Measures of follow-up in time-to-event studies: Why provide them and what should they be?

摘要

Background/Aims: There is some consensus among authors of reports of clinical studies that a measure of follow-up time is informative for the interpretation of the Kaplan-Meier estimate of the survivor function of the event time of interest. Previous authors have suggested that length of follow-up is important to report because the findings of a study should be extracted from the time frame in which most of the subjects have had the event or have remained under observation. This time frame is where the Kaplan-Meier estimate is most stable. This concept of stability is relative to the potential maximum information about the event time distribution contained in the sample; it is not relative to the true, population survivor function. A measure of stability is useful for the interpretation of an interim analysis in which an immature survivor function is presented. Our interest in this article lies in characterizing the unobserved, complete follow-up Kaplan-Meier estimate based on the observed, partial follow-up estimate. Our focus is not on characterizing the true event time distribution relative to its estimate. The concept of stability has not been well-defined in the literature, which has led to inconsistency and lack of transparency across trials in their attempts to capture it through a variety of measures of follow-up.