Re: COX Proportional Hazard Model with Time DependentCovariate
Jeff,
Thanks for highlighting the time to event analysis terminology issue. I think
nmusers need to pay particular attention to a major difference between two
classes of methods.
1. The Cox proportional hazards model is a semiparametric method that is used
to describe the difference between treatments. It assumes the underlying hazard
for both treatments is the same.
2. Parametric methods (e.g. using the Weibull distribution) try to describe the
undelying hazard for each treatment and do not require the assumption that the
underlying hazard is the same.
The semiparametric method is somewhat similar to doing a bioequivalence
analysis with NCA. It can tell you about the difference between the two
formulations under the assumption that the clearance is the same but it doesnt
tell you the underlying PK parameters (clearance, volume, absorption rate
constant etc) and cannot make predictions of the time course of concentration.
The parametric time to event method describes the full hazard function but is
dependent on assuming a particular model -- just like assuming a specific
compartmental model and input function in compartmental PK.
As nmusers will appreciate, one can learn and understand much more from a
compartmental model than one can from doing a bioequivalence analysis. The
parametric approach does not require the restrictive assumption that the
underlying hazard is the same for both treatments (which is analogous to having
to assume clearance is the same for a bioequivalence analysis).
So it depends what you want -- if you just want to collect P values then use
the semiparametric method. But if you want to understand the biology of the
disease and the effects of drug treatments you need to seriously consider the
parametric method.
Nick
[EMAIL PROTECTED] wrote:
>
> Liang - There are some examples of NONMEM code in the following link. I have
> used this in the past as a good starting point for specifying time-dependent
> hazard models.
>
> http://anesthesia.stanford.edu/pkpd/NONMEM%20Repository/
>
> A note on nomenclature, I always felt a bit confused about these models till
> I realized the level of ambiguity in the literature. The following words are
> often used in an apparent mosaic fashion to describe different analyses that
> are actually quite similar.
> Survival analysis
> Failure analysis
> Event modeling
> Hazard regression
> Cox proportional hazards model
> Cox model
> Proportional hazards model.
> Weibull (...or insert your favorite function here...) proportional hazards
> model
> Parametric proportional hazards models
> Semi-parametric proportional hazards models
> Cox regression
> Poisson regression, etc...
>
> For more check out: http://en.wikipedia.org/wiki/Proportional_hazards_models
>
> Regards, Jeff
>
>
> "Nick Holford" <[EMAIL PROTECTED]>
>
> Sent by: [EMAIL PROTECTED]
>
> j¬72Z·ÌG{»%Ù·ÿ±
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
email:[EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:373-7556
http://www.health.auckland.ac.nz/pharmacology/staff/nholford/