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Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects.

Abstract：

:Relative survival is used to estimate patient survival excluding causes of death not related to the disease of interest. Rather than using cause of death information from death certificates, which is often poorly recorded, relative survival compares the observed survival to that expected in a matched group from the general population. Models for relative survival can be expressed on the hazard (mortality) rate scale as the sum of two components where the total mortality rate is the sum of the underlying baseline mortality rate and the excess mortality rate due to the disease of interest. Previous models for relative survival have assumed that covariate effects act multiplicatively and have thus provided relative effects of differences between groups using excess mortality rate ratios. In this paper we consider (i) the use of an additive covariate model, which provides estimates of the absolute difference in the excess mortality rate; and (ii) the use of fractional polynomials in relative survival models for the baseline excess mortality rate and time-dependent effects. The approaches are illustrated using data on 115 331 female breast cancer patients diagnosed between 1 January 1986 and 31 December 1990. The use of additive covariate relative survival models can be useful in situations when the excess mortality rate is zero or slightly less than zero and can provide useful information from a public health perspective. The use of fractional polynomials has advantages over the usual piecewise estimation by providing smooth estimates of the baseline excess mortality rate and time-dependent effects for both the multiplicative and additive covariate models. All models presented in this paper can be estimated within a generalized linear models framework and thus can be implemented using standard software.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Lambert PC,Smith LK,Jones DR,Botha JL

doi

10.1002/sim.2399

subject

Has Abstract

pub_date

2005-12-30 00:00:00

pages

3871-85

issue

eissn

0277-6715

issn

1097-0258

journal_volume

pub_type

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Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects.