RE-JOIN 研究联盟的临床和生物行为表型评估及数据协调:通用数据元素选择建议

Q2 Medicine Neurobiology of Pain Pub Date : 2024-07-01 DOI:10.1016/j.ynpai.2024.100163
Yenisel Cruz-Almeida , Bella Mehta , Nele A. Haelterman , Alisa J. Johnson , Chloe Heiting , Malin Ernberg , Dana Orange , Martin Lotz , Jacqueline Boccanfuso , Shad B. Smith , Marlena Pela , Jyl Boline , Miguel Otero , Kyle Allen , Daniel Perez , Christopher Donnelly , Alejandro Almarza , Merissa Olmer , Henah Balkhi , Joost Wagenaar , Maryann Martone
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引用次数: 0

摘要

背景恢复关节健康和功能以减轻疼痛(RE-JOIN)联盟是 "长期帮助戒毒®(HEAL)计划 "的一部分。HEAL 是一项雄心勃勃的全美国国立卫生研究院(NIH)倡议,旨在加快科学解决方案的步伐,以遏制全国阿片类药物公共卫生危机。RE-JOIN联盟的总体目标是采用最新的神经科学方法,确定慢性关节疼痛介导神经元如何支配不同的关节和关节周围组织,重点是跨物种的膝关节和颞下颌关节(TMJ)。本手稿旨在阐明 RE-JOIN 联合体收集的人类数据,并阐述其基本原理以及 RE-JOIN 联合体制定的协调和标准化方法和协议。方法整个联合体的人类模型工作分组制定了 RE-JOIN 最低协调数据元素,将在所有人类研究中收集这些元素,并为制定平行的临床前数据收集标准奠定基础。数据协调方面的考虑因素包括 HEAL 计划的要求,以及联盟研究人员和信息学、知识管理和数据整理专家的建议。结果多学科专家(包括临床前和临床研究人员,以及临床科学家)制定了 RE-JOIN 最低人体数据标准,其中包括跨项目和跨机构收集的所需领域和结果测量。RE-JOIN 最低数据标准将包括 HEAL 通用数据元素 (CDE)(如标准化人口统计学、一般疼痛、社会心理和功能测量)和 RE-JOIN 通用数据元素 (R-CDE)(即一般和特定关节的标准化和临床重要的自我报告疼痛和功能测量,以及定量感官测试的压力痛阈值)。此外,各研究机构还将收集针对膝关节或颞下颌关节的特定部位测量数据(如扩大的定量感觉测试和步态生物力学评估)。研究团队将通过一个安全的云端中央数据存储库和计算基础设施,向 RE-JOIN 数据协调中心 (DCG) 提交标准化元数据集,供研究人员共享和分析由 RE-JOIN 收集或为 RE-JOIN 获取的数据。RE-JOIN 数据集将去除受保护的健康信息 (PHI),并在 SPARC 门户网站上公开发布,同时可通过 HEAL 数据生态系统访问。所获得的统一表型信息将极大地提高我们对人类疼痛与病理关系的神经生物学的理解,为与临床前模型进行比较提供宝贵的见解。
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Clinical and biobehavioral phenotypic assessments and data harmonization for the RE-JOIN research consortium: Recommendations for common data element selection

Background

The Restoring Joint Health and Function to Reduce Pain (RE-JOIN) Consortium is part of the Helping to End Addiction Long-term® (HEAL) Initiative. HEAL is an ambitious, NIH-wide initiative to speed scientific solutions to stem the national opioid public health crisis. The RE-JOIN consortium’s over-arching goal is to define how chronic joint pain-mediating neurons innervate different articular and peri-articular tissues, with a focus on the knee and temporomandibular joints (TMJ) across species employing the latest neuroscience approaches. The aim of this manuscript is to elucidate the human data gathered by the RE-JOIN consortium, as well as to expound upon its underlying rationale and the methodologies and protocols for harmonization and standardization that have been instituted by the RE-JOIN Consortium.

Methods

The consortium-wide human models working subgroup established the RE-JOIN minimal harmonized data elements that will be collected across all human studies and set the stage to develop parallel pre-clinical data collection standards. Data harmonization considerations included requirements from the HEAL program and recommendations from the consortium’s researchers and experts on informatics, knowledge management, and data curation.

Results

Multidisciplinary experts − including preclinical and clinical researchers, with both clinician-scientists- developed the RE-JOIN’s Minimal Human Data Standard with required domains and outcome measures to be collected across projects and institutions. The RE-JOIN minimal data standard will include HEAL Common Data Elements (CDEs) (e.g., standardized demographics, general pain, psychosocial and functional measures), and RE-JOIN common data elements (R-CDE) (i.e., both general and joint-specific standardized and clinically important self-reported pain and function measures, as well as pressure pain thresholds part of quantitative sensory testing). In addition, discretionary, site-specific measures will be collected by individual institutions (e.g., expanded quantitative sensory testing and gait biomechanical assessments), specific to the knee or TMJ. Research teams will submit datasets of standardized metadata to the RE-JOIN Data Coordinating Center (DCG) via a secure cloud-based central data repository and computing infrastructure for researchers to share and conduct analyses on data collected by or acquired for RE-JOIN. RE-JOIN datasets will have protected health information (PHI) removed and be publicly available on the SPARC portal and accessible through the HEAL Data Ecosystem.

Conclusion

Data Harmonization efforts provide the multidisciplinary consortium with an opportunity to effectively collaborate across decentralized research teams, and data standardization sets the framework for efficient future analyses of RE-JOIN data collected by the consortium. The harmonized phenotypic information obtained will significantly enhance our understanding of the neurobiology of the pain-pathology relationships in humans, providing valuable insights for comparison with pre-clinical models.

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来源期刊
Neurobiology of Pain
Neurobiology of Pain Medicine-Anesthesiology and Pain Medicine
CiteScore
4.40
自引率
0.00%
发文量
29
审稿时长
54 days
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