Leveraging External Data to Augment the Control Arm in Randomized Clinical Trials

• Activity Number: 12 - Opportunities and Challenges in the Use of External Control Arms in Drug Development
• Type: Invited
• Date/Time: Sunday, August 7, 2022 : 2:00 PM to 3:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Ram Tiwari*
• Companies: Bristol Myers Squibb
• Keywords: Composite Likelihood ; Propensity Score; Rea-world Data ; Real-world Evidence

Abstract

Incorporating external data into clinical trials has mainly been through using various matching methods for baseline characteristics to establish an external control arm or to augment a single-arm study or the control arm of a randomized controlled trial (RCT). In this talk, a propensity score-integrated composite likelihood (PSCL) approach for augmenting the control arm of an RCT is proposed. The PSCL approach first estimates the propensity score for every patient as the probability of the patient being in the the RCT rather than the RWD, and then stratifies all patients into strata based on the estimated propensity scores. Within each stratum, a composite likelihood function is specified and utilized to down-weight the information contributed by the RWD source. The stratum-specific parameter estimates are obtained by maximizing the composite likelihood function. These stratum-specific estimates are then combined to obtain an overall population-level estimate of the parameter of interest. The implementation of PSCL approach is illustrated using a hypothetical two-arm RCT and a hypothetical RWD source.