Hunter David J, Lavalley Michael, Li Jiang, Bauer Doug C, Nevitt Michael, DeGroot Jeroen, Poole Robin, Eyre David, Guermazi Ali, Gale Daniel, Totterman Saara, Felson David T
Department of Epidemiology and Biostatistics, Boston University School of Medicine, Albany Street, Boston, Massachusetts 02118, USA.
Arthritis Res Ther. 2008;10(4):R102. doi: 10.1186/ar2494. Epub 2008 Aug 29.
Our objective was to determine whether markers of bone resorption and formation could serve as markers for the presence of bone marrow lesions (BMLs).
We conducted an analysis of data from the Boston Osteoarthritis of the Knee Study (BOKS). Knee magnetic resonance images were scored for BMLs using a semiquantitative grading scheme. In addition, a subset of persons with BMLs underwent quantitative volume measurement of their BML, using a proprietary software method. Within the BOKS population, 80 people with BMLs and 80 without BMLs were selected for the purposes of this case-control study. Bone biomarkers assayed included type I collagen N-telopeptide (NTx) corrected for urinary creatinine, bone-specific alkaline phosphatase, and osteocalcin. The same methods were used and applied to a nested case-control sample from the Framingham study, in which BMD assessments allowed evaluation of this as a covariate. Logistic regression models were fit using BML as the outcome and biomarkers, age, sex, and body mass index as predictors. An receiver operating characteristic curve was generated for each model and the area under the curve assessed.
A total of 151 subjects from BOKS with knee OA were assessed. The mean (standard deviation) age was 67 (9) years and 60% were male. Sixty-nine per cent had maximum BML score above 0, and 48% had maximum BML score above 1. The only model that reached statistical significance used maximum score of BML above 0 as the outcome. Ln-NTx (Ln is the natural log) exhibited a significant association with BMLs, with the odds of a BML being present increasing by 1.4-fold (95% confidence interval = 1.0-fold to 2.0-fold) per 1 standard deviation increase in the LnNTx, and with a small partial R2 of 3.05. We also evaluated 144 participants in the Framingham Osteoarthritis Study, whose mean age was 68 years and body mass index was 29 kg/m2, and of whom 40% were male. Of these participants 55% had a maximum BML score above 0. The relationship between NTx and maximum score of BML above 0 revealed a significant association, with an odds ratio fo 1.7 (95% confidence interval = 1.1 to 2.7) after adjusting for age, sex, and body mass index.
Serum NTx was weakly associated with the presence of BMLs in both study samples. This relationship was not strong and we would not advocate the use of NTx as a marker of the presence of BMLs.
我们的目的是确定骨吸收和形成标志物是否可作为骨髓病变(BMLs)存在的标志物。
我们对波士顿膝骨关节炎研究(BOKS)的数据进行了分析。使用半定量分级方案对膝关节磁共振图像的BMLs进行评分。此外,一部分患有BMLs的人使用专有软件方法对其BML进行了定量体积测量。在BOKS人群中,为该病例对照研究挑选了80名患有BMLs的人和80名没有BMLs的人。检测的骨生物标志物包括校正尿肌酐后的I型胶原N-端肽(NTx)、骨特异性碱性磷酸酶和骨钙素。相同的方法也应用于弗雷明汉姆研究的一个巢式病例对照样本,在该研究中,骨密度评估允许将其作为协变量进行评估。使用BML作为结果,生物标志物、年龄、性别和体重指数作为预测因子拟合逻辑回归模型。为每个模型生成受试者工作特征曲线并评估曲线下面积。
对来自BOKS的151名膝骨关节炎受试者进行了评估。平均(标准差)年龄为67(9)岁,60%为男性。69%的人BML最高评分高于0,48%的人BML最高评分高于1。唯一达到统计学显著性的模型将BML最高评分高于0作为结果。Ln-NTx(Ln为自然对数)与BMLs存在显著关联,每增加1个标准差的LnNTx,出现BML的几率增加1.4倍(95%置信区间 = 1.0倍至2.0倍),且偏R2较小,为3.05。我们还评估了弗雷明汉姆骨关节炎研究中的144名参与者,他们的平均年龄为