Non-Parametric Combined Reference Regions and Prediction of Clinical Risk.
Non-Parametric Combined Reference Regions and Prediction of Clinical Risk.
复制标题
非参数组合参考区域和临床风险预测。
DOI：
10.1093/clinchem/hvz020
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发表时间：
2020
影响因子：
9.3
通讯作者：
Higgins,JohnM
中科院分区：
文献类型：
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作者：
Malka,Roy;Brugnara,Carlo;Cialic,Ron;Higgins,JohnM
背景许多临床决策依赖于通过解释相对于参考区间的测试结果来估计临床结果的患者风险，但是参考区间的标准应用受到两个主要限制，这两个限制降低了临床决策的准确性：（1）相对于单变量参考区间单独评估每个测试结果，忽略多变量关系中丰富的病理生理信息，参考区间旨在反映人群的生物学特征，而不是为了预测结果而校准。方法我们开发了一个联合参考区（CRR），推导出一些对全血细胞计数（CBC）指标的CRR（RBC、MCH、RDW、WBC、PLT），并评估CRR是否可以增强单变量参考区间对一般临床结局的预测，5年死亡率风险（MR）。结果CRR显着改善MR估计为21/21患者子集定义的当前单变量参考区间。CRR在许多情况下识别出MR增加>2倍的个体，并一致提高了所有五对测试的准确性。总体而言，95%的CRR确定个人与一个>7×增加5年MR.ConclusionsThe CRR提高了准确性的预测5年MR相对于目前的单变量参考区间。CRR可推广到更多数量的检测或生物标志物，以及比MR更特异的临床结局，并可提供一种使用现有数据的通用方法，以提高临床决策的准确性和精确度。
BackgroundMany clinical decisions depend on estimating patient risk of clinical outcomes by interpreting test results relative to reference intervals, but standard application of reference intervals suffers from two major limitations that reduce the accuracy of clinical decisions: (1) each test result is assessed separately relative to a univariate reference interval, ignoring the rich pathophysiologic information in multivariate relationships, and (2) reference intervals are intended to reflect a population’s biological characteristics and are not calibrated for outcome prediction.MethodsWe developed a combined reference region (CRR), derived CRRs for some pairs of complete blood count (CBC) indices (RBC, MCH, RDW, WBC, PLT), and assessed whether the CRR could enhance the univariate reference interval’s prediction of a general clinical outcome, 5-year mortality risk (MR).ResultsThe CRR significantly improved MR estimation for 21/21 patient subsets defined by current univariate reference intervals. The CRR identified individuals with >2-fold increase in MR in many cases and uniformly improved the accuracy for all five pairs of tests considered. Overall, the 95% CRR identified individuals with a >7× increase in 5-year MR.ConclusionsThe CRR enhances the accuracy of the prediction of 5-year MR relative to current univariate reference intervals. The CRR generalizes to higher numbers of tests or biomarkers, as well as to clinical outcomes more specific than MR, and may provide a general way to use existing data to enhance the accuracy and precision of clinical decisions.