Principled estimation and evaluation of treatment effect heterogeneity: A case study application to dabigatran for patients with atrial fibrillation.
Principled estimation and evaluation of treatment effect heterogeneity: A case study application to dabigatran for patients with atrial fibrillation.
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DOI：
10.1016/j.jbi.2023.104420
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发表时间：
2023-07
影响因子：
4.5
通讯作者：
Shah, Nigam
中科院分区：
文献类型：
--
作者：
Xu, Yizhe;Bechler, Katelyn;Callahan, Alison;Shah, Nigam
在长期抗凝治疗(RE-LY)试验的端到端案例研究中应用最新的异质治疗效果(HTE)评估指南，并深入总结应用最先进的元学习者和新的评估指标的主要收获，以告知它们在生物医学研究中的个性化护理应用。根据RE-LY数据的特点，我们选择了四个元学习者(S-套索学习者，X-学习者套索学习者，R-学习者随机生存森林和套索学习者，以及因果生存森林)来估计达比加兰的HTEs。对于(1)中风或全身栓塞和(2)大出血的结果，我们比较了达比加兰150毫克、达比加兰110毫克和华法林。我们通过全局归零分析评估了元学习者对治疗异质性的高估，并使用两个新的衡量标准：等级加权平均治疗效果(率)和估计的治疗异质性校准误差来评估他们的辨别和校准能力。最后，我们使用部分依赖图可视化了估计的治疗效果和基线协变量之间的关系。比率指标表明，要么是应用的元学习者在评估HTE方面表现不佳，要么是在任何治疗比较中，中风/SE或大出血结果都不存在治疗异质性。偏相关图显示，几个协变量与多个元学习者估计的治疗效果有一致的关系。应用的元学习者在结果和治疗比较中表现出不同的表现，X学习者和R学习者产生的校准误差比其他人小。估计是困难的，必须有一个原则性的估计和评估过程，以提供可靠的证据，防止错误的发现。我们已经演示了如何根据特定的数据属性选择合适的元学习者，使用现成的实现工具SurvLearning应用它们，并使用最近定义的正式度量来评估他们的表现。我们建议，应该根据应用的元习者的共同趋势来得出临床意义。
To apply the latest guidance for estimating and evaluating heterogeneous treatment effects (HTEs) in an end-to-end case study of the Long-term Anticoagulation Therapy (RE-LY) trial, and summarize the main takeaways from applying state-of-the-art metalearners and novel evaluation metrics in-depth to inform their applications to personalized care in biomedical research. Based on the characteristics of the RE-LY data, we selected four metalearners (S-learner with Lasso, X-learner with Lasso, R-learner with random survival forest and Lasso, and causal survival forest) to estimate the HTEs of dabigatran. For the outcomes of (1) stroke or systemic embolism and (2) major bleeding, we compared dabigatran 150 mg, dabigatran 110 mg, and warfarin. We assessed the overestimation of treatment heterogeneity by the metalearners via a global null analysis and their discrimination and calibration ability using two novel metrics: rank-weighted average treatment effects (RATE) and estimated calibration error for treatment heterogeneity. Finally, we visualized the relationships between estimated treatment effects and baseline covariates using partial dependence plots. The RATE metric suggested that either the applied metalearners had poor performance of estimating HTEs or there was no treatment heterogeneity for either the stroke/SE or major bleeding outcome of any treatment comparison. Partial dependence plots revealed that several covariates had consistent relationships with the treatment effects estimated by multiple metalearners. The applied metalearners showed differential performance across outcomes and treatment comparisons, and the X- and R-learners yielded smaller calibration errors than the others. HTE estimation is difficult, and a principled estimation and evaluation process is necessary to provide reliable evidence and prevent false discoveries. We have demonstrated how to choose appropriate metalearners based on specific data properties, applied them using the off-the-shelf implementation tool survlearners, and evaluated their performance using recently defined formal metrics. We suggest that clinical implications should be drawn based on the common trends across the applied metalearners.
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影响因子：
168.9
作者：
Ruff, Christian T.;Giugliano, Robert P.;Antman, Elliott M.
通讯作者：
Antman, Elliott M.
DOI：
10.1080/01621459.2014.951443
发表时间：
2014-12-01
影响因子：
3.7
作者：
Tian, Lu;Alizadeh, Ash A.;Tibshirani, Robert
通讯作者：
Tibshirani, Robert
DOI：
10.1073/pnas.1510489113
发表时间：
2016-07-05
影响因子：
11.1
作者：
Athey, Susan;Imbens, Guido
通讯作者：
Imbens, Guido
影响因子：
6.6
作者：
Kravitz, RL;Duan, NH;Braslow, J
通讯作者：
Braslow, J
DOI：
10.1073/pnas.1804597116
发表时间：
2019-03-05
影响因子：
11.1
作者：
Kunzel, Soren R.;Sekhon, Jasjeet S.;Yu, Bin
通讯作者：
Yu, Bin