Servicio de Micologia, Centro Nacional de Microbiologia, Instituto de Salud Carlos III, Majadahonda, Madrid.
Antimicrob Agents Chemother. 2010 Apr;54(4):1541-6. doi: 10.1128/AAC.01688-09. Epub 2010 Feb 1.
The EUCAST and the CLSI have established different breakpoints for fluconazole and Candida spp. However, the reference methodologies employed to obtain the MICs provide similar results. The aim of this work was to apply supervised classification algorithms to analyze the clinical data used by the CLSI to establish fluconazole breakpoints for Candida infections and to compare these data with the results obtained with the data set used to set up EUCAST fluconazole breakpoints, where the MIC for detecting failures was >4 mg/liter, with a sensitivity of 87%, a false-positive rate of 8%, and an area under the receiver operating characteristic (ROC) curve of 0.89. Five supervised classifiers (J48 and CART decision trees, the OneR decision rule, the naïve Bayes classifier, and simple logistic regression) were used to analyze the original cohort of patients (Rex's data set), which was used to establish CLSI breakpoints, and a later cohort of candidemia (Clancy's data set), with which CLSI breakpoints were validated. The target variable was the outcome of the infections, and the predictor variable was the MIC or dose/MIC ratio. For Rex's data set, the MIC detecting failures was >8 mg/liter, and for Clancy's data set, the MIC detecting failures was >4 mg/liter, in close agreement with the EUCAST breakpoint (MIC > 4 mg/liter). The sensitivities, false-positive rates, and areas under the ROC curve obtained by means of CART, the algorithm with the best statistical results, were 52%, 18%, and 0.7, respectively, for Rex's data set and 65%, 6%, and 0.72, respectively, for Clancy's data set. In addition, the correlation between outcome and dose/MIC ratio was analyzed for Clancy's data set, where a dose/MIC ratio of >75 was associated with successes, with a sensitivity of 93%, a false-positive rate of 29%, and an area under the ROC curve of 0.83. This dose/MIC ratio of >75 was identical to that found for the cohorts used by EUCAST to establish their breakpoints (a dose/MIC ratio of >75, with a sensitivity of 91%, a false-positive rate of 10%, and an area under the ROC curve of 0.90).
EUCAST 和 CLSI 为氟康唑和念珠菌属建立了不同的折点。然而，用于获得 MIC 的参考方法提供了相似的结果。本研究的目的是应用监督分类算法分析 CLSI 为念珠菌感染设定氟康唑折点所使用的临床数据，并将这些数据与用于建立 EUCAST 氟康唑折点的数据集中获得的结果进行比较，该数据集的 MIC 用于检测失败的标准为>4 毫克/升，灵敏度为 87%，假阳性率为 8%，ROC 曲线下面积为 0.89。使用五种监督分类器（J48 和 CART 决策树、OneR 决策规则、朴素贝叶斯分类器和简单逻辑回归）分析了用于建立 CLSI 折点的原始患者队列（Rex 数据集）和后来的念珠菌血症队列（Clancy 数据集），CLSI 折点在该队列中得到了验证。目标变量是感染的结果，预测变量是 MIC 或剂量/MIC 比值。对于 Rex 数据集，检测失败的 MIC 为>8 毫克/升，对于 Clancy 数据集，检测失败的 MIC 为>4 毫克/升，与 EUCAST 折点（MIC>4 毫克/升）非常吻合。通过 CART（具有最佳统计结果的算法）获得的 Rex 数据集的灵敏度、假阳性率和 ROC 曲线下面积分别为 52%、18%和 0.7，Clancy 数据集分别为 65%、6%和 0.72。此外，还分析了 Clancy 数据集的结果与剂量/MIC 比值之间的相关性，其中剂量/MIC 比值>75 与成功相关，灵敏度为 93%，假阳性率为 29%，ROC 曲线下面积为 0.83。这个剂量/MIC 比值>75 与 EUCAST 用于建立其折点的队列相同（剂量/MIC 比值>75，灵敏度为 91%，假阳性率为 10%，ROC 曲线下面积为 0.90）。
