在临床试验招聘中提高选址策略,使用现实世界的数据建模
Lars Hulstaert1, Isabell Twick1, Khaled Sarsour2
1R&D Data Science & Digital Health, Janssen-Cilag GmbH, Neuss, North Rhine-Westphalia, Germany.
PloS one
|March 11, 2024
概括
机器学习准确地预测了临床试验地点选择的患者入学情况. 这种方法改进了传统方法,提高了识别高招聘研究站点的效率,以更快地完成试验.
科学领域:
- 临床试验操作临床试验操作
- 机器学习在医疗保健中的应用
- 制药研究 制药研究
背景情况:
- 临床试验招生延迟显著破坏研究时间表.
- 有效的地点选择对于实现患者招募目标至关重要.
- 可以改进目前识别高招聘网站的方法.
研究的目的:
- 开发和评估一种机器学习 (ML) 方法,根据预测的患者入学率来对临床研究站点进行排名.
- 将ML模型的性能与传统行业基线进行比较.
- 确定影响现场患者招募的关键因素.
主要方法:
- 使用历史招聘和现实世界的数据开发了一种机器学习方法.
- 基于已发表的招聘假设的共变量被定义和分析.
- 线性和非线性ML模型与行业基线进行了比较,用于两个症状:炎症性肠病和多发性髓瘤.
主要成果:
- 非线性机器学习模型的表现显著超过了基线方法和线性模型在测试组上的表现.
- 该研究通过检查共变量和患者招募之间的关系来验证招募假设.
- 开发的ML方法表明,与常见的行业基线相比,站点排名有所改善.
结论:
- 机器学习,特别是非线性模型,为预测患者招生和对临床试验地点进行排名提供了一种卓越的方法.
- 结合现场层面的招聘和现实世界的数据,提高了选址的准确性.
- 这种ML方法有可能优化临床试验规划并加快招聘时间表.
相关概念视频
Clinical Trials
6.7K
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...
6.7K
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
126
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,...
126


