Robins James, Orellana Liliana, Rotnitzky Andrea
Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA.
Stat Med. 2008 Oct 15;27(23):4678-721. doi: 10.1002/sim.3301.
We review recent developments in the estimation of an optimal treatment strategy or regime from longitudinal data collected in an observational study. We also propose novel methods for using the data obtained from an observational database in one health-care system to determine the optimal treatment regime for biologically similar subjects in a second health-care system when, for cultural, logistical, or financial reasons, the two health-care systems differ (and will continue to differ) in the frequency of, and reasons for, both laboratory tests and physician visits. Finally, we propose a novel method for estimating the optimal timing of expensive and/or painful diagnostic or prognostic tests. Diagnostic or prognostic tests are only useful in so far as they help a physician to determine the optimal dosing strategy, by providing information on both the current health state and the prognosis of a patient because, in contrast to drug therapies, these tests have no direct causal effect on disease progression. Our new method explicitly incorporates this no direct effect restriction.
我们回顾了从观察性研究中收集的纵向数据估计最优治疗策略或方案的最新进展。我们还提出了新方法,用于利用在一个医疗保健系统的观察性数据库中获得的数据,来确定在第二个医疗保健系统中生物学上相似的受试者的最优治疗方案,当由于文化、后勤或财务原因,这两个医疗保健系统在实验室检查频率和原因以及医生问诊频率和原因方面存在差异(并且将继续存在差异)时。最后,我们提出了一种估计昂贵和/或痛苦的诊断或预后测试的最优时间的新方法。诊断或预后测试只有在通过提供有关患者当前健康状况和预后的信息来帮助医生确定最优给药策略的情况下才有用,因为与药物治疗不同,这些测试对疾病进展没有直接因果效应。我们的新方法明确纳入了这种无直接效应限制。