index, 2.4 (2.4) for the SEM, 2.3 (2.3) for the standard error of estimation, and 3.3 (3.4) for the standard error of prediction and the reliable change index. The amount of change on the ISS needed for significant individual change in both samples was about 15-16 for the standard deviation index, 5 for the SEM and for the standard error of estimation, and 7 for the standard error of prediction and reliable change index. The percentage of people classified as responders ranged from 1% (standard deviation index in Sample 1) to 57% (SEM and standard error of estimate in Sample 2).Conclusions: The standard error of prediction and reliable change index estimates of significant change are consistent with retrospective ratings of change of at least moderately better in prior research. These two are less likely than other methods to classify people as responders who have not actually gotten better.