Olga Marchenko1, Estelle Russek-Cohen2, Mark Levenson2, Richard C Zink3,4, Michelle R Krukas-Hampel1, Qi Jiang5. 1. 1 QuintilesIMS, Durham, NC, USA. 2. 2 FDA CDER, Silver Spring, MD, USA. 3. 3 JMP Life Sciences, SAS Institute, Cary, NC, USA. 4. 4 Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 5. 5 Amgen, Thousand Oaks, CA, USA.
Abstract
BACKGROUND: Although randomized controlled clinical trials provide necessary information and serve as the basis for regulatory decision making, a significant gap exists between the evidence these trials provide and what the biomedical community needs. It is recognized that a wealth of data are routinely collected outside clinical trials. Such real-world data (RWD) are not of comparable quality, it does not have similar immunity from bias and confounding as data collected in randomized clinical trials, but it might offer additional understanding of the benefit-risk, provide new insights to different stakeholders, and aid in regulatory decision making. This can be especially true when rare but serious adverse events are considered because randomized clinical trials are often not large enough and have insufficient duration to address safety concerns fully. Also, the passage of the 21st Century Cures bill passed by Congress in 2016 means that several data sources outside traditional clinical trials will play a greater role in regulatory decision making. This manuscript is third in a series of articles from the American Statistical Association Biopharmaceutical Section Safety Working Group. METHODS: In this manuscript, authors reviewed some RWD sources and shared considerations for statistical strategies and methodologies needed to design and analyze observational safety studies and pragmatic trials. RESULTS: Authors presented case studies and shared recommendations for statistical methods necessary to design and analyze safety trials using RWD. CONCLUSIONS: RWD is an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. However, it is important to determine if such data are fit for purpose.
BACKGROUND: Although randomized controlled clinical trials provide necessary information and serve as the basis for regulatory decision making, a significant gap exists between the evidence these trials provide and what the biomedical community needs. It is recognized that a wealth of data are routinely collected outside clinical trials. Such real-world data (RWD) are not of comparable quality, it does not have similar immunity from bias and confounding as data collected in randomized clinical trials, but it might offer additional understanding of the benefit-risk, provide new insights to different stakeholders, and aid in regulatory decision making. This can be especially true when rare but serious adverse events are considered because randomized clinical trials are often not large enough and have insufficient duration to address safety concerns fully. Also, the passage of the 21st Century Cures bill passed by Congress in 2016 means that several data sources outside traditional clinical trials will play a greater role in regulatory decision making. This manuscript is third in a series of articles from the American Statistical Association Biopharmaceutical Section Safety Working Group. METHODS: In this manuscript, authors reviewed some RWD sources and shared considerations for statistical strategies and methodologies needed to design and analyze observational safety studies and pragmatic trials. RESULTS: Authors presented case studies and shared recommendations for statistical methods necessary to design and analyze safety trials using RWD. CONCLUSIONS: RWD is an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. However, it is important to determine if such data are fit for purpose.