Département de médecine sociale et préventive, Université Laval, Québec, Canada.
Axe santé des Populations et Pratiques Optimales en Santé, Centre de Recherche du CHU de Québec - Université Laval, Québec, Canada.
Stat Med. 2023 Jan 30;42(2):178-192. doi: 10.1002/sim.9608. Epub 2022 Nov 21.
Precision medicine aims to tailor treatment decisions according to patients' characteristics. G-estimation and dynamic weighted ordinary least squares are double robust methods to identify optimal adaptive treatment strategies. It is underappreciated that they require modeling all existing treatment-confounder interactions to be consistent. Identifying optimal partially adaptive treatment strategies that tailor treatments according to only a few covariates, ignoring some interactions, may be preferable in practice. Building on G-estimation and dWOLS, we propose estimators of such partially adaptive strategies and demonstrate their double robustness. We investigate these estimators in a simulation study. Using data maintained by the Centre des Maladies du Sein, we estimate a partially adaptive treatment strategy for tailoring hormonal therapy use in breast cancer patients. R software implementing our estimators is provided.
精准医学旨在根据患者的特征来定制治疗决策。G 估计和动态加权最小二乘法是识别最优自适应治疗策略的双重稳健方法。人们对它们需要对所有现有的治疗混杂因素交互作用进行建模以保持一致性的认识不足。在实践中，根据仅少数协变量来定制治疗而忽略某些交互作用的最优部分自适应治疗策略可能更可取。基于 G 估计和 dWOLS，我们提出了这些部分自适应策略的估计量，并证明了它们的双重稳健性。我们在模拟研究中对这些估计量进行了研究。我们使用乳腺疾病中心维护的数据，估计了一种针对乳腺癌患者激素治疗使用的部分自适应治疗策略。提供了实现我们的估计量的 R 软件。
