Detection of EEG-Based Biomarkers of Chronic Low Back Pain
- Conditions
- Chronic Low-back PainHealthy
- Interventions
- Behavioral: Resting State EEGBehavioral: Picture Viewing EEGBehavioral: Stop Signal EEG
- Registration Number
- NCT06025201
- Lead Sponsor
- Stanford University
- Brief Summary
Chronic low back pain (CLBP) is a pervasive disorder affecting up to one-fifth of adults globally and is the single greatest cause of disability worldwide. Despite the high prevalence and detrimental impact of CLBP, its treatments and mechanisms remain largely unclear. Biomarkers that predict symptom progression in CLBP support precision-based treatments and ultimately aid in reducing suffering. Longitudinal brain-based resting-state neuroimaging of patients with CLBP has revealed neural networks that predict pain chronification and its symptom progression. Although early findings suggest that measurements of brain networks can lead to the development of prognostic biomarkers, the predictive ability of these models is strongest for short-term follow-up. Measurements of different neural systems may provide additional benefits with better predictive power.
Emotional and cognitive dysfunction is common in CLBP, occurring at the behavioral and cerebral level, presenting a unique opportunity to detect prognostic brain-based biomarkers. Likewise, improvements in electroencephalogram (EEG) neuroimaging strategies have led to increased spatial resolution, enabling researchers to overcome the limitations of classically used neuroimaging modalities (e.g., magnetic resonance imaging \[MRI\] and functional MRI), such as high cost and limited accessibility. Using longitudinal EEG, this patient-oriented research project will provide a comprehensive neural picture of emotional, cognitive, and resting-state networks in patients with CLBP, which will aid in predicting symptom progression in CLBP. Through this award, the investigators will use modern EEG source analysis strategies to track biomarkers at baseline and 1- and 2-month follow-ups and their covariance with markers for pain and emotional and cognitive dysfunction. A 5-month follow up will also be used to only assess patient reported outcomes. In Aim 1, the investigators will identify and characterize differences in resting-state, emotional, and cognitive networks between patients with CLPB and age/sex-matched controls. In Aim 2, the investigators will identify within-subject changes across time and their relationship with clinical symptoms. In Aim 3, as an exploratory aim, the investigators will apply machine- and deep-learning strategies to detect a comprehensive signature of CLBP using EEG features from resting-state, emotional, and cognitive networks.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 130
- Current diagnosis of Chronic Low Back Pain
- Current diagnosis of cancer
- Severe psychiatric conditions
- Pending personal litigation relating to an injury or receiving workers' compensation benefits
- Being a non-English speaker.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description Single Arm Resting State EEG All participants will complete all interventions Single Arm Stop Signal EEG All participants will complete all interventions Single Arm Picture Viewing EEG All participants will complete all interventions
- Primary Outcome Measures
Name Time Method Pain Intensity changes from baseline as assessed by the PROMIS current, 7 day maximal and 7 day average Baseline, 1-month, 2-month and 5-month follow-ups Within subjects change in pain intensity from baseline to each follow up point. Pain intensity measures are 0-10 range with larger numbers indicating more pain
EEG late positive potential changes from baseline Baseline, 1-month and 2-month follow-ups Within subjects change in late positive potential from baseline to each follow up point.
EEG resting state functional connectivity changes from baseline Baseline, 1-month and 2-month follow-ups Within subjects change in resting state functional connectivity from baseline to each follow up point.
EEG error related negativity changes from baseline Baseline, 1-month and 2-month follow-ups Within subjects change in error related negativity from baseline to each follow up point.
- Secondary Outcome Measures
Name Time Method Neuropsychological changes from baseline as assessed by the NIH toolbox Baseline, 1-month and 2-month follow-ups Within subjects change in metrics of fluid and crystallized intelligence from baseline to each follow up point
Trial Locations
- Locations (1)
Stanford's Systems and Neuroscience Pain Lab
🇺🇸Palo Alto, California, United States