  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 investigational products and/or subpopulations
are studied under a single protocol. Master protocols can use external data and
evidence (e.g., external controls) for treatment effect estimation, which can
further improve efficiency of master protocol trials. 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, assessment
of fit-for-use real-world data, and considerations for different types of
master protocols. Similarities and differences between regular randomized
controlled trials and master protocols when using external controls are
discussed. 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 sensitivity analyses. Two illustrative examples for master protocols
using external controls are discussed for their merits and possible improvement
in causal effect estimation.
