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Re: st: stcrreg: startifications and median survival?


From   rgutierrez@stata.com (Roberto G. Gutierrez, StataCorp)
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: stcrreg: startifications and median survival?
Date   Wed, 14 Oct 2009 14:17:25 -0500

Wei Xun <weiwxun@googlemail.com> asks:

> I apologise if this has been asked before but my search in the archives did
> not return any relevant results.

> I am currently trying to estimating the effects of certain exposures on
> mortality from specific cancers where a large proportion of deaths occur
> from other causes. The new command stcrreg in STATA 11 has been most useful.

> However, I noticed that unlike stcox, stcrreg does not allow any
> stratification terms within the model. Are there any particular reasons why
> this not possible? I am aware of the fact that the power will be
> significantly reduced.

To the best of our knowledge, the theoretical aspects of stratification in the
Fine and Gray (1999) regression model have yet to be established in the
literature.  Fine and Gray do discuss stratifying to achieve better estimates
of the censoring distribution of the data, a key component in competing-risks
regression, and that is a feature we do plan on adding to -stcrreg-.  They do
not, however, discuss stratification in the sense of allowing different
subhazard functions over groups while maintaining unified subhazards ratios,
and we unaware of any other reference that makes this extension.

Offhand I can think of no reason why stratification would not work just as it
does in Cox regression, but because with competing risks you are dealing with
subdistribution functions and not proper probability distribution functions it
is hard to say whether the theory will back that up.  More investigation is
needed.

> Also my second problem is that I also would like to calculate the median
> survival time after the adjustment for competing causes. The stci command
> which works with stcox does not extent to stcrreg. Could I alternatively use
> stcompt to calculate the cumulative incidence curve and estimate it from the
> point of 50%?

Yes.  Or you could alternatively fit an -stccreg- model with no covariates
(or with covariates for that matter) and use -stcurve- afterward to plot the
cumulative incidence curve.  From that curve, you can estimate the 50% point.

Reference:

Fine, J. P. and R. J. Gray. 1999. A proportional hazards model for the
    subdistribution of a competing risk.  Journal of the American Statistical
    Association. 94: 496-509.

--Bobby
rgutierrez@stata.com
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