Ep 131 [20 March 2024]: Conversation with Sudhir Venkatesan PhD MPH, Director, Medical & Payer Evidence Statistics at AstraZeneca – We discussed correcting underpowered RWD studies due to information bias. Sample size and power calculations are often applied to real-world data (RWD) in the same manner as RCTs, but without the operational control as present in RCTs, the results are subject to greater information bias. Some sources of bias may have little impact on the effect estimate, but they will result in greater uncertainty and potentially in failure to reach desired power if not accounted for while planning. Quantitative Bias Analysis (QBA) provides a useful framework to incorporate estimated bias into sample size calculations for RWD studies. You can review Sudhir's ICPE abstract #153: https://onlinelibrary.wiley.com/doi/10.1002/pds.5687 Disclaimer: The views expressed in this podcast are the guest's and host's alone, and do not reflect the official position of any organization or entity with whom they are, or have been, professionally affiliated.