Health economic evaluations often require predictions of survival rates
beyond the follow-up period. Parametric survival models can be more convenient
for economic modelling than the Cox model. The generalized gamma (GG) and
generalized F (GF) distributions are extensive families that contain almost all
commonly used distributions with various hazard shapes and arbitrary
complexity. In this study, we present a new SAS macro for implementing a wide
variety of flexible parametric models including the GG and GF distributions and
their special cases, as well as the Gompertz distribution. Proper custom
distributions are also supported. Different from existing SAS procedures, this
macro not only supports regression on the location parameter but also on
ancillary parameters, which greatly increases model flexibility. In addition,
the SAS macro supports weighted regression, stratified regression and robust
inference. This study demonstrates with several examples how the SAS macro can
be used for flexible survival modeling and extrapolation.Comment: 15 pages, 1 figure, 10 tables, accepted by The Clinical Data Science
Conference - PHUSE US Connect 202