  In adaptive clinical trials, the conventional end-of-trial point estimate of
a treatment effect is prone to bias, that is, a systematic tendency to deviate
from its true value. As stated in recent FDA guidance on adaptive designs, it
is desirable to report estimates of treatment effects that reduce or remove
this bias. However, it may be unclear which of the available estimators are
preferable, and their use remains rare in practice. This paper is the second in
a two-part series that studies the issue of bias in point estimation for
adaptive trials. Part I provided a methodological review of approaches to
remove or reduce the potential bias in point estimation for adaptive designs.
In part II, we discuss how bias can affect standard estimators and assess the
negative impact this can have. We review current practice for reporting point
estimates and illustrate the computation of different estimators using a real
adaptive trial example (including code), which we use as a basis for a
simulation study. We show that while on average the values of these estimators
can be similar, for a particular trial realisation they can give noticeably
different values for the estimated treatment effect. Finally, we propose
guidelines for researchers around the choice of estimators and the reporting of
estimates following an adaptive design. The issue of bias should be considered
throughout the whole lifecycle of an adaptive design, with the estimation
strategy pre-specified in the statistical analysis plan. When available,
unbiased or bias-reduced estimates are to be preferred.
