Diagnostic and Prognostic Biomarkers for High-impact Chronic Pain: Development and Validation
Study Details
Study Description
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.
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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, we 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, we aim 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.
Study Design
Outcome Measures
Primary Outcome Measures
- 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)
Eligibility Criteria
Criteria
Inclusion Criteria:
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- Inclusion criteria: Adults (18-80 years; ~64% female expected based on clinic distribution) with chronic MSP as categorized by the World Health Organization (WHO).
Exclusion Criteria:
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- 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.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Stanford University | Palo Alto | California | United States | 94304 |
Sponsors and Collaborators
- Stanford University
- National Institute of Neurological Disorders and Stroke (NINDS)
Investigators
- Principal Investigator: Sean Mackey, MD, PhD., Stanford University
Study Documents (Full-Text)
None provided.More Information
Publications
- Bhandari RP, Feinstein AB, Huestis SE, Krane EJ, Dunn AL, Cohen LL, Kao MC, Darnall BD, Mackey SC. Pediatric-Collaborative Health Outcomes Information Registry (Peds-CHOIR): a learning health system to guide pediatric pain research and treatment. Pain. 2016 Sep;157(9):2033-2044. doi: 10.1097/j.pain.0000000000000609.
- Brown JE, Chatterjee N, Younger J, Mackey S. Towards a physiology-based measure of pain: patterns of human brain activity distinguish painful from non-painful thermal stimulation. PLoS One. 2011;6(9):e24124. doi: 10.1371/journal.pone.0024124. Epub 2011 Sep 13.
- Feinstein AB, Sturgeon JA, Darnall BD, Dunn AL, Rico T, Kao MC, Bhandari RP. The Effect of Pain Catastrophizing on Outcomes: A Developmental Perspective Across Children, Adolescents, and Young Adults With Chronic Pain. J Pain. 2017 Feb;18(2):144-154. doi: 10.1016/j.jpain.2016.10.009. Epub 2016 Nov 5.
- Goodin BR, Bulls HW, Herbert MS, Schmidt J, King CD, Glover TL, Sotolongo A, Sibille KT, Cruz-Almeida Y, Staud R, Fessler BJ, Redden DT, Bradley LA, Fillingim RB. Temporal summation of pain as a prospective predictor of clinical pain severity in adults aged 45 years and older with knee osteoarthritis: ethnic differences. Psychosom Med. 2014 May;76(4):302-10. doi: 10.1097/PSY.0000000000000058.
- Karayannis NV, Baumann I, Sturgeon JA, Melloh M, Mackey SC. The Impact of Social Isolation on Pain Interference: A Longitudinal Study. Ann Behav Med. 2019 Jan 1;53(1):65-74. doi: 10.1093/abm/kay017.
- Kutch JJ, Labus JS, Harris RE, Martucci KT, Farmer MA, Fenske S, Fling C, Ichesco E, Peltier S, Petre B, Guo W, Hou X, Stephens AJ, Mullins C, Clauw DJ, Mackey SC, Apkarian AV, Landis JR, Mayer EA; MAPP Research Network. Resting-state functional connectivity predicts longitudinal pain symptom change in urologic chronic pelvic pain syndrome: a MAPP network study. Pain. 2017 Jun;158(6):1069-1082. doi: 10.1097/j.pain.0000000000000886.
- Sharifzadeh Y, Kao MC, Sturgeon JA, Rico TJ, Mackey S, Darnall BD. Pain Catastrophizing Moderates Relationships between Pain Intensity and Opioid Prescription: Nonlinear Sex Differences Revealed Using a Learning Health System. Anesthesiology. 2017 Jul;127(1):136-146. doi: 10.1097/ALN.0000000000001656.
- Sturgeon JA, Dixon EA, Darnall BD, Mackey SC. Contributions of physical function and satisfaction with social roles to emotional distress in chronic pain: a Collaborative Health Outcomes Information Registry (CHOIR) study. Pain. 2015 Dec;156(12):2627-2633. doi: 10.1097/j.pain.0000000000000313.
- Ung H, Brown JE, Johnson KA, Younger J, Hush J, Mackey S. Multivariate classification of structural MRI data detects chronic low back pain. Cereb Cortex. 2014 Apr;24(4):1037-44. doi: 10.1093/cercor/bhs378. Epub 2012 Dec 17.
- Von Korff M, Scher AI, Helmick C, Carter-Pokras O, Dodick DW, Goulet J, Hamill-Ruth R, LeResche L, Porter L, Tait R, Terman G, Veasley C, Mackey S. United States National Pain Strategy for Population Research: Concepts, Definitions, and Pilot Data. J Pain. 2016 Oct;17(10):1068-1080. doi: 10.1016/j.jpain.2016.06.009. Epub 2016 Jul 1.
- 60657
- 1R61NS118651-01A1