Suppr超能文献

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

Clinical and biobehavioral phenotypic assessments and data harmonization for the RE-JOIN research consortium: Recommendations for common data element selection.

作者信息

Cruz-Almeida Yenisel, Mehta Bella, Haelterman Nele A, Johnson Alisa J, Heiting Chloe, Ernberg Malin, Orange Dana, Lotz Martin, Boccanfuso Jacqueline, Smith Shad B, Pela Marlena, Boline Jyl, Otero Miguel, Allen Kyle, Perez Daniel, Donnelly Christopher, Almarza Alejandro, Olmer Merissa, Balkhi Henah, Wagenaar Joost, Martone Maryann

机构信息

Pain Research & Intervention Center of Excellence, University of Florida, FL, USA.

Hospital for Special Surgery, New York, USA and Weill Cornell Medical College, New York, USA.

出版信息

Neurobiol Pain. 2024 Aug 22;16:100163. doi: 10.1016/j.ynpai.2024.100163. eCollection 2024 Jul-Dec.

Abstract

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 -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.

摘要

背景

恢复关节健康与功能以减轻疼痛(RE-JOIN)联盟是“助力长期戒除成瘾”(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计划,旨在加速科学解决方案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,重点关注采用最新神经科学方法研究的跨物种的膝关节和颞下颌关节(TMJ)。本文的目的是阐明RE-JOIN联盟收集的人类数据,并阐述其基本原理以及RE-JOIN联盟制定的协调与标准化方法和方案。

方法

联盟范围内的人类模型工作小组确定了将在所有人类研究中收集的RE-JOIN最小协调数据元素,并为制定平行的临床前数据收集标准奠定了基础。数据协调考虑因素包括HEAL计划的要求以及联盟研究人员和信息学、知识管理及数据管理专家的建议。

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的最小人类数据标准,其中包含跨项目和机构所需收集的领域及结果指标。RE-JOIN最小数据标准将包括HEAL通用数据元素(CDE)(例如,标准化人口统计学信息、一般疼痛、社会心理和功能指标)以及RE-JOIN通用数据元素(R-CDE)(即一般和特定关节的标准化且临床上重要的自我报告疼痛和功能指标,以及定量感觉测试中的压痛阈值)。此外,各个机构将收集特定于膝关节或颞下颌关节的酌情使用的、特定地点的指标(例如,扩展的定量感觉测试和步态生物力学评估)。研究团队将通过基于云的安全中央数据存储库和计算基础设施,将标准化元数据的数据集提交给RE-JOIN数据协调中心(DCG),以便研究人员共享并对RE-JOIN收集或获取的数据进行分析。RE-JOIN数据集将去除受保护的健康信息(PHI),并在SPARC门户网站上公开提供,可通过HEAL数据生态系统访问。

结论

数据协调工作为多学科联盟提供了一个跨分散研究团队有效协作的机会,数据标准化为联盟未来高效分析所收集的RE-JOIN数据奠定了框架。所获得的协调表型信息将显著增强我们对人类疼痛 - 病理关系神经生物学的理解,为与临床前模型进行比较提供有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c111/11399706/841759627a8b/gr1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验