Developing the Necessary Information for Sample Size Calculations in Future Spinal Cord Stimulation Clinical Trials.

Abstract

Background: Spinal cord stimulation (SCS) is a nonpharmacological, minimally invasive intervention designed to ameliorate chronic low back pain. However, meta-analyses have not supported the use of SCS due to a lack of high-quality evidence. This work provides the necessary information to design better statistically powered clinical trials for SCS by providing estimates and variances for various patient-reported outcomes and biometrics across time in this population.

Methods: A cohort of 18 patients was followed across 7 months before and after SCS implantation. The patients were administered a monthly battery of patient-reported outcomes, and daily biometrics were obtained. Multilevel Bayesian distributional models quantified the median and variance change across time, both of which are necessary in sample size calculations. Secondary to estimating effects, we also determine the probability of a directional effect and equivalence.

Results: Scales for pain show sustained improvements and stable variance. There were no changes in quality-of-life medians or variance. Robust improvements were made in fatigue and reported sleep quality, despite an unclear effect on total hours slept as recorded by the daily wearable. Resting heart rate decreased after SCS and had low changes in variance; whereas pulse rate variability/heart rate variability exhibited no median change across time but wild swings in variance, indicating it is a poor biomarker in this population.

Conclusions: This study reports many patient-reported outcomes and digital biomarkers used in SCS clinical research, including which ones have potential value and the exact information necessary to plan future high-quality clinical trials in the SCS population.

Significance: There is currently only low-quality evidence that spinal cord stimulation is effective for low back pain. This study supplies all the necessary information (effect estimates, variances and within-measure correlations across time) to better estimate sample sizes, a primary criticism of current evidence in this population. We also provide a preliminary indication as to which patient-reported outcomes and wearable measures are most effective in a spinal cord stimulation population.