Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Department of Statistics, University of Washington, Seattle, Washington.
JAMA Psychiatry. 2021 Dec 1;78(12):1384-1390. doi: 10.1001/jamapsychiatry.2021.2500.
Clinical trials have identified numerous prescriptive predictors of mental disorder treatment response, ie, predictors of which treatments are best for which patients. However, none of these prescriptive predictors is strong enough alone to guide precision treatment planning. This has prompted growing interest in developing precision treatment rules (PTRs) that combine information across multiple prescriptive predictors, but this work has been much less successful in psychiatry than some other areas of medicine. Study designs and analysis schemes used in research on PTR development in other areas of medicine are reviewed, key challenges for implementing similar studies of mental disorders are highlighted, and recent methodological advances to address these challenges are described here.
Discovering prescriptive predictors requires large samples. Three approaches have been used in other areas of medicine to do this: conduct very large randomized clinical trials, pool individual-level results across multiple smaller randomized clinical trials, and develop preliminary PTRs in large observational treatment samples that are then tested in smaller randomized clinical trials. The third approach is most feasible for research on mental disorders. This approach requires working with large real-world observational electronic health record databases; carefully selecting samples to emulate trials; extracting information about prescriptive predictors from electronic health records along with other inexpensive data augmentation strategies; estimating preliminary PTRs in the observational data using appropriate methods; implementing pragmatic trials to validate the preliminary PTRs; and iterating between subsequent observational studies and quality improvement pragmatic trials to refine and expand the PTRs. New statistical methods exist to address the methodological challenges of implementing this approach.
Advances in pragmatic precision psychiatry will require moving beyond the current focus on randomized clinical trials and adopting an iterative discovery-confirmation process that integrates observational and experimental studies in real-world clinical populations.
临床试验已经确定了许多精神障碍治疗反应的预测因子，即哪种治疗对哪种患者最有效。然而，这些预测因子都不够强大，无法单独指导精准治疗计划。这促使人们越来越感兴趣地开发精准治疗规则 (PTRs)，这些规则结合了多个预测因子的信息，但在精神病学中，这方面的工作不如其他医学领域成功。本文回顾了其他医学领域中关于 PTR 开发的研究设计和分析方案，强调了实施类似精神障碍研究的关键挑战，并描述了最近解决这些挑战的方法学进展。
发现预测因子需要大样本。在其他医学领域，已经使用了三种方法来实现这一目标：进行非常大型的随机临床试验、在多个小型随机临床试验中汇总个体水平的结果，以及在大型观察性治疗样本中开发初步的 PTRs，然后在小型随机临床试验中进行测试。第三种方法对于精神障碍的研究最为可行。这种方法需要使用大型真实世界的观察性电子健康记录数据库；仔细选择样本来模拟试验；从电子健康记录中提取预测因子信息以及其他廉价的数据增强策略；使用适当的方法在观察数据中估计初步的 PTRs；实施实用临床试验来验证初步的 PTRs；并在随后的观察性研究和质量改进实用临床试验之间迭代，以改进和扩展 PTRs。新的统计方法可用于解决实施这种方法的方法学挑战。
精准精神病学的进步将需要超越当前对随机临床试验的关注，并采用一种迭代的发现-确认过程，将真实世界临床人群中的观察性和实验性研究结合起来。
