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RE: Modeling accelerated phase of malignancy

From: Juan Ballesteros <jballesteros>
Date: Sat, 30 May 2015 09:02:03 +0200

Hi Mark,
A different but related issue is that when the malignant cells start prolif=
erating fast, which is the definition of entering an accelerated phase, you=
 would at least 2 different clones or subpopulation within your malignant c=
ells: one initial clone less proliferating, and a new clone highly prolifer=
ating. These 2 clones have different biology, and different sensitivity to=
 different drugs. The different drug sensitivity come snot only from differ=
ent molecular lesions that made the cells highly proliferating, but also be=
cause many drugs have different activities on proliferating vs non prolifer=
ating cells. Can you model 2 cell subpopulations, one less proliferating a=
nd 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 t=
he malignant cells? This would be much closer to the real process.

De: owner-nmusers
ombre de Mark Sale
Enviado el: Saturday, May 30, 2015 4:45 AM
Para: echigutsa
CC: nmusers
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).

From: echigutsa]
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 ap=
pears to behave better for time-dependent changes.

Best wishes,


Sent from Yahoo Mail on Android<

From: Mark Sale <msale
To: nmusers<mailto:nmusers
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 stand=
ard serial compartment model, with a zero order input rate, then first orde=
r 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 poin=
t change to an exponential growth. I'm having trouble getting NONMEM 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) 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 fo=
r the natural history and haven't been able to yet. That, I think would so=
lve 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=


Received on Sat May 30 2015 - 03:02:03 EDT

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