We derive new estimators of an optimal joint testing and treatment regime under the no direct effect (NDE) assumption that a given laboratory, diagnostic, or screening test has no effect on a patient's clinical outcomes except through the effect of the test results on the choice of treatment. We model the optimal joint strategy using an optimal regime structural nested mean model (opt-SNMM). The proposed estimators are more efficient than previous estimators of the parameters of an opt-SNMM because they efficiently leverage the `no direct effect (NDE) of testing' assumption. Our methods will be of importance to decision scientists who either perform cost-benefit analyses or are tasked with the estimation of the `value of information' supplied by an expensive diagnostic test (such as an MRI to screen for lung cancer).

中文翻译：

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在无直接影响的假设下有效估计最佳制度*

我们在无直接影响 (NDE) 假设下推导出最佳联合测试和治疗方案的新估计值，即给定的实验室、诊断或筛查测试对患者的临床结果没有影响，除非测试结果对选择产生影响的治疗。我们使用最佳制度结构嵌套平均模型（opt-SNMM）对最佳联合策略进行建模。提议的估计器比 opt-SNMM 参数的先前估计器更有效，因为它们有效地利用了“测试的无直接影响（NDE）”假设。我们的方法对于决策科学家来说非常重要，他们要么执行成本效益分析，要么负责评估昂贵的诊断测试（例如筛查肺癌的 MRI）提供的“信息价值”。