Bayesian approach for design and analysis of medical device trials in the era of modern clinical studies

Author:

Cao Han12,Yao Chen134ORCID,Yuan Ying5

Affiliation:

1. Department of Biostatistics , Peking University First Hospital , Beijing , China

2. Medical Data Science Center, Beijing Tsinghua Changgung Hospital , School of Clinical Medicine, Tsinghua University , Beijing , China

3. Peking University Clinical Research Institute , Beijing , China

4. Hainan Institute of Real World Data , Qionghai , Hainan Province , China

5. Department of Biostatistics , The University of Texas MD Anderson Cancer Center , Houston , USA

Abstract

Abstract 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.

Funder

The Real World Study Project of Hainan Baoao Lecheng Pilot Zone

The National Key Research and Development Program of China

Publisher

Walter de Gruyter GmbH

Reference121 articles.

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