RE: Modeling accelerated phase of malignancy
Hi Mark,
A different but related issue is that when the malignant cells start
proliferating fast, which is the definition of entering an accelerated phase,
you would at least 2 different clones or subpopulation within your malignant
cells: one initial clone less proliferating, and a new clone highly
proliferating. These 2 clones have different biology, and different
sensitivity to different drugs. The different drug sensitivity come snot only
from different molecular lesions that made the cells highly proliferating, but
also because many drugs have different activities on proliferating vs non
proliferating cells. Can you model 2 cell subpopulations, one less
proliferating and another more proliferating, where at the beginning there is
only the non-proliferating clone, then the proliferating clone appears taking
over the % of cells over time, until only the proliferating clone is present
among the malignant cells? This would be much closer to the real process.
Best
Joan
Quoted reply history
De: [email protected] [mailto:[email protected]] En
nombre de Mark Sale
Enviado el: Saturday, May 30, 2015 4:45 AM
Para: [email protected]
CC: [email protected]
Asunto: RE: [NMusers] Modeling accelerated phase of malignancy
Thanks to Mannie, this is the correct way to solve this (and seems to work as
well).
Thanks
Mark
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]]
Sent: Friday, May 29, 2015 7:34 PM
To: Mark Sale
Subject: Re: [NMusers] Modeling accelerated phase of malignancy
Hi Mark
Have you tried using MTIME and MPAST for the switch? In my experience it
appears to behave better for time-dependent changes.
Best wishes,
Mannie
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________________________________
From: Mark Sale <[email protected]<mailto:[email protected]>>;
To: [email protected]<mailto:[email protected]>
<[email protected]<mailto:[email protected]>>;
Subject: [NMusers] Modeling accelerated phase of malignancy
Sent: Fri, May 29, 2015 7:52:36 PM
Dear Colleagues,
I'm working on a model of a malignancy that, at some point in the course of
the disease enters into an accelerated phase. I'm using a sort of standard
serial compartment model, with a zero order input rate, then first order
transit to the next compartment. I think the "correct" model for natural
history is a slow increase in the input rate over time, then, at some point
change to an exponential growth. I'm having trouble getting NONMEM to do this.
The relevant code I have in $DES is:
IF(T.LT.NTLAG) THEN
LGIND = 0
ELSE
LGIND = 1
END IF
NATHL = LGIND*NATH
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 the
study and the onset of the accelerated phase, NATH is the natural history term,
NATHL is the lagged natural history term, INPUT is the zero order input 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 from person to
person. With FOCE I get zero gradient for it. BAYES, SAEM, IMP 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 that
point in time, so small changes in ETA (smaller than the integration step size)
don't change the predicted value, so no gradient and all ETAs = 0 with EM
methods.
I've tried to figure out a way to do this with an additional compartment for
the natural history and haven't been able to yet. That, I think would 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 time?
Thanks
Mark