我们盘算了分歧骨代谢生物标志物的生物变异(BV)年夜于,描述良好的受试者队列。BV对于计算参考变化值(或最不显著的变化)是重要的,这允许评估在患者中的两个连续测量之间观察到的差异是否是生物学显著的。
背景:受试者内(CVI)和受试者间(CVG)生物变异(BV)估计对于确定分析性能规范(APS)和参考变化值(RCV)至关重要。先前发表的骨代谢生物标志物的BV估计通常不符合BV研究的最新质量标准。我们计算了不同骨代谢标志物的BV和RCV,即I型胶原蛋白的β-异构化C末端端肽(β-CTX),I型胶原蛋白的N端前肽(PINP),骨钙蛋白(OC),完整成纤维细胞生长因子23(iFGF-23),和未羧化-未磷酸化的基质-Gla蛋白(uCuP-MGP),使用来自欧洲生物学变异研究(EuBIVAS)的样品。
方法:在EuBIVAS中,从六个欧洲实验室招募了91名受试者。每周获得空腹血样,连续10周。样品在IDSiSYS或DiaSorin联络仪器上一式两份运行。在使用CV-ANOVA获得BV估计值之前,对结果进行离群值和方差齐性分析。
结果:我们发现性别对CVI估计没有影响。获得了以下具有95%置信区间(95%CI)的CVI估计值:β-CTX15.1%(14.4-16.0%),PINP8.8%(8.4-9.3%),OC8.9%(8.5-9.4%),iFGF2313.9%(13.2-14.7%),和uCuP-MGP6.9%(6.1-7.3%)。
结论:EuBIVAS提供了骨标志物的最新BV估计值,包括之前尚未发布的iFGF23,促进改善接受代谢性骨病治疗的患者的随访。
We have calculated the biological variation (BV) of different bone metabolism biomarkers on a large, well-described cohort of subjects. BV is important to calculate reference change value (or least significant change) which allows evaluating if the difference observed between two consecutive measurements in a patient is biologically significant or not.
BACKGROUND: Within-subject (CVI) and between-subject (CVG) biological variation (BV) estimates are essential in determining both analytical performance specifications (APS) and reference change values (RCV). Previously published estimates of BV for bone metabolism biomarkers are generally not compliant with the most up-to-date quality criteria for BV studies. We calculated the BV and RCV for different bone metabolism markers, namely β-isomerized C-terminal telopeptide of type I collagen (β-CTX), N-terminal propeptide of type I collagen (PINP), osteocalcin (OC), intact fibroblast growth factor 23 (iFGF-23), and uncarboxylated-unphosphorylated Matrix-Gla Protein (uCuP-
MGP) using samples from the European Biological Variation
Study (EuBIVAS).
METHODS: In the EuBIVAS, 91 subjects were recruited from six European laboratories. Fasting blood samples were obtained weekly for ten consecutive weeks. The samples were run in duplicate on IDS iSYS or DiaSorin Liaison instruments. The results were subjected to outlier and variance homogeneity analysis before CV-ANOVA was used to obtain the BV estimates.
RESULTS: We found no effect of gender upon the CVI estimates. The following CVI estimates with 95% confidence intervals (95% CI) were obtained: β-CTX 15.1% (14.4-16.0%), PINP 8.8% (8.4-9.3%), OC 8.9% (8.5-9.4%), iFGF23 13.9% (13.2-14.7%), and uCuP-
MGP 6.9% (6.1-7.3%).
CONCLUSIONS: The EuBIVAS has provided updated BV estimates for bone markers, including iFGF23, which have not been previously published, facilitating the improved follow-up of patients being treated for metabolic bone disease.