Development of a multi-biomarker disease activity test for rheumatoid arthritis.
Development of a multi-biomarker disease activity test for rheumatoid arthritis.
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DOI：
10.1371/journal.pone.0060635
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Curtis JR
中科院分区：
文献类型：
--
作者：
Centola M;Cavet G;Shen Y;Ramanujan S;Knowlton N;Swan KA;Turner M;Sutton C;Smith DR;Haney DJ;Chernoff D;Hesterberg LK;Carulli JP;Taylor PC;Shadick NA;Weinblatt ME;Curtis JR
疾病活动性测量是类风湿关节炎（RA）管理的关键组成部分。捕获RA的复杂和异质生物学的生物标志物具有补充临床疾病活动评估的潜力。建立类风湿关节炎多生物标志物疾病活动性（MBDA）检测方法。从广泛的文献筛选、生物信息学数据库、mRNA表达和蛋白质微阵列数据中选择候选血清蛋白质生物标志物。确定并优化定量测定用于测量RA患者血清中的候选生物标志物。在一系列研究中，根据其与RA临床疾病活动的相关性（例如疾病活动评分28-C-反应蛋白[DAS 28-CRP]，临床试验中常用的经验证指标）及其对多变量模型的贡献，对具有合格检测的生物标志物进行优先排序。使用优先化的生物标志物来训练算法以测量疾病活动性，通过与DAS的相关性和用于低与中/高疾病活动性分类的接受者工作特征曲线下面积来评估。使用线性模型评估合并症对MBDA评分的影响，并对多重假设检验进行调整。在可行性研究中测试了130种候选生物标志物，并选择了25种用于算法训练。多生物标志物统计模型在估计疾病活动性方面优于单个生物标志物。基于生物标志物的评分与DAS 28-CRP显著相关，并且可以区分具有低与中/高临床疾病活动性的患者。这些评分也能够追踪DAS 28-CRP的变化，并且与超声测量的关节炎症和放射学测量的损伤进展显著相关。最终的MBDA算法使用12种生物标志物来生成1至100之间的MBDA评分。常见合并症对MBDA评分无显著影响。我们遵循一种逐步的方法，以12种生物标志物为基础，开发了一种定量的基于血清的RA疾病活动性测量方法，该方法与临床疾病活动水平一致。
Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.
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影响因子：
16.2
作者：
Kolberg JA;Jørgensen T;Gerwien RW;Hamren S;McKenna MP;Moler E;Rowe MW;Urdea MS;Xu XM;Hansen T;Pedersen O;Borch-Johnsen K
通讯作者：
Borch-Johnsen K
影响因子：
5.5
作者：
Leeb, BF;Andel, I;Rintelen, B
通讯作者：
Rintelen, B
影响因子：
27.4
作者：
Lavie, Frederic;Miceli-Richard, Corinne;Mariette, Xavier
通讯作者：
Mariette, Xavier
影响因子：
27.4
作者：
CHAMBERS, RE;MACFARLANE, DG;DIEPPE, PA
通讯作者：
DIEPPE, PA
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y