From: Nick Holford <*n.holford*>

Date: Thu, 08 Oct 2009 21:28:34 -0400

Tianli,

Please look carefully at this:

http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford/teaching/pharmacometrics/_docs/modelling_likelihoods_using_NONMEM_VI.pdf

It shows you how to do time to event models which also include PKPD

variables which change as a function of dose and time.

Nick

wangx826

*> Dear Nick,
*

*>
*

*> I think I didn't make it clear in my first email that my model is a
*

*> PK-PD linked model, which means, the probability of a certain event is
*

*> a function of drug exposure which can describe as a function of time
*

*> and some other parameters like CL, V, etc. But it seems to me that the
*

*> hazard function only takes time into account. I am not familiar with
*

*> survival analysis so this might be a very basic question: How can I
*

*> combine the PK/PD model with the time-to-event model?
*

*>
*

*> Thanks in advance,
*

*> Tianli
*

*>
*

*> On Oct 8 2009, Nick Holford wrote:
*

*>
*

*>> Tianli,
*

*>>
*

*>> Your data sounds like it could be described by a survival analysis. A
*

*>> time to event model will give you the survivor function i.e. the prob
*

*>> of not having had the event as a function of time. The event in your
*

*>> case is defined by the 'certain PD score'. The censoring will of
*

*>> course be taken care of by a typical survival analysis.
*

*>>
*

*>> Nick
*

*>>
*

*>> wangx826 *

*>>> Dear NMUsers,
*

*>>>
*

*>>> I am modeling ordered-categorical PD data versus time, but since the
*

*>>> clinical trial is ongoing, I don't currently have complete data set
*

*>>> for each subject. In other words, for some subjects, I have 1 year's
*

*>>> PD data, but for some others, I can only collect PD data for 1
*

*>>> month. For the 1 month's case, it is like missing data for the rest
*

*>>> of time. But I need to consider time course of the proportion of
*

*>>> subjects who got a certain PD score. In my case, if I use the
*

*>>> general logistic regression model to fit the relationship between
*

*>>> time and proportions of event, would there be any problem? If so,
*

*>>> how can I avoid it? Or need I consider censoring like survival
*

*>>> analysis?
*

*>>>
*

*>>> Any suggestion would be appreciated very much.
*

*>>>
*

*>>> Thanks in advance,
*

*>>> Tianli
*

*>>> *****************************************************************
*

*>>> Tianli Wang
*

*>>> University of Minnesota
*

*>>
*

*>>
*

--

Nick Holford, Professor Clinical Pharmacology

Dept Pharmacology & Clinical Pharmacology

University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand

n.holford

mobile: +64 21 46 23 53

http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

Received on Thu Oct 08 2009 - 21:28:34 EDT

Date: Thu, 08 Oct 2009 21:28:34 -0400

Tianli,

Please look carefully at this:

http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford/teaching/pharmacometrics/_docs/modelling_likelihoods_using_NONMEM_VI.pdf

It shows you how to do time to event models which also include PKPD

variables which change as a function of dose and time.

Nick

wangx826

--

Nick Holford, Professor Clinical Pharmacology

Dept Pharmacology & Clinical Pharmacology

University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand

n.holford

mobile: +64 21 46 23 53

http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

Received on Thu Oct 08 2009 - 21:28:34 EDT