NONMEM Users Network Archive

Hosted by Cognigen

RE: Modeling accelerated phase of malignancy

Date: Fri, 29 May 2015 22:12:58 +0100

Dear Mark,

I think one problem might be the distributioal assumption on NTLAG in that =
if you have outlying individuals with early/late lag you may need to think =
of a sensible transformation for the ETA or there might be no obvious one. =
 Do all the subjects go into the exponential phase or might the typical val=
ue of NTLAG be greater than your observed time? That aside, something to t=
ry would be to have a continuous function driving NTLAG, e.g.:

NATHL = NATH*T**50/(T**50+NTLAG**50)

Play around with the shape parameter value, or even consider estimating it =
thus allowing a more gradual transition?
Hope this helps,


Joseph F Standing
MRC Fellow, UCL Institute of Child Health
Antimicrobial Pharmacist, Great Ormond Street Hospital
Tel: +44(0)207 905 2370
Mobile: +44(0)7970 572435
From: owner-nmusers
 Of Mark Sale [msale
Sent: 29 May 2015 20:52
To: nmusers
Subject: [NMusers] Modeling accelerated phase of malignancy

Dear Colleagues,
  Iím working on a model of a malignancy that, at some point in the cours=
e of the disease enters into an accelerated phase. Iím using a sort of s=
tandard serial compartment model, with a zero order input rate, then first =
order transit to the next compartment. I think the ďcorrectĒ model for=
 natural history is a slow increase in the input rate over time, then, at s=
ome point change to an exponential growth. Iím having trouble getting NO=
NMEM to do this. The relevant code I have in $DES is:

    LGIND = 0
    LGIND = 1
DADT(3) = (INPUT-A(3)*K)+ A(3)*NATHL
DADT(4) = A(3)*K-A(4)*K
Where NTLAG is an estimated parameter for the lag time between entry into t=
he study and the onset of the accelerated phase, NATH is the natural histor=
y term, NATHL is the lagged natural history term, INPUT is the zero order i=
nput rate and K is the first order transit constant. FOCE actually works =
pretty well for this for the THETA term for NTLAG, gives reasonable values.=
  Probably is with the ETA for NTLAG (which is essential since it varies fr=
om person to person. With FOCE I get zero gradient for it. BAYES, SAEM, I=
MP MAP and ITS give reasonable values for OMEGA, but conditional values for=
 ETA are all zero.
What I think is going on is that, unlike an ALAG, there is not event at tha=
t point in time, so small changes in ETA (smaller than the integration step=
 size) donít change the predicted value, so no gradient and all ETAs = =
0 with EM methods.
Iíve tried to figure out a way to do this with an additional compartment =
for the natural history and havenít been able to yet. That, I think woul=
d solve the problem, since an event would be inserted at the end of ALAG.
Any ideas on a solution, is there a way to insert an event at an unknown ti=



This message may contain confidential information. If you are not the inten=
ded recipient please inform the
sender that you have received the message in error before deleting it.
Please do not disclose, copy or distribute information in this e-mail or ta=
ke any action in reliance on its contents:
to do so is strictly prohibited and may be unlawful.

Thank you for your co-operation.

NHSmail is the secure email and directory service available for all NHS sta=
ff in England and Scotland
NHSmail is approved for exchanging patient data and other sensitive informa=
tion with NHSmail and GSi recipients
NHSmail provides an email address for your career in the NHS and can be acc=
essed anywhere

Received on Fri May 29 2015 - 17:12:58 EDT

The NONMEM Users Network is maintained by ICON plc. Requests to subscribe to the network should be sent to:

Once subscribed, you may contribute to the discussion by emailing: