..
When you use -adjustfor()- in -sts graph-, the survival functions are obtained from a Cox model.
Suppose you are interested in the effect of a treatment (treat, 0=no, 1=yes) adjusted for sex (0=female, 1=male).
sts graph, by(treat) adjustfor(sex)
This will produce a graph with two curves that are obtained from the baseline survival functions estimated in two Cox models:
xi:stcox i.sex if treat==0
xi:stcox i.sex if treat==1
______________________________________________
Kieran McCaul MPH PhD
WA Centre for Health & Ageing (M573)
University of Western Australia
Level 6, Ainslie House
48 Murray St
Perth 6000
Phone: (08) 9224-2701
Fax: (08) 9224 8009
email: [email protected]
http://myprofile.cos.com/mccaul
http://www.researcherid.com/rid/B-8751-2008
______________________________________________
Man is a credulous animal, and must believe something; in the absence of good grounds for belief,
he will be satisfied with bad ones. Bertrand Russell
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Ricardo Ovaldia
Sent: Tuesday, 9 June 2009 9:02 AM
To: [email protected]
Subject: RE: st: Adjusted Kaplan-Meier curves
Thank you Kieran. That is what I was thinking. The parallelism is cause by the PH assumptions. So the question remains. What method is being use in published manuscripts that report "Adjusted Kaplan-Meier curves"?
See for example:
http://content.nejm.org/cgi/reprint/342/15/1077.pdf
or
http://content.nejm.org/cgi/reprint/342/15/1077.pdf
They claim using Cox to adjust, but the curves are not parallel.
Ricardo Ovaldia, MS
Statistician
Oklahoma City, OK
--- On Mon, 6/8/09, Kieran McCaul <[email protected]> wrote:
> From: Kieran McCaul <[email protected]>
> Subject: RE: st: Adjusted Kaplan-Meier curves
> To: [email protected]
> Date: Monday, June 8, 2009, 7:00 PM
> The curves generated after a Cox
> model are always going to be parallel because the Cox model
> assumes proportional hazards. If your Kaplan-Meier
> curves are crossing, this could indicate that the hazards
> are not proportional. It depends where the cross-over
> occurs. They will often cross-over towards the end of
> follow-up, but that's usually because the data is getting
> sparse and the survival estimates are becoming a bit
> erratic.
>
> If the cross-over occurs at a time point where you still
> have a reasonable amount of data, then you need to check the
> proportionality assumption in the Cox model.
>
> ______________________________________________
> Kieran McCaul MPH PhD
> WA Centre for Health & Ageing (M573)
> University of Western Australia
> Level 6, Ainslie House
> 48 Murray St
> Perth 6000
> Phone: (08) 9224-2701
> Fax: (08) 9224 8009
> email: [email protected]
> http://myprofile.cos.com/mccaul
> http://www.researcherid.com/rid/B-8751-2008
> ______________________________________________
> Man is a credulous animal, and must believe something; in
> the absence of good grounds for belief,
> he will be satisfied with bad ones. Bertrand Russell
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]]
> On Behalf Of Ricardo Ovaldia
> Sent: Tuesday, 9 June 2009 7:33 AM
> To: [email protected]
> Subject: Re: st: Adjusted Kaplan-Meier curves
>
> Thank you Maarten.
>
> That is what exactly what I did, except that I used the
> -at()- option to plot one curve for each drug. I used the
> dummies to do that such that for example for drug=1 it would
> be -at(_Idrug_2=0 _Idrug_3=0)- and so on. However the curves
> are parallel, with jumps at every death and do not look like
> the unadjusted curves.
>
> Ricardo.
>
> Ricardo Ovaldia, MS
> Statistician
> Oklahoma City, OK
>
>
> --- On Mon, 6/8/09, Maarten buis <[email protected]>
> wrote:
>
> > From: Maarten buis <[email protected]>
> > Subject: Re: st: Adjusted Kaplan-Meier curves
> > To: [email protected]
> > Date: Monday, June 8, 2009, 11:12 AM
> >
> > --- On Mon, 8/6/09, Ricardo Ovaldia wrote:
> > > I have been asked to plot Kaplan-Meier curves
> adjusted
> > for
> > > covariates, such as age, gender, race.
> > > My thought was to use -stcox- to adjust and then
> plot
> > the
> > > adjusted survival using -stcurve-.
> > > But I am not sure I am doing this correctly. The
> KM
> > curves
> > > plotted with -sts graph,by()- crossover, but
> those
> > plotted
> > > with -stcurve- do not and also they have a lot
> more
> > steps
> > > than the original curves. Any ideas?
> >
> > Sounds like a reasonable strategy to me. I don't have
> any
> > concrete ideas, except that I added the example below
> of
> > how I would do this. Maybe you can see something in my
>
> > example that is different from what you did (no
> guarantees
> > that what did is better than what you did though).
> >
> > *--------- begin example --------
> > sysuse cancer, clear
> > stset studytime, failure(died)
> > xi: stcox i.drug age, basesurv(S)
> > stcurve, survival
> > *--------- end example ----------
> >
> > Hope this helps,
> > Maarten
> >
> > -----------------------------------------
> > Maarten L. Buis
> > Institut fuer Soziologie
> > Universitaet Tuebingen
> > Wilhelmstrasse 36
> > 72074 Tuebingen
> > Germany
> >
> > http://home.fsw.vu.nl/m.buis/
> > -----------------------------------------
> >
> >
> >
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/help.cgi?search
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
>
>
>
> *
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>
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