Rudrapatna Vivek A, Ravindranath Vignesh G, Arneson Douglas V, Mosenia Arman, Butte Atul J, Wang Shan
Division of Gastroenterology, Department of Medicine, University of California, San Francisco, CA, USA.
Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA.
NPJ Digit Med. 2025 May 31;8(1):327. doi: 10.1038/s41746-025-01627-w.
Clinical practice is currently guided by studies that average over patient outcomes. This may not be the best approach, as different patients may have different treatment responses. Here we extend a method for simulating clinical trials to identify optimal treatments for each patient, and we illustrate this approach in the context of Crohn's disease. Using the data from 15 randomized trials (N = 5703), we used statistical hypothesis testing to identify seven subgroups with distinct responses to three different drug classes. The largest subgroup consisted of patients with equivocal responses to all drug classes, whereas the second largest showed superiority with anti-TNFs. We also identified a subgroup of women over 50 with superior responses to anti-IL-12/23s. Interestingly, this group appeared under-represented in the trials (2%) compared to patients at the University of California (25%). Overall, these results underscore the importance of studying personalized medicine, demonstrate the value of clinical trial data, and provide a roadmap for applying this method broadly across diseases. These results also highlight the importance of diverse and representative recruitment into clinical trials.
目前的临床实践是以对患者治疗结果进行平均的研究为指导的。这可能不是最佳方法，因为不同患者可能有不同的治疗反应。在此，我们扩展了一种模拟临床试验的方法，以确定适合每个患者的最佳治疗方法，并在克罗恩病的背景下阐释了这种方法。利用来自15项随机试验（N = 5703）的数据，我们使用统计假设检验来识别对三种不同药物类别有不同反应的七个亚组。最大的亚组由对所有药物类别反应不明确的患者组成，而第二大亚组显示出对抗肿瘤坏死因子（anti-TNFs）药物有优势。我们还识别出一个年龄超过50岁的女性亚组，她们对抗白细胞介素12/23（anti-IL-12/23s）药物有更好的反应。有趣的是，与加利福尼亚大学的患者（25%）相比，这个亚组在试验中的占比似乎较低（2%）。总体而言，这些结果强调了研究个性化医疗的重要性，证明了临床试验数据的价值，并为在多种疾病中广泛应用这种方法提供了路线图。这些结果还突出了临床试验中多样化和具有代表性的招募工作的重要性。
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