Robust classification of bacterial and viral infections via integrated host gene expression diagnostics.
Robust classification of bacterial and viral infections via integrated host gene expression diagnostics.
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DOI：
10.1126/scitranslmed.aaf7165
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发表时间：
2016-07-06
影响因子：
17.1
通讯作者：
Khatri P
中科院分区：
文献类型：
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作者：
Sweeney TE;Wong HR;Khatri P
改善急性感染的诊断可以通过增加细菌感染患者的早期抗生素和减少无细菌感染患者的不必要抗生素来降低发病率和死亡率。几个小组已经使用基因表达微阵列来构建急性感染的分类器，但这些都受到了基因集大小，过拟合模型使用或缺乏独立验证的阻碍。我们使用多队列分析来推导出一组7个基因，用于对细菌和病毒感染进行强有力的区分，然后在30个独立队列中进行验证。接下来，我们使用我们先前发表的11基因脓毒症MetaScore以及新的细菌/病毒分类器来构建综合抗生素决策模型。在对来自20个队列（不包括婴儿）的1057份样本的汇总分析中，综合抗生素决策模型对细菌感染的敏感性和特异性分别为94.0%和59.8%（阴性似然比，0.10）。在将这些发现用于患者护理之前，需要进行前瞻性临床验证。
Improved diagnostics for acute infections could decrease morbidity and mortality by increasing early antibiotics for patients with bacterial infections and reducing unnecessary antibiotics for patients without bacterial infections. Several groups have used gene expression microarrays to build classifiers for acute infections, but these have been hampered by the size of the gene sets, use of overfit models, or lack of independent validation. We used multicohort analysis to derive a set of seven genes for robust discrimination of bacterial and viral infections, which we then validated in 30 independent cohorts. We next used our previously published 11-gene Sepsis MetaScore together with the new bacterial/viral classifier to build an integrated antibiotics decision model. In a pooled analysis of 1057 samples from 20 cohorts (excluding infants), the integrated antibiotics decision model had a sensitivity and specificity for bacterial infections of 94.0 and 59.8%, respectively (negative likelihood ratio, 0.10). Prospective clinical validation will be needed before these findings are implemented for patient care.