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Clinical Trial Summary

The purpose of this research is to find out if there are inflammatory biomarkers (also known as biological markers) in epidural space that can predict response to an epidural steroid injection. This study will also be evaluating whether the results of an EMG study (also known as electromyography) can predict the response to an epidural steroid injection.


Clinical Trial Description

Lumbar spinal stenosis is a common cause of back pain and mobility impairment in older adults. It is often a multi-factorial condition resulting from degenerative changes in the spine, and may result in severe disability, with symptoms of lower back pain and/or pain, numbness and weakness of the lower extremities that are often exacerbated by walking and/or standing. Since lumbar spinal stenosis mostly stems from slowly progressive degenerative changes, symptoms often worsen over time, leading to poor health outcomes and high rates of healthcare utilization. Epidural steroid injection (ESI) with anti-inflammatory compounds such as glucocorticoids is commonly provided to alleviate pain from neurogenic claudication in spinal stenosis: it is estimated that 25% of ESI's performed in the Medicare population and 74% of ESIs in the Veterans Affairs system are for spinal stenosis. However, one recent, large, multi-center, randomized controlled trial (RCT) demonstrated no significant benefit of epidural corticosteroids in alleviating symptoms of spinal stenosis. In this study, Friedly et al. conducted a double-blind, RCT comparing patient outcomes with epidural injection of glucocorticoid plus anesthetic (lidocaine) vs. anesthetic (lidocaine) only. No significant differences were observed at 6 weeks between the two groups of patients with respect to pain-related functional disability or pain intensity. However, a subset of patients who received glucocorticoids plus lidocaine reported significantly higher treatment satisfaction and higher reductions in depressive symptoms. This suggests that ESIs may be effective for a subset of patients with spinal stenosis. Another treatment modality for spinal stenosis is decompression surgery, which may be effective for some patients but is associated with higher risk especially in the elderly and patients with multiple medical comorbidities. In Davis et al.'s observational study, in a two-year period with 68 patients, 32% of patients opted for surgery, 44% of patients were satisfied with non-surgical management and were discharged after 2 years, but the remaining 24% with non-surgical management (some of whom chose to decline surgery) did not seem to be satisfied with treatment. This study indicates the potential key role that non-surgical management options such as ESIs may play, in some patients. However, appropriate patient selection using indicators or biomarkers for patients who may most likely benefit from ESIs would be extremely beneficial. In studying biomarkers that may predict patients' response to ESIs, Scuderi et al. found interferon-gamma (IFG) levels to have high predictive value for patients with lumbar nerve root irritation, while Golish et al. and Smith et al. found fibronectin-aggrecan complex (FAC) levels to have high predictive value for patients with herniated nucleus pulposus (HNP). In addition, many other factors (such as lower age and higher education) have been found to predict better outcome for radiculopathy. In particular, needle electromyography (EMG) has been shown in several studies to be a strong predictor for response to lumbar epidural steroid injection (LESI) and transforaminal epidural steroid injection (TESI) for patients with lumbosacral radiculopathy (LSR). Inspired by these studies, this study aims to explore if certain biomarkers such as IFG & FAC along with EMG findings can help predict which patients with spinal stenosis and neurogenic claudication will optimally benefit from ESIs. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03511053
Study type Interventional
Source Dallas VA Medical Center
Contact
Status Completed
Phase N/A
Start date December 19, 2017
Completion date July 26, 2018

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