Evaluating the effect of optimized cutoff values in the assessment of prognostic factors
Evaluating the effect of optimized cutoff values in the assessment of prognostic factors
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DOI：
10.1016/0167-9473(95)00016-x
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发表时间：
1996-03-01
影响因子：
1.8
通讯作者：
Schumacher, M
中科院分区：
文献类型：
--
作者：
Lausen, B;Schumacher, M
在临床研究中，预后因素的评估通常基于将患者分为两组：高风险组和低风险组。一种常见的策略是在定义这两组的预后因素中选择一个最佳的临界值。效果是通过组之间的差异来衡量的。我们给出了选定的两样本统计量的正确P值的简单修正公式。此外，我们还讨论了这种优化对截止点的估计量和估计效果的影响。给出了这两个参数的近似置信域。通过蒙特卡罗研究分析了小样本行为。截断值的优化导致高估了预后组之间的差异。文中还给出了对删失数据的扩展讨论。最后，我们将我们的方法应用于肿瘤学的一个例子。
In clinical research the assessment of prognostic factors is often based on the division of the patients into two groups: a high risk and a low risk group. A common strategy is to select an optimal cutoff value in the prognostic factor which defines the two groups. The effect is measured as difference between the groups. We provide simple correction formulae for the correct P-value of the selected two-sample statistic. Moreover, we discuss consequences of that optimization on both the estimator of the cutoff point and the estimated effect. An approximate confidence region for both parameters is given. The small sample behaviour is analysed by means of a Monte-Carlo study. The optimization of the cutoff value results in an overestimation of the difference between the prognostic groups. Extensions of our discussion to censored data are given, too. Finally, we apply our approach to an example from oncology.