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The excess hazard ratio of death was estimated using a relative survival model based on the general linear model.
The excess mortality rates were estimated for patients diagnosed with colon cancer in five cancer control regions in Finland during 2000 2007 using a relative survival regression model.
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It uses a relative survival method which gives a measure of excess mortality due to cancer.
We used a relative survival model in which the excess mortality hazard is estimated with a maximum likelihood approach from individual tumour records (Estève et al, 1990).
Secondly, since information on cause of death was missing for 86% of the individuals in this series, we used a relative survival model, but the results could not be confirmed by Cox proportional regression.
Our analysis used a relative risk of survival for revascularization in high risk patients from a meta-analysis of trials done nearly 20 years ago [ 5].
(A) Relative survival using EcASNase2.
It has been shown that the extrapolation of the observed survival function can be done reliably using flexible parametric survival models within a relative survival approach [ 3].
For T1 and T2, a relative survival of 87% was used, for T3 a relative survival of 77% (source: IKA, Comprehensive Cancer Centre Amsterdam).
To predict the potential mortality reduction from PCR+ triggered earlier adequate treatment, we used a relative risk of non-survival between immediate and delayed adequate antimicrobial treatment (RR †) of 2.32 (CI 1.96 to 2.74; P < 0.001).
The risk of cardiovascular LEs was modelled using Royston Parmar relative survival, thereby adjusting for the risk of a cardiovascular event in the general population by attained age, year of event and sex (Royston and Lambert, 2006).
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