RE: Modeling accelerated phase of malignancy

From: [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 Sent from Yahoo Mail on https://overview.mail.yahoo.com/mobile/?.src=Android ________________________________ 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