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st: new command for the covariate-adjusted cumulative incidence

From   "" <>
Subject   st: new command for the covariate-adjusted cumulative incidence
Date   Thu, 25 Jun 2009 13:12:07 +0200 (CEST)

Dear Stata Users,

thanks to Kit Baum, a new Stata macro, -stcompadj-, 
is available for download from the SSC Archive.

-stcompadj- estimates 
the covariate-adjusted cumulative incidence function in the presence of 
competing risks.
It should be noted that the covariate adjustment is 
obtained by fitting a Cox model or a flexible parametric model.

Therefore, the covariate-adjusted cumulative incidence is different 
from the same function obtained after fitting a Fine and Gray model, 
not yet available within Stata.

For Stata users interested in this 
topic, here are some remarks from the help file.

Cox regression in the 
presence of competing risks is usually performed by fitting separate 
models for each failure type.  It is possible
to obtain the same 
results by using a single analysis after appropriately adapting the 
data set. In short this consists of expanding each
observation for each 
cause of failure, ...

After adapting the data set -stcompadj- fits a 
Cox model whose covariates are the variables specified in var [[= #] 
var ...]. Then, from the
baseline cumulative hazard and the linear 
predictor -stcompadj- computes and saves in two variables the 
cumulative incidence (CI) function for the
main and competing event 
adjusted to the mean or to the specified number of each covariate if 
the = # part is specified.

As an alternative to the Cox model, a 
flexible parametric model can be fitted to the expanded data set by 
specifying flexible. This allows
one to easily estimate the confidence 
intervals of the CI function. The stpm2 (Lambert 2009) and rcsgen 
(Nelson, Lambert, Rutherford 2008)
user packages must be installed on 
the system. (net describe stpm2 and ssc describe rcsgen).

Data in the 
expanded format can be saved by using savexpanded(filename). This 
format allows to test the equality of the effects of a
covariate on the 
main and on the competing event and the difference between the hazards 
of the main and competing event under the
assumption of the cause-
specific hazards being proportional.

The new command is provided with 
a help file which enables the user to run the example, described in the 
references below, by simply clicking on the viewer window.

Rosthoj S., Andersen P. K., and Abildstrom S. Z. SAS macros 
for estimation of the cumulative incidence functions based on a Cox 
regression model for competing risks. Computer methods and Programs in 
Biomedicine (2004) 74: 69-75.
Putter H., Fiocco M., and Geskus R. B. 
Tutorial in biostatistics: Competing risks and multi-state models.  
Statistics in Medicine (2007) 26: 2389-2430.

Hope it can be useful.


Enzo Coviello
Unità di Epidemiologia e Statistica ASL Bari

Piazza V. Emanuele, 14 - 70054 GIOVINAZZO (BA)
tel +39 080 
3357883 - fax +39 080 3357867
mobile 347 5016016 
Imbriani, 186 - 70055 MINERVINO MURGE (BA)
tel +39 0883 695055

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