TL30: Interval Censoring in Time to Event data
*Mihaela Obreja, Onyx Pharmaceuticals 

Keywords: survival function, interval censoring, PFS analysis, time to event

Time to event data is critically depending on the time when a certain event of interest happens. In most cases, that time is not exactly known, but only that the event happened within an interval between visits of observation. The estimation of the survival function for this type of data is not trivial and its software implementation is still under development. In this discussion, I plan to summarize some of existing methods (e.g. emicm macro, proc phreg in SAS, glrt package in R) and how to implement them on an example of simulated data with PFS being the event of interest.