There has been an increasing use of master protocols in oncology clinical
trials because of its efficiency and flexibility to accelerate cancer drug
development. Depending on the study objective and design, a master protocol
trial can be a basket trial, an umbrella trial, a platform trial, or any other
form of trials in which multiple drugs and/or multiple subpopulations are
studied in parallel under a single protocol. External data and evidence (EDE)
can be used in the design and analysis of master protocols such as external
controls for treatment effect estimation, which can further improve efficiency
of the master protocol trial. This paper provides an overview of different
types of external controls and their unique features when used in master
protocols. Some key considerations in master protocols with external controls
are discussed including construction of estimands and assessment of fit-for-use
real-world data. A targeted learning-based causal roadmap is presented which
constitutes three key steps: (1) define a target statistical estimand that
aligns with the causal estimand for the study objective, (2) use an efficient
estimator to estimate the target statistical estimand and its uncertainty, and
(3) evaluate the impact of causal assumptions on the study conclusion by
performing a sensitivity analysis. Two illustrative examples are provided for
master protocols using external controls