  This research was motivated by studying anti-drug antibody (ADA) formation
and its potential impact on long-term benefit of a biologic treatment in a
randomized controlled trial, in which ADA status was not only unobserved in the
control arm but also in a subset of patients from the experimental treatment
arm. Recent literature considers the principal stratum estimand strategy to
estimate treatment effect in groups of patients defined by an intercurrent
status, i.e. in groups defined by a post-randomization variable only observed
in one arm and potentially associated with the outcome. However, status
information might be missing even for a non-negligible number of patients in
the experimental arm. For this setting, a novel weighted principal stratum
approach is presented: Data from patients with missing intercurrent event
status were re-weighted based on baseline covariates and additional
longitudinal information. A theoretical justification of the proposed approach
is provided for different types of outcomes, and assumptions allowing for
causal conclusions on treatment effect are specified and investigated.
Simulations demonstrated that the proposed method yielded valid inference and
was robust against certain violations of assumptions. The method was shown to
perform well in a clinical study with ADA status as an intercurrent event.
