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Joint Statistical Meetings (JSM) Conference: August 3–8, 2024
Randomized controlled trials augmented by external controls involve two distinct sampling processes. First, the clinical trial or intervention arm is sampled from a population defined by the clinical and operational characteristics of the study design, such as the enrollment period, choice of enrolling sites, site enrollment rate, trial inclusion criteria, and patient consent. Second, an external control data set arises from a distinct sampling process. When samples from these two populations are combined for analysis, the covariate distributions are mixed. The mixing proportion may be proportional to the contributing sample sizes or dependent on the choice of balancing weights, thus giving rise to different target populations. We define relevant estimands for studies that augment clinical trials with real-world data using balancing weights. We highlight the advantages and disadvantages of different estimands with respect to interpretation. Finally, we compare alternative estimators through simulation and in application to an augmented clinical trial of idiopathic pulmonary fibrosis.
This session also includes the following presentations:
- Biomarker-Guided Multi-Stage Trials with Threshold Detection and Patient Enrichment with Information Borrowing from Historical Controls | Xiaofei Wang, Duke University Medical Center
- Combining external aggregate information with primary data to improve statistical efficiency | Yu Shen, UT M.D. Anderson Cancer Center
- Considerations for Master Protocols Using External Controls | Jie Chen, Overland Pharma