The Current Landscape in Biostatistics of Real-World Data and Evidence: Clinical Study Design and Analysis

Abstract

Real-world data (RWD), such as electronic health records, reimbursement requests as adjudicated by health insurance companies, and health survey data as collected by government agencies or other research organizations, are increasingly used in drug development. Regulatory agencies, public-private partnerships, and professional organizations have initiated major programs and released guidance or guidelines to address challenges in the use of real-world evidence (RWE) to inform regulatory decision making. Since statistical research and considerations in the design, analysis, and interpretation of RWE studies is still a nascent area, the ASA Biopharmaceutical Section established a scientific working group to survey the existing practices and identify opportunities in the area. This article reviews the current landscape of using external data such as RWD/RWE to inform clinical study design and analysis. Two companion articles review the landscape of using RWE in medical product label expansion and of causal inference frameworks to generate RWE.

Keywords:

• Causal inference
• External control
• Historical control
• Real-world data
• Real-world evidence