在风险算法中加入单核苷酸多态性是否能改善类风湿性关节炎的心血管疾病风险预测?临床风险评分的内外部验证。

IF 3.7 2区 医学 Q1 RHEUMATOLOGY
Rabia Agca, Calin D. Popa, Martijn W. Heymans, Bart Crusius, Alexandre E. Voskuyl, Michael T. Nurmohamed
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引用次数: 0

摘要

目的:目前的风险算法不能准确预测类风湿性关节炎(RA)患者的心血管疾病(CVD)风险。单核苷酸多态性(SNPs)是一个值得关注的领域,其中有几个单核苷酸多态性与普通人群中的心血管疾病相关。我们研究了这些 SNPs 是否与 RA 患者的心血管疾病相关,以及 SNPs 是否能改善 RA 患者的心血管疾病风险预测。方法:对 353 名 RA 患者的 60 个 SNPs 进行了基因分型,并进行了 Logistic 和 Cox 回归分析,以确定与心血管疾病相关的 SNPs(n=99)。建立了一个包含临床变量的预测模型。增加了 SNPs 以研究其额外的预测价值。两个模型都经过了内部验证。结果:rs3184504、rs4773144、rs12190287 和 rs445925 与新发心血管疾病显著相关。临床预测模型由年龄、性别、体重指数(BMI)、收缩压(SBP)、高密度脂蛋白胆固醇(HDLc)和肌酐组成,曲线下面积(AUC)为 0.74,P=0.03。内部验证的曲线下面积(AUC)为 0.76(P=0.03):多个SNP与RA患者的心血管疾病相关。将 SNPs 加入模型后,风险预测略有改善,但其临床相关性值得商榷。不过,要更准确地确定这些 SNP 对心血管疾病风险预测算法的额外价值,还需要进行更大规模的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Does Adding Single-Nucleotide Polymorphisms to Risk Algorithms Improve Cardiovascular Disease Risk Prediction in Rheumatoid Arthritis? An Internal and External Validation of a Clinical Risk Score

Does Adding Single-Nucleotide Polymorphisms to Risk Algorithms Improve Cardiovascular Disease Risk Prediction in Rheumatoid Arthritis? An Internal and External Validation of a Clinical Risk Score

Objective

Current risk algorithms do not accurately predict cardiovascular disease (CVD) risk in rheumatoid arthritis (RA). An area of interest is that of single-nucleotide polymorphisms (SNPs), of which several have been associated with CVD in the general population. We investigated whether these SNPs are associated with CVD in RA and whether SNPs could improve CVD risk prediction in RA.

Methods

Sixty SNPs were genotyped in 353 patients with RA. Logistic and Cox regression analyses were performed to identify SNPs that were associated with CVD (n = 99). A prediction model with clinical variables was made. SNPs were added to investigate the additional predictive value. Both models were internally validated. External validation was done in a separate cohort (n = 297).

Results

rs3184504, rs4773144, rs12190287, and rs445925 were significantly associated with new CVD. The clinical prediction model consisted of age, sex, body mass index, systolic blood pressure, high-density lipoprotein cholesterol (HDLc), and creatinine, with an area under the curve (AUC) of 0.74 (P = 0.03). Internal validation resulted in an AUC of 0.76 (P < 0.01). A new model was made including SNPs and resulted in a model with rs17011666 and rs801426, age, total cholesterol, and HDLc, which performed slightly better with an AUC of 0.77 (P < 0.01). External validation resulted in a good fit for the clinical model, but a poor fit for the SNP model.

Conclusion

Several SNPs were associated with CVD in RA. Risk prediction slightly improved after adding SNPs to the models, but the clinical relevance is debatable. However, larger studies are needed to determine more accurately the additional value of these SNPs to CVD risk prediction algorithms.

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来源期刊
CiteScore
9.40
自引率
6.40%
发文量
368
审稿时长
3-6 weeks
期刊介绍: Arthritis Care & Research, an official journal of the American College of Rheumatology and the Association of Rheumatology Health Professionals (a division of the College), is a peer-reviewed publication that publishes original research, review articles, and editorials that promote excellence in the clinical practice of rheumatology. Relevant to the care of individuals with rheumatic diseases, major topics are evidence-based practice studies, clinical problems, practice guidelines, educational, social, and public health issues, health economics, health care policy, and future trends in rheumatology practice.
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