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下腰痛护理预测性临床生物标志物的开发与应用:国际腰椎研究学会表型/精准脊柱焦点小组的建议

Development and application of predictive clinical biomarkers for low back pain care: recommendations from the ISSLS phenotype/precision spine focus group.

作者信息

Hodges Paul W, Sowa Gwendolyn, O'Neill Conor, Vo Nam, Foster Nadine, Samartzis Dino, Lotz Jeffrey

机构信息

University of Queensland, Brisbane, Australia.

University of Pittsburgh, Pittsburgh, USA.

出版信息

Eur Spine J. 2025 Apr;34(4):1309-1318. doi: 10.1007/s00586-025-08720-4. Epub 2025 Feb 18.

DOI:10.1007/s00586-025-08720-4
PMID:39964488
Abstract

Predictive biomarkers (or moderators of treatment) are features, or more likely feature clusters, that discriminate individuals who are more likely to experience a favourable or unfavourable effect from a specific treatment. Utilization of validated predictive biomarkers for chronic low back pain (CLBP) treatments is a plausible strategy to guide patients more rapidly to effective treatments thereby reducing wastage of finite healthcare funds on treatments that are ineffective (or potentially harmful). Yet, few predictive biomarkers have been successfully validated in clinical studies. This paper summarizes work by the Phenotype/Precision Spine Focus Group of the International Society for the Study of the Lumbar Spine that addressed: (1) relevant definitions for terminology; (2) advantages and disadvantages of different research approaches for the specification of predictive biomarkers; (3) methods for assessment of clinical validity; (4) approaches for their implementation; (5) barriers to predictive biomarker identification; and (6) a prioritised list of recommendations for the development and refinement of predictive biomarkers for CLBP. Key recommendations include the harmonisation of data collection, data sharing, integration of theoretical models, development of new treatments, and health economic analyses to inform cost-benefit of assessments and the application of matched treatments. The complexity of CLBP demands large datasets to derive meaningful progress. This will require coordinated and substantive collaboration involving multiple disciplines and across the research spectrum from the basic sciences to clinical applications.

摘要

预测性生物标志物(或治疗调节因子)是一些特征,更可能是特征簇,它们能够区分哪些个体更有可能从特定治疗中经历有利或不利的效果。利用经过验证的慢性下腰痛(CLBP)治疗预测性生物标志物是一种合理的策略,可引导患者更快地接受有效治疗,从而减少有限医疗保健资金在无效(或可能有害)治疗上的浪费。然而,很少有预测性生物标志物在临床研究中得到成功验证。本文总结了国际腰椎研究学会表型/精准脊柱焦点小组的工作,该工作涉及:(1)术语的相关定义;(2)用于确定预测性生物标志物的不同研究方法的优缺点;(3)临床有效性评估方法;(4)其实施方法;(5)预测性生物标志物识别的障碍;以及(6)CLBP预测性生物标志物开发和完善的优先建议清单。关键建议包括数据收集的协调统一、数据共享、理论模型的整合、新治疗方法的开发以及健康经济分析,以告知评估的成本效益和匹配治疗的应用。CLBP的复杂性需要大量数据集才能取得有意义的进展。这将需要多学科以及从基础科学到临床应用的整个研究领域进行协调一致的实质性合作。

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