Cuppen Bart V J, Welsing Paco M J, Sprengers Jan J, Bijlsma Johannes W J, Marijnissen Anne C A, van Laar Jacob M, Lafeber Floris P J G, Nair Sandhya C
Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands
Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht, The Netherlands.
Rheumatology (Oxford). 2016 May;55(5):826-39. doi: 10.1093/rheumatology/kev421. Epub 2015 Dec 29.
To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers.
A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. The added value was determined by the added value on prior probability for each (bio)marker. Only an increase/decrease in chance of response ⩾15% was considered clinically relevant, whereas in oncology values >25% are common.
Of the 57 eligible studies, 14 (bio)markers were studied in more than one cohort and an overview of the added predictive value of each marker is presented. Of the replicated predictors, none consistently showed an increase/decrease in probability of response ⩾15%. However, positivity of RF and ACPA in case of rituximab and the presence of the TNF-α promoter 308 GG genotype for TNF inhibitor therapy were consistently predictive, yet low in added predictive value. Besides these, 65 (bio)markers studied once showed remarkably high (but not validated) predictive values.
We were unable to address clinically useful baseline (bio)markers for use in individually tailored treatment. Some predictors are consistently predictive, yet low in added predictive value, while several others are promising but await replication. The challenge now is to design studies to validate all explored and promising findings individually and in combination to make these (bio)markers relevant to clinical practice.
回顾关于类风湿关节炎(RA)生物治疗反应预测的研究,并探讨所研究的(生物)标志物的临床实用性。
在PubMed、Embase和Cochrane数据库中检索相关文章。选择呈现预测值或可计算预测值的研究。通过每个(生物)标志物在先验概率上的增加值来确定其附加值。只有反应机会增加/减少≥15%才被认为具有临床相关性,而在肿瘤学中,>25%的值较为常见。
在57项符合条件的研究中,有14种(生物)标志物在多个队列中进行了研究,并给出了每个标志物附加预测价值的概述。在重复研究的预测指标中,没有一个能持续显示反应概率增加/减少≥15%。然而,利妥昔单抗治疗时RF和ACPA的阳性以及TNF抑制剂治疗时TNF-α启动子308 GG基因型的存在具有持续预测性,但附加预测价值较低。除此之外,仅研究过一次的65种(生物)标志物显示出非常高(但未经验证)的预测价值。
我们未能找到可用于个体化治疗的具有临床实用性的基线(生物)标志物。一些预测指标具有持续预测性,但附加预测价值较低,而其他一些指标很有前景,但有待重复验证。目前的挑战是设计研究,分别或联合验证所有已探索和有前景的发现,以使这些(生物)标志物与临床实践相关。