Statistical methods for the assessment of prognostic biomarkers(part II): calibration and re-classification
Statistical methods for the assessment of prognostic biomarkers(part II): calibration and re-classification
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DOI：
10.1093/ndt/gfq046
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发表时间：
2010-05-01
影响因子：
6.1
通讯作者：
Zoccali, Carmine
中科院分区：
文献类型：
--
作者：
Tripepi, Giovanni;Jager, Kitty J.;Zoccali, Carmine
校正是指预测模型在整个预测估计范围(例如，30%的死亡概率、40%的心肌梗死概率等)中正确估计给定事件的概率的能力。校准和判别之间的关键区别在于，后者反映了给定的预后生物标记物区分状态(死亡/存活、事件/非事件)的能力，而校准衡量的是预测模型的预后估计与实际结果概率(即，观察到的事件的比例)的匹配程度。重新分类是预后准确性的另一种衡量标准，它反映了与基于现有预后生物标记物或预测模型的先前分类相比，新的预后生物标记物增加了正确地重新分类为具有或不具有给定事件的个体的比例。
Calibration is the ability of a prognostic model to correctly estimate the probability of a given event across the whole range of prognostic estimates (for example, 30% probability of death, 40% probability of myocardial infarction, etc.). The key difference between calibration and discrimination is that the latter reflects the ability of a given prognostic biomarker to distinguish a status (died/survived, event/non-event), while calibration measures how much the prognostic estimation of a predictive model matches the real outcome probability (that is, the observed proportion of the event). Re-classification is another measure of prognostic accuracy and it reflects how much a new prognostic biomarker increases the proportion of individuals correctly re-classified as having or not having a given event compared to a previous classification based on an existing prognostic biomarker or predictive model.