Qualitative interaction trees: a tool to identify qualitative treatment-subgroup interactions
Qualitative interaction trees: a tool to identify qualitative treatment-subgroup interactions
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DOI：
10.1002/sim.5933
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发表时间：
2014-01-30
影响因子：
2
通讯作者：
Van Mechelen, Iven
中科院分区：
文献类型：
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作者：
Dusseldorp, Elise;Van Mechelen, Iven
当有两种替代治疗（A 和 B）可用时，某些亚组患者使用治疗 A 可能会比使用 B 表现出更好的结果，而对于另一个亚组，情况可能相反。如果是这种情况，则存在定性（即无序）治疗-亚组相互作用。这种相互作用意味着某些亚组患者应该受到不同的治疗，因此与个性化医疗最相关。如果来自随机临床试验的数据具有许多患者特征，可能以复杂的方式与治疗相互作用，则尚无合适的统计方法来检测定性治疗与亚组相互作用。作为一种出路，在本文中，我们为此提出了一种新方法，称为定量交互树（QUINT）。 QUINT 产生一棵二叉树，根据患者特征将患者细分为终端节点；这些节点进一步分配给三个类别之一：第一个类别，A 优于 B；第二个类别，B 优于 A；可选的第三个类别，治疗类型没有区别。 QUINT 对模拟数据的结果在优化和恢复方面显示出令人满意的性能。实际数据的应用结果表明，与其他方法相比，QUINT 提供了数据中存在的定性相互作用的更明显的图像。版权所有 (c) 2013 John Wiley & Sons, Ltd.
When two alternative treatments (A and B) are available, some subgroup of patients may display a better outcome with treatment A than with B, whereas for another subgroup, the reverse may be true. If this is the case, a qualitative (i.e., disordinal) treatment-subgroup interaction is present. Such interactions imply that some subgroups of patients should be treated differently and are therefore most relevant for personalized medicine. In case of data from randomized clinical trials with many patient characteristics that could interact with treatment in a complex way, a suitable statistical approach to detect qualitative treatment-subgroup interactions is not yet available. As a way out, in the present paper, we propose a new method for this purpose, called QUalitative INteraction Trees (QUINT). QUINT results in a binary tree that subdivides the patients into terminal nodes on the basis of patient characteristics; these nodes are further assigned to one of three classes: a first for which A is better than B, a second for which B is better than A, and an optional third for which type of treatment makes no difference. Results of QUINT on simulated data showed satisfactory performance, with regard to optimization and recovery. Results of an application to real data suggested that, compared with other approaches, QUINT provided a more pronounced picture of the qualitative interactions that are present in the data. Copyright (c) 2013 John Wiley & Sons, Ltd.