Can We Identify Patients with High Risk of Osteoarthritis Progression Who Will Respond to Treatment? A Focus on Biomarkers and Frailty.
Can We Identify Patients with High Risk of Osteoarthritis Progression Who Will Respond to Treatment? A Focus on Biomarkers and Frailty.
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DOI：
10.1007/s40266-015-0276-7
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发表时间：
2015-07
期刊：
影响因子：
2.8
通讯作者：
Reginster JY
中科院分区：
文献类型：
--
作者：
Arden N;Richette P;Cooper C;Bruyère O;Abadie E;Branco J;Brandi ML;Berenbaum F;Clerc C;Dennison E;Devogelaer JP;Hochberg M;D'Hooghe P;Herrero-Beaumont G;Kanis JA;Laslop A;Leblanc V;Maggi S;Mautone G;Pelletier JP;Petit-Dop F;Reiter-Niesert S;Rizzoli R;Rovati L;Tajana Messi E;Tsouderos Y;Martel-Pelletier J;Reginster JY
骨关节炎（OA），一种影响不同患者表型的疾病，似乎是个性化医疗保健的最佳候选者。欧洲骨质疏松和骨关节炎临床和经济方面学会（ESCEO）工作组讨论的目的是探讨不同来源的标志物在定义OA患者不同表型方面的价值。ESCEO组织了一系列会议，根据最近的数据和专家意见，探讨确定哪些患者将从OA治疗中获益最多的可能性。在第一次会议上，根据受影响关节的数量、生物力学因素和软骨下骨病变的存在来确定患者的表型。在第二次会议上，工作组探讨了OA中涉及的其他标记，本文对此进行了总结。患者的概况可以根据他们的疼痛程度、功能限制和存在共存的慢性病（包括虚弱状态）来定义。相当多的数据表明，磁共振成像也可以帮助描述OA患者的不同表型。在已确定的多种生化生物标志物中，没有一种得到充分验证和认可，以确定应该治疗的患者。人们也作出了相当大的努力来确定OA所涉及的遗传和表观遗传因素，但结果仍然有限。许多潜在的生物标记物可以用作潜在的分层物，但需要更多的研究来表征和鉴定现有的生物标记物，并确定新的候选物。
Osteoarthritis (OA), a disease affecting different patient phenotypes, appears as an optimal candidate for personalized healthcare. The aim of the discussions of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) working group was to explore the value of markers of different sources in defining different phenotypes of patients with OA. The ESCEO organized a series of meetings to explore the possibility of identifying patients who would most benefit from treatment for OA, on the basis of recent data and expert opinion. In the first meeting, patient phenotypes were identified according to the number of affected joints, biomechanical factors, and the presence of lesions in the subchondral bone. In the second meeting, summarized in the present article, the working group explored other markers involved in OA. Profiles of patients may be defined according to their level of pain, functional limitation, and presence of coexistent chronic conditions including frailty status. A considerable amount of data suggests that magnetic resonance imaging may also assist in delineating different phenotypes of patients with OA. Among multiple biochemical biomarkers identified, none is sufficiently validated and recognized to identify patients who should be treated. Considerable efforts are also being made to identify genetic and epigenetic factors involved in OA, but results are still limited. The many potential biomarkers that could be used as potential stratifiers are promising, but more research is needed to characterize and qualify the existing biomarkers and to identify new candidates.