Rescaling pain intensity measures for meta-analyses of analgesic medicines for low back pain appears justified: an empirical examination from randomised trials.

Objective: Meta-analyses of analgesic medicines for low back pain often rescale measures of pain intensity to use mean difference (MD) instead of standardised mean difference for pooled estimates. Although this improves clinical interpretability, it is not clear whether this method is justified. Our study evaluated the justification for this method.

Methods: We identified randomised clinical trials of analgesic medicines for adults with low back pain that used two scales with different ranges to measure the same construct of pain intensity. We transformed all data to a 0-100 scale, then compared between-group estimates across pairs of scales with different ranges.

Results: Twelve trials were included. Overall, differences in means between pain intensity measures that were rescaled to a common 0-100 scale appeared to be small and randomly distributed. For one study that measured pain intensity on a 0-100 scale and a 0-10 scale; when rescaled to 0-100, the difference in MD between the scales was 0.8 points out of 100. For three studies that measured pain intensity on a 0-10 scale and 0-3 scale; when rescaled to 0-100, the average difference in MD between the scales was 0.2 points out of 100 (range 5.5 points lower to 2.7 points higher). For two studies that measured pain intensity on a 0-100 scale and a 0-3 scale; when rescaled to 0-100, the average difference in MD between the scales was 0.7 points out of 100 (range 6.2 points lower to 12.1 points higher). Finally, for six studies that measured pain intensity on a 0-100 scale and a 0-4 scale; when rescaled to 0-100, the average difference in MD between the scales was 0.7 points (range 5.4 points lower to 8.3 points higher).

Conclusion: Rescaling pain intensity measures may be justified in meta-analyses of analgesic medicines for low back pain. Systematic reviewers may consider this method to improve clinical interpretability and enable more data to be included.

Study Registration/data Availability: Open Science Framework (osf.io/8rq7f).