Parmsurv: a SAS Macro for Flexible Parametric Survival Analysis with Long-Term Predictions

TL;DR

This paper introduces Parmsurv, a versatile SAS macro enabling flexible parametric survival analysis with long-term predictions, supporting various distributions and advanced modeling features for health economic evaluations.

Contribution

The paper presents a new SAS macro that extends survival modeling capabilities by supporting diverse distributions, regression on multiple parameters, and advanced features like weighted and stratified regression.

Findings

Supports a wide range of parametric distributions including GG, GF, and Gompertz.

Enables regression on location and ancillary parameters for increased flexibility.

Demonstrates practical applications with examples for survival modeling and extrapolation.

Abstract

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.