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Diagnostic and Prognostic Biomarkers for High-impact Chronic Pain: Development and Validation

Recruiting
Conditions
Pain
Chronic Musculoskeletal Pain
Pain, Chronic
Joint Pain
Registration Number
NCT04994249
Lead Sponsor
Stanford University
Brief Summary

To identify diagnostic and prognostic biomarker signatures of recovery versus having persisting high-impact chronic pain and functional disability in adults with Chronic Musculoskeletal Pain.

Detailed Description

Our overall goal is to discover and validate diagnostic and prognostic biomarkers for musculoskeletal high-impact chronic pain. Chronic pain represents a public health crisis that affects 50-100 million Americans and costs over $500 billion dollars annually. Chronic musculoskeletal pain conditions comprise 70-80% of all chronic pain. The highest-need and most impacted patients are those with high-impact chronic pain (affecting \~20 million Americans), or pain associated with substantially restricted work, social, and self-care activities for six or more months. Chronic pain-and high-impact chronic pain in particular-is often treated with prescription opioids, and is linked to opioid-use disorder. Multidisciplinary chronic pain treatments show incomplete recovery at the population level. However, subgroups of individuals completely respond, do not change, or even worsen following pain management. Thus, robust and validated diagnostic and prognostic biomarkers are needed to identify those with high-impact chronic pain and determine the trajectory of outcome (i.e., recovery versus persistence), respectively. Such biomarkers are essential to develop safer, more effective patient-specific treatment strategies, particularly for those who are refractory to current treatment options.

Many factors have been shown to be (1) diagnostic for the severity and impact of chronic pain or (2) prognostic of the trajectory of chronic pain, including those that are related to the central nervous system (CNS; structure, function), psychosocial (e.g., anxiety, catastrophizing, social isolation), sensory (e.g., temporal summation, conditioned pain modulation),1functional (e.g., accelerometry), multiomic (e.g., immune, microbiome), and demographic. However, these studies are limited by (1) association rather than predictive validity; (2) small sample sizes; (3) homogenous populations limiting external validity; and (4) single modality factors. As chronic pain is a biopsychosocial condition, the investigator will need to measure broadly across these multiple dimensions; the most valuable insights will be gained by understanding not only individual pieces of data, but the relationships among them. Recognizing the critical need for rapid, valid, and clinically useful breakthroughs in signature discovery for risk- and treatment-stratification and novel therapeutic targets for chronic pain, as called for in the HEAL initiative, the investigator's aim is to discover reliable, validated diagnostic and prognostic biomarker signatures of musculoskeletal high-impact chronic pain by integrating CNS, multiomic, sensory, functional, psychosocial, and demographic domains.

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
250
Inclusion Criteria
    1. Inclusion criteria: Adults (18-80 years; ~64% female expected based on clinic distribution) with chronic MSP as categorized by the World Health Organization (WHO).
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Exclusion Criteria
    1. Chronic musculoskeletal pain (MSP) explained by inflammatory disease (e.g., rheumatoid arthritis, lupus) or CP with a primary diagnosis other than chronic MSP (e.g., neuropathic pain), (2) significant cognitive impairment, (3) MRI contraindication, (4) medical or psychiatric problems interfering with the study, (5) current medicolegal factors (e.g., open disability claim), (6) plans for surgery during the study, (7) pregnancy and (8) Children under the age of 18 will not be included in the study.
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Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Pain Interference:6 months after baseline assessment

Pain Interference using Patient-Reported Outcome Measurement Information System (PROMIS)-Pain Interference on a T score (mean: 50; standard deviation: 10) and Graded Chronic Pain Scale (GCPS)

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Stanford University

🇺🇸

Palo Alto, California, United States

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