Methods for Improving the Variance Estimator of the Kaplan-Meier Survival Function, When There Is No, Moderate and Heavy Censoring-Applied in Oncological Datasets.

In case of heavy and even moderate censoring, a common problem with the Greenwood and Peto variance estimators of the Kaplan-Meier survival function is that they can underestimate the true variance in the left and right tails of the survival distribution. Here, we introduce a variance estimator for the Kaplan-Meier survival function by assigning weight greater than zero to the censored observation. On the basis of this weight, a modification of the Kaplan-Meier survival function and its variance is proposed.