Institute of Medical Microbiology, University of Zurich, Gloriastrasse 30/32, 8006 Zürich, Switzerland.
J Antimicrob Chemother. 2017 Sep 1;72(9):2553-2561. doi: 10.1093/jac/dkx196.
The procedure for setting clinical breakpoints (CBPs) for antimicrobial susceptibility has been poorly standardized with respect to population data, pharmacokinetic parameters and clinical outcome. Tools to standardize CBP setting could result in improved antibiogram forecast probabilities. We propose a model to estimate probabilities for methodological categorization errors and defined zones of methodological uncertainty (ZMUs), i.e. ranges of zone diameters that cannot reliably be classified. The impact of ZMUs on methodological error rates was used for CBP optimization.
The model distinguishes theoretical true inhibition zone diameters from observed diameters, which suffer from methodological variation. True diameter distributions are described with a normal mixture model. The model was fitted to observed inhibition zone diameters of clinical Escherichia coli strains. Repeated measurements for a quality control strain were used to quantify methodological variation.
For 9 of 13 antibiotics analysed, our model predicted error rates of < 0.1% applying current EUCAST CBPs. Error rates were > 0.1% for ampicillin, cefoxitin, cefuroxime and amoxicillin/clavulanic acid. Increasing the susceptible CBP (cefoxitin) and introducing ZMUs (ampicillin, cefuroxime, amoxicillin/clavulanic acid) decreased error rates to < 0.1%. ZMUs contained low numbers of isolates for ampicillin and cefuroxime (3% and 6%), whereas the ZMU for amoxicillin/clavulanic acid contained 41% of all isolates and was considered not practical.
We demonstrate that CBPs can be improved and standardized by minimizing methodological categorization error rates. ZMUs may be introduced if an intermediate zone is not appropriate for pharmacokinetic/pharmacodynamic or drug dosing reasons. Optimized CBPs will provide a standardized antibiotic susceptibility testing interpretation at a defined level of probability.
抗菌药物药敏试验临床折点（CBPs）的设定程序在人群数据、药代动力学参数和临床结局方面尚未得到很好的标准化。用于标准化 CBP 设置的工具可能会提高药敏试验预测概率。我们提出了一种模型，用于估计方法分类错误和定义方法不确定性区（ZMUs）的概率，即无法可靠分类的抑菌环直径范围。ZMUs 对方法错误率的影响用于 CBP 优化。
该模型区分了理论上的真实抑菌环直径与受到方法学变异影响的观察直径。真实直径分布采用正态混合模型描述。该模型适用于临床大肠埃希菌菌株的观察抑菌环直径。使用质控菌株的重复测量来量化方法学变异。
对于分析的 13 种抗生素中的 9 种，我们的模型预测应用现行 EUCAST CBPs 时，错误率<0.1%。对于氨苄西林、头孢西丁、头孢呋辛和阿莫西林/克拉维酸，错误率>0.1%。增加敏感 CBP（头孢西丁）并引入 ZMUs（氨苄西林、头孢呋辛、阿莫西林/克拉维酸）可将错误率降低至<0.1%。对于氨苄西林和头孢呋辛，ZMUs 包含的分离株数量较少（分别为 3%和 6%），而阿莫西林/克拉维酸的 ZMU 包含所有分离株的 41%，被认为不切实际。
我们证明，通过最小化方法分类错误率，可以改进和标准化 CBPs。如果中间范围由于药代动力学/药效学或药物剂量原因不合适，则可以引入 ZMUs。优化的 CBPs 将在定义的概率水平上提供标准化的抗生素药敏试验解释。
