Hyewon,

Sorry -- I just realized that EFF is not the drug effect but 1-drug effect so that it has a value of 1 when AUC is zero. Please ignore my remarks about EFF being zero when AUC is zero in my comments below and consider this code to describe the effect of AUC on hazard:

 HAZNOW=LAMD*ALPH*(TIME+DEL2)**(ALPH-1)*(1-BETAE*AUC/(EC+AUC))

I think it is a very strong assumption that the drug will reduce the hazard to zero at infinite AUC which you can test by estimating a parameter (such as BETAE). If BETAE is significantly less than 1 then this means the assumption is not supported.

Nick

On 24/03/2011 8:17 a.m., Nick Holford wrote:
Hyewon,

The most obvious problem with your code is in $DES. You must use the variable T not the variable TIME when referring to a time varying hazard. TIME is the time on each data record. It does not change in $DES. T is the time from the last data record upto the current data record and changes within $DES.

You are predicting the likelihood of an event at the exact time of the event observation record with multiple events per subject. As you seem to realize you need tocompute the cumulative hazard (CUMHAZ) either from TIME=0 or from the TIME of the last non-censored event for each subject.

In my opinion the following code is clearer and less dependent on your data structure than the method you are using which works only if your data has just event records after the TIME=0 record.

IF (MDV.EQ.0.AND.CS.EQ.0) THEN
   OLDCHZ=A(1) ; cum haz upto time of this event
ELSE
  OLDCHZ=OLDCHZ ; need to do this if OLDCHZ is a random variable
ENDIF

Your hazard model looks rather complicated. It seems to be based on the product of a Weibull baseline hazard
LAMD*ALPH*(TIME+DEL2)**(ALPH-1)
then something odd involving the Weibull parameters
*EXP(-LAMD*(TIME+DEL2)**ALPH)
and then forces the hazard to be zero if AUC is zero.
*EFF
Is this really what you want? Do you know the hazard of event is zero if AUC is zero? Or is the last right parenthesis in the wrong place?

I would suggest something like this where LAMD and ALPH are the two parameters of the Weibull baseline hazard (when AUC is zero) and BETAE is a parameter describing the effect of the drug on the overall hazard.

 HAZNOW=LAMD*ALPH*(TIME+DEL2)**(ALPH-1)*EXP(BETAE*EFF)

You may also find it easier to develop the model if you do not try to estimate a random effect on LAMD until you have got reasonable estimates for the other parameters.

You may find it helpful to look at this presentation showing how to code time to event models in NM-TRAN:
http://pkpdrx.com/holford/docs/time-to-event-analysis.pdf

Best wishes,

Nick

On 24/03/2011 3:25 a.m., Hyewon Kim wrote:
Dear NMuser

I am trying to analyze time to repeated event data using NONMEM.
The response were obtained till 24 hours after drug administration.
Inhibitory Emax model was implemented.
I am getting unreasonable parameter estimates which is far beyond what data say. If some body can point out what i am doing wrong, it would be very helpful.
Thank you in advance.

Hyewon


Data set (# of observations =62, # of patients=50 )
C        ID        TIME         CS         MDV        AUC
.          101     0                .            1                1.111
.          101     0.05           0            0               1.111
.          101     2               0            0                1.111
.          102     0                .            1                 0
.          102     24             1            0                0
.          103     0                .            1                0.999
.          103     0.75          .             0                0.999
....

Model File
$PROB RUN# 101
$INPUT C ID TIME CS MDV AUC
;CS:0=having event,1=censored
$DATA .data.csv IGNORE=C
$SUBROUTINE ADVAN=6 TOL=6
$MODEL
COMP=(HAZARD)
$PK
   LAMD=THETA(1)*EXP(ETA(1))    ;scale factor
   ALPH=THETA(2)                             ;shape factor

EC=THETA(3) ;AUC when effect is half of its max
   EFF=1-AUC/(EC+AUC)                 ;drug effect

$DES
  DEL=1E-6
  DADT(1)=LAMD*ALPH*(TIME+DEL)**(ALPH-1)*EXP(-LAMD*(TIME+DEL)**ALPH)*EFF

$ERROR
  DEL2=1E-6
  IF(NEWIND.NE.2) OLDCHZ=0
  CHZ=A(1)-OLDCHZ
  OLDCHZ=A(1)
  SUR=EXP(-CHZ)
HAZNOW=LAMD*ALPH*(TIME+DEL2)**(ALPH-1)*EXP(-LAMD*(TIME+DEL2)**ALPH)*EFF

  IF(CS.EQ.1) Y=SUR                        ;survival prob of censored
  IF(CS.EQ.0) Y=SUR*HAZNOW         ;pdf of event

$THETA
  (0,10)         ;[scale factor]
  (0,1.0)        ;[shaph factor]
  (0,0.01)      ;[AUC at half of Emax]

$OMEGA
  0.01     ;[p] omega(1,1)

$EST METHOD=COND LIKE LAPLACIAN PRINT=5 SIG=3 MAX=9999 MSFO=101.msf

$COV PRINT=E

$TABLE ID TIME SUR AUC ONEHEADER NOPRINT FILE=101.tab

--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology&  Clinical Pharmacology
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53
email:n.holf...@auckland.ac.nz
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology&  Clinical Pharmacology
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53
email: n.holf...@auckland.ac.nz
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford

Reply via email to