在统一的AUD临床试验数据集中的治疗轨迹的经验推导和预测
Robert J Kohler1, Yasmin Zakiniaeiz1, Terril L Verplaetse1
1Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Addiction biology
|July 23, 2025
概括
机器学习准确地预测酒精使用障碍 (AUD) 治疗反应表型. 识别轻度和重度AUD集群揭示了不同的治疗轨迹和性别特定的消费模式.
科学领域:
- 计算精神病学是一种计算精神病学.
- 准确医学在成治疗中的应用.
- 酒精使用障碍 (AUD) 研究研究
背景情况:
- 预测患者对酒精使用障碍 (AUD) 治疗的反应在临床环境中具有挑战性.
- 机器学习 (ML) 为个性化医疗提供了潜力,但其在AUD治疗中的临床实用性尚未得到充分研究.
- 现有的AUD治疗方法缺乏个性化反应预测.
研究的目的:
- 开发和验证一种ML模型,用于预测AUD治疗反应表型.
- 根据治疗结束时的饮酒模式来描述不同的患者群.
- 探索ML在指导AUD治疗决策中的临床实用性.
主要方法:
- 利用了由NIAAA赞助的五项随机临床试验 (四项第二阶段,一项第三阶段) 的统一数据.
- 开发了一个基于树的ML分类器,使用人口统计和基线临床/生物评估.
- 根据治疗结束时的饮酒率,将患者分为轻度,中度和重度饮酒组.
主要成果:
- 在包括基线饮酒时,ML模型在预测治疗响应表型方面达到71%的准确性.
- 确定了三个不同的群体 (轻度,中度,严重),显示不同的治疗轨迹 (减少与升级).
- 在治疗阶段观察到酒精消费模式的性别特异性差异,尽管在治疗结束时没有.
结论:
- 治疗结束时的酒精消费模式可以定义具有临床意义的AUD表型.
- 机器学习模型可以有效地预测这些表型,强调它们在AUD的精准医学中的实用性.
- 研究结果支持使用计算方法,在各种临床试验数据中推导出强大的AUD表型.
更多相关视频
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
10.8K
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.2K
相关概念视频
01:52Regression Toward the Mean
6.5K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.5K
01:16Clinical Trials
8.5K
Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
There are four phases in a clinical trial. A phase one...
8.5K
01:12Analysis of Population Pharmacokinetic Data
389
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
389
01:11Clinical Trials: Overview
3.4K
Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
3.4K
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
177
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
177
01:21Cancer Survival Analysis
456
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
456