Gabriel S E, O'Fallon W M, Achkar A A, Lie J T, Hunder G G
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905.
J Rheumatol. 1995 Jan;22(1):93-6.
To develop a mathematical model which predicts temporal artery biopsy results.
We collected clinical and laboratory data as well as biopsy results among a consecutive cohort of all individuals who underwent temporal artery biopsy at Mayo Medical Center between January 1, 1988 and December 31, 1991. All biopsies were independently reviewed by one pathologist. Logistic regression was used to identify a set of variables which best predicted the biopsy results. This model was then used to identify patients who were highly likely (> or = 95% predictive value) to have either a negative or a positive biopsy. A receiver operating characteristic (ROC) curve was generated using the best fit model.
Of the 525 people in the study, there were 187 men and 338 women. The logistic regression model and the ROC curve generated from this model were of modest value in predicting biopsy results from prebiopsy clinical characteristics. However, this model identified 60 (11%) individuals who had a > or = 95% probability of having a negative biopsy. None of these individuals had any symptoms of claudication, only 5 of 60 (8%) had temporal artery abnormalities on examination, 45 (75%) had synovitis (suggesting an alternate diagnosis), and their median erythrocyte sedimentation rate was only 31 mm/h (Westergren).
In individuals with these findings, we recommend a careful search for other diagnoses before temporal artery biopsy.
建立一个能预测颞动脉活检结果的数学模型。
我们收集了1988年1月1日至1991年12月31日在梅奥医学中心接受颞动脉活检的所有连续队列个体的临床和实验室数据以及活检结果。所有活检均由一名病理学家独立复查。采用逻辑回归来确定一组最能预测活检结果的变量。然后使用该模型来识别活检结果极有可能为阴性或阳性（预测值≥95%）的患者。使用最佳拟合模型生成受试者工作特征（ROC）曲线。
在该研究的525人中，有187名男性和338名女性。由该逻辑回归模型及生成的ROC曲线在根据活检前临床特征预测活检结果方面价值有限。然而，该模型识别出60名（11%）个体，其活检结果为阴性的概率≥95%。这些个体均无间歇性跛行症状，60人中只有5人（8%）在检查时有颞动脉异常，45人（75%）有滑膜炎（提示有其他诊断可能），且他们的红细胞沉降率中位数仅为31mm/h（魏氏法）。
对于有这些表现的个体，我们建议在进行颞动脉活检前仔细寻找其他诊断。
