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Assessing the Significance of Individual Change in 2 Samples of Patients in Treatment for Low Back Pain Using 5 Different Statistical Indicators

Abstract

Objective

The purpose of this study was to estimate the significance of individual change using 5 statistical indicators in 2 samples of patients treated for low back pain.

Methods

This secondary analysis used observational and clinical trial data from 2 samples of patients with low back pain to compare 5 ways of estimating significant individual change on the Impact Stratification Score (ISS) administered at the following 2 time points: 3 months apart in an observational study of 1680 patients undergoing chiropractic care, and 6 weeks apart in a randomized trial of 750 active-duty military personnel with low back pain. The following 5 methods were compared: (1) standard deviation index; (2) standard error of measurement (SEM); (3) standard error of estimate (SEE); (4) standard error of prediction (SEP); and (5) the reliable change index (RCI). The ISS is the sum of the Patient-Reported Outcomes Measurement Information System (PROMIS)-29 v2.1 physical function, pain interference, and pain intensity scores and is scored to have a possible range of 8 (least impact) to 50 (greatest impact).

Results

The amount of change on the ISS needed for significant individual change in both samples was 5 for the SEM and for the SEE and 7 for the SEP and RCI.

Conclusions

The results of the current study provide some preliminary support for use of the SEP or the RCI to identify significant individual change and provide estimated thresholds of individual change that can be used for the ISS. The SEP and RCI estimates of significant change were consistent with retrospective ratings of change of at least moderately better in prior research. These 2 were less likely than other methods to classify people with low back pain as responders who have not actually gotten better (false positive). In contrast, the SEM and SEE were less likely to miss real change (false negative).

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