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

NCT ID: NCT04994249

Last Updated: 2025-05-13

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

250 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-03-21

Study Completion Date

2027-12-31

Brief Summary

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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

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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.

Conditions

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Chronic Musculoskeletal Pain Pain Pain, Chronic Joint Pain

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Institute of Neurological Disorders and Stroke (NINDS)

NIH

Sponsor Role collaborator

Stanford University

OTHER

Sponsor Role lead

Responsible Party

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Sean Mackey

Chief, Division of Pain Medicine Director, Stanford Systems Neuroscience and Pain Lab

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Sean Mackey, MD, PhD.

Role: PRINCIPAL_INVESTIGATOR

Stanford University

Locations

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Stanford University

Palo Alto, California, United States

Site Status RECRUITING

Countries

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United States

Central Contacts

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Anne Cunniffe Marcy, MSBH

Role: CONTACT

6507216931

Facility Contacts

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Anne Cunniffe Marcy, MSBH

Role: primary

650-721-6931

References

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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.

Reference Type BACKGROUND
PMID: 27377620 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28328579 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23246778 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 21931652 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 27825857 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 27280328 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28614083 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 29668841 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 26230739 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 24804882 (View on PubMed)

Other Identifiers

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1R61NS118651-01A1

Identifier Type: NIH

Identifier Source: secondary_id

View Link

60657

Identifier Type: -

Identifier Source: org_study_id

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