Cao Han, Yao Chen, Yuan Ying
Department of Biostatistics, Peking University First Hospital, Beijing, China.
Medical Data Science Center, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing, China.
Med Rev (2021). 2023 Oct 3;3(5):408-424. doi: 10.1515/mr-2023-0026. eCollection 2023 Oct.
Medical device technology develops rapidly, and the life cycle of a medical device is much shorter than drugs. It is necessary to evaluate the safety and effectiveness of a medical device in a timely manner to keep up with technology flux. Bayesian methods provides an efficient approach to addressing this challenge. In this article, we review the characteristics of the Bayesian approach and some Bayesian designs that were commonly used in medical device regulatory setting, including Bayesian adaptive design, Bayesian diagnostic design, Bayesian multiregional design, and Bayesian label expansion study. We illustrate these designs with medical devices approved by the US Food and Drug Administration (FDA). We also review several innovative Bayesian information borrowing methods, and briefly discuss the challenges and future directions of the Bayesian application in medical device trials. Our objective is to promote the use of the Bayesian approach to accelerate the development of innovative medical devices and their accessibility to patients for effective disease diagnoses and treatments.
医疗设备技术发展迅速，医疗设备的生命周期比药物短得多。及时评估医疗设备的安全性和有效性以跟上技术潮流是很有必要的。贝叶斯方法为应对这一挑战提供了一种有效的途径。在本文中，我们回顾了贝叶斯方法的特点以及一些在医疗设备监管环境中常用的贝叶斯设计，包括贝叶斯适应性设计、贝叶斯诊断设计、贝叶斯多区域设计和贝叶斯标签扩展研究。我们用美国食品药品监督管理局（FDA）批准的医疗设备来说明这些设计。我们还回顾了几种创新的贝叶斯信息借用方法，并简要讨论了贝叶斯方法在医疗设备试验中的应用所面临的挑战和未来方向。我们的目标是促进贝叶斯方法的使用，以加速创新医疗设备的开发及其对患者的可及性，从而实现有效的疾病诊断和治疗。
