PERFORMANCE GUARANTEES FOR INDIVIDUALIZED TREATMENT RULES.
PERFORMANCE GUARANTEES FOR INDIVIDUALIZED TREATMENT RULES.
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DOI：
10.1214/10-aos864
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发表时间：
2011-04-01
影响因子：
4.5
通讯作者：
Murphy SA
中科院分区：
文献类型：
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作者：
Qian M;Murphy SA
由于许多疾病对治疗呈现出异质性反应，人们对针对患者进行个体化治疗的兴趣日益增加。个体化治疗规则是一种根据患者特征推荐治疗的决策规则。我们考虑利用临床试验数据构建能使平均反应最高的个体化治疗规则。这是一个困难的计算问题，因为目标函数是一个加权指示函数的期望，该函数在参数上是非凹的。此外，通常有许多预处理变量，它们在构建最优个体化治疗规则时可能有用，也可能无用，但成本和可解释性方面的考虑意味着个体化治疗规则应该只使用少数几个变量。为了应对这些挑战，我们考虑基于L1惩罚最小二乘法进行估计。通过对估计的个体化治疗规则所产生的平均反应与最优个体化治疗规则所产生的平均反应之间差异的有限样本上限，这种方法是合理的。
Because many illnesses show heterogeneous response to treatment, there is increasing interest in individualizing treatment to patients. An individualized treatment rule is a decision rule that recommends treatment according to patient characteristics. We consider the use of clinical trial data in the construction of an individualized treatment rule leading to highest mean response. This is a difficult computational problem because the objective function is the expectation of a weighted indicator function that is non-concave in the parameters. Furthermore there are frequently many pretreatment variables that may or may not be useful in constructing an optimal individualized treatment rule yet cost and interpretability considerations imply that only a few variables should be used by the individualized treatment rule. To address these challenges we consider estimation based on l1 penalized least squares. This approach is justified via a finite sample upper bound on the difference between the mean response due to the estimated individualized treatment rule and the mean response due to the optimal individualized treatment rule.