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2017 ; 17
(1
): 79
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On comparison of net survival curves
#MMPMID28464839
Pavli? K
; Perme MP
BMC Med Res Methodol
2017[May]; 17
(1
): 79
PMID28464839
show ga
BACKGROUND: Relative survival analysis is a subfield of survival analysis where
competing risks data are observed, but the causes of death are unknown. A first
step in the analysis of such data is usually the estimation of a net survival
curve, possibly followed by regression modelling. Recently, a log-rank type test
for comparison of net survival curves has been introduced and the goal of this
paper is to explore its properties and put this methodological advance into the
context of the field. METHODS: We build on the association between the log-rank
test and the univariate or stratified Cox model and show the analogy in the
relative survival setting. We study the properties of the methods using both the
theoretical arguments as well as simulations. We provide an R function to enable
practical usage of the log-rank type test. RESULTS: Both the log-rank type test
and its model alternatives perform satisfactory under the null, even if the
correlation between their p-values is rather low, implying that both approaches
cannot be used simultaneously. The stratified version has a higher power in case
of non-homogeneous hazards, but also carries a different interpretation.
CONCLUSIONS: The log-rank type test and its stratified version can be interpreted
in the same way as the results of an analogous semi-parametric additive
regression model despite the fact that no direct theoretical link can be
established between the test statistics.
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