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临床试验/NCT04994249
NCT04994249进行中(未招募)不适用

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

Stanford University1 个研究点 分布在 1 个国家目标入组 250 人开始时间: 2022年3月21日最近更新:
适应症

试验速览

阶段
不适用
状态
进行中(未招募)
入组人数
250
试验地点
1
主要终点
Pain Interference:

研究概览

简要总结

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.

详细描述

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.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 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).

排除标准

  • 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.

结局指标

主要结局

Pain Interference:

时间窗: 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)

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Sean Mackey

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

Stanford University

研究点 (1)

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