  The Brier score is commonly used for evaluating probability predictions. In
survival analysis, with right-censored observations of the event times, this
score can be weighted by the inverse probability of censoring (IPCW) to retain
its original interpretation. It is common practice to estimate the censoring
distribution with the Kaplan-Meier estimator, even though it assumes that the
censoring distribution is independent of the covariates. This paper discusses
the general impact of the censoring estimates on the Brier score and shows that
the estimation of the censoring distribution can be problematic. In particular,
when the censoring times can be identified from the covariates, the IPCW score
is no longer valid. For administratively censored data, where the potential
censoring times are known for all individuals, we propose an alternative
version of the Brier score. This administrative Brier score does not require
estimation of the censoring distribution and is valid even if the censoring
times can be identified from the covariates.
