Validation of prognostic indices using the frailty model
Validation of prognostic indices using the frailty model
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DOI：
10.1007/s10985-008-9092-2
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发表时间：
2009-03-01
影响因子：
1.3
通讯作者：
Sylvester, R.
中科院分区：
文献类型：
--
作者：
Legrand, C.;Duchateau, L.;Sylvester, R.
提出一个新的预后指数时的一个主要问题是它的日常临床实践的普适性。因此，需要进行验证。大多数验证技术评估在新的患者样本中对患者进行分类时通过预后指数获得的“平均”结果是否与在构建集中获得的结果相似。我们介绍了一个新的重要方面的普适性的预后指数：异质性的预后指数风险组的风险比在不同的中心。如果中心之间存在实质性差异，则预后指数在某些中心可能没有区分能力。为了模拟这种异质性，我们使用了一个脆弱模型，包括一个随机的中心效应和一个随机的预后指数中心的相互作用。统计推断基于贝叶斯方法，使用随机效应方差的边际后验分布的拉普拉斯近似。我们研究了不同的方法来总结从这种边缘后验分布中获得的信息。我们的方法被应用到一个真实的膀胱癌数据库，我们展示了如何调查和解释异质性的预后指标的影响中心。
A major issue when proposing a new prognostic index is its generalisibility to daily clinical practice. Validation is therefore required. Most validation techniques assess whether "on average" the results obtained by the prognostic index in classifying patients in a new sample of patients are similar to the results obtained in the construction set. We introduce a new important aspect of the generalisibility of a prognostic index: the heterogeneity of the prognostic index risk group hazard ratios over different centers. If substantial variability between centers exists, the prognostic index may have no discriminatory capability in some of the centers. To model such heterogeneity, we use a frailty model including a random center effect and a random prognostic index by center interaction. Statistical inference is based on a Bayesian approach using a Laplacian approximation for the marginal posterior distribution of the variances of the random effects. We investigate different ways to summarize the information available from this marginal posterior distribution. Our approach is applied to a real bladder cancer database for which we demonstrate how to investigate and interpret heterogeneity in prognostic index effect over centers.