On Estimation in Relative survival

Speaker: Maja Pohar Perme, Associate Professor, Institute of Biostatistics and Medical Informatics, Faculty of Medicine, University of Ljubljana, Slovenia.


In population based cancer survival analysis, the information on cause of death is often unavailable or unreliable, nevertheless cancer specific questions are of interest.  The idea of relative survival is to bring in the missing information through the population mortality tables that serve as the information on the other-cause mortality. In cancer registry analysis, the researchers are interested in a measure that is directly related to cancer specific hazard and hence enables more direct comparisons of populations with different background mortality hazard, this is the reason why net survival is often considered. In this talk we review the assumptions of net survival and discuss what measure can be estimated without forcing assumptions that cannot be tested and do not make much sense in the real world.
Several estimators have been proposed for net survival estimation, but only recently, a consistent estimator has been introduced. Its use in practice has revealed an excessively large variance when estimating net survival of older age groups. We first simplify the problem by considering a non-censored case to show that the problem of large variance is intrinsic to the definition of net survival and not a property of a specific estimator. We then continue from the definition of net survival and generalize it to the censored case by the use of pseudo-observations. The estimator developed in this way has all the desired properties, we also provide a formula for its variance. We illustrate the issues using Slovene cancer registry data.


Published Feb. 1, 2019 12:11 PM - Last modified Feb. 6, 2019 9:38 AM