Hosnijeh Fatemeh Saberi, Runhaar Jos, van Meurs Joyce B J, Bierma-Zeinstra Sita M
Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands.
Department of General Practice, Erasmus University Medical Center, Rotterdam, The Netherlands.
Maturitas. 2015 Sep;82(1):36-49. doi: 10.1016/j.maturitas.2015.04.004. Epub 2015 Apr 14.
The identification of early biochemical predictors of osteoarthritis (OA) has been the focus of much research over the past few years. However, it still is unclear whether current biochemical markers can be used in prognostic risk assessment of OA. The aim of this systematic review is to evaluate the possible prognostic application of blood and urinary biochemical markers of knee and hip OA. Abstract and full text selection was done by two independent reviewers. A total of 25 relevant publications including 37 biochemical markers of bone and cartilage turnover and inflammation associated with some aspects of OA were reviewed. Most of those biomarkers were studied only once or twice. Due to heterogeneity of both OA-phenotype and determinant among the publications, meta-analysis of the studied biochemical markers was not possible. There was strong evidence for urinary C-terminal telopeptide of collagen type II (uCTX-II) as a prognostic marker for knee OA progression and serum cartilage oligomeric protein (COMP) level as prognostic marker for incidence of knee and hip OA. Evidence for prognostic value of C-reactive protein is still inconclusive. International standardization of future investigations should be pursued to obtain more high-quality, homogenous data on the full spectrum of biochemical OA markers.
在过去几年中,骨关节炎(OA)早期生化预测指标的识别一直是众多研究的重点。然而,目前的生化标志物是否可用于OA的预后风险评估仍不明确。本系统评价的目的是评估膝关节和髋关节OA的血液及尿液生化标志物在预后方面的可能应用。摘要和全文筛选由两名独立评审员完成。共检索了25篇相关文献,其中包括37种与OA某些方面相关的骨和软骨代谢及炎症的生化标志物。这些生物标志物大多仅被研究过一两次。由于各文献中OA表型和决定因素的异质性,无法对所研究的生化标志物进行荟萃分析。有强有力的证据表明,尿Ⅱ型胶原C端肽(uCTX-II)是膝关节OA进展的预后标志物,血清软骨寡聚蛋白(COMP)水平是膝关节和髋关节OA发病的预后标志物。C反应蛋白预后价值的证据仍不确凿。应推进未来研究的国际标准化,以获取关于全谱OA生化标志物的更多高质量、同质化数据。