Humby Frances Claire, Al Balushi Farida, Lliso Gloria, Cauli Alberto, Pitzalis Costantino
Department of Experimental Medicine and Rheumatology, William Harvey Research Institute, Queen Mary University of London, London, UK.
Department of Rheumatology, Royal Hospital, Muscat, Oman.
Front Med (Lausanne). 2017 May 3;4:41. doi: 10.3389/fmed.2017.00041. eCollection 2017.
Although great progress has been made in the past decade toward understanding the pathogenesis of rheumatoid arthritis (RA), clinicians remain some distance from a goal of personalized health care. The capacity to diagnose RA early, predict prognosis, and moreover predict response to biologic therapies has been a research focus for many years. How currently available clinical prediction models can facilitate such goals is reviewed in this article. In addition, the role of current imaging techniques in this regard is also discussed. Finally, the authors review the current literature regarding synovial biomarkers and consider whether integration of synovial pathobiology into clinical prediction algorithms may enhance their predictive value.
尽管在过去十年里,在理解类风湿关节炎(RA)发病机制方面已取得了巨大进展,但临床医生距离个性化医疗的目标仍有一段距离。早期诊断RA、预测预后以及预测对生物疗法的反应能力多年来一直是研究重点。本文将对当前可用的临床预测模型如何促进这些目标进行综述。此外,还将讨论当前成像技术在这方面的作用。最后,作者回顾了关于滑膜生物标志物的当前文献,并考虑将滑膜病理生物学整合到临床预测算法中是否可能提高其预测价值。