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Effect size varies based on calculation method and may affect interpretation of treatment effect: an illustration using randomised clinical trials in osteoarthritis

Posted on 2024-04-23 - 04:01
Abstract Background To illustrate how (standardised) effect sizes (ES) vary based on calculation method and to provide considerations for improved reporting. Methods Data from three trials of tanezumab in subjects with osteoarthritis were analyzed. ES of tanezumab versus comparator for WOMAC Pain (outcome) was defined as least squares difference between means (mixed model for repeated measures analysis) divided by a pooled standard deviation (SD) of outcome scores. Three approaches to computing the SD were evaluated: Baseline (the pooled SD of WOMAC Pain values at baseline [pooled across treatments]); Endpoint (the pooled SD of these values at the time primary endpoints were assessed); and Median (the median pooled SD of these values based on the pooled SDs across available timepoints). Bootstrap analyses were used to compute 95% confidence intervals (CI). Results ES (95% CI) of tanezumab 2.5 mg based on Baseline, Endpoint, and Median SDs in one study were − 0.416 (− 0.796, − 0.060), − 0.195 (− 0.371, − 0.028), and − 0.196 (− 0.373, − 0.028), respectively; negative values indicate pain improvement. This pattern of ES differences (largest with Baseline SD, smallest with Endpoint SD, Median SD similar to Endpoint SD) was consistent across all studies and doses of tanezumab. Conclusion Differences in ES affect interpretation of treatment effect. Therefore, we advocate clearly reporting individual elements of ES in addition to its overall calculation. This is particularly important when ES estimates are used to determine sample sizes for clinical trials, as larger ES will lead to smaller sample sizes and potentially underpowered studies. Trial Registration Clinicaltrials.gov NCT02697773, NCT02709486, and NCT02528188.

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Advances in Rheumatology

AUTHORS (9)

Thomas J. Schnitzer
Philip G. Conaghan
Francis Berenbaum
Lucy Abraham
Joseph C. Cappelleri
Andrew G. Bushmakin
Lars Viktrup
Ruoyong Yang
Mark T. Brown
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