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RE: [NMusers] PRED for BLQ-like observations

From: Bauer, Robert <Robert.Bauer_at_iconplc.com>
Date: Fri, 20 Nov 2015 21:04:19 +0000

Unfortunately adding records to estimation slows down estimation even with MDV=1 records. Please do a search on MDV=101 option in nm730.pdf 1 (section Ignoring Non-Impact Records During Estimation (NM73)). These records will be used only on the $TABLE step.


Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics R&D
ICON Early Phase
Office: (215) 616-6428
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Robert.Bauer_at_iconplc.com<mailto:Robert.Bauer_at_iconplc.com>
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From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] On Behalf Of Nick Holford
Sent: Friday, November 20, 2015 12:39 PM
To: nmusers
Subject: Re: [NMusers] PRED for BLQ-like observations

Pavel,
Did you test the run time with double the records?
I would expect that the MDV=1 records would be largely ignored in the
estimation step and not contribute much to run time.
Nick

On 21-Nov-15 08:59, Pavel Belo wrote:
> Thank you Bill,
> In my case it exactly doubles the number of records... The records
> are daily measures and the code is running slow enough. I'll split the
> code into estimation part and one that that is redundant, but uses a
> larger file and creates an output. It will be something like
> $EST MAXEVALS=9999 SIG=3 NOABORT PRINT=1 SORT CONSTRAIN=5
> METHOD=SAEM NBURN=0 NITER=0 POSTHOC INTERACTION
> LAPLACIAN GRD=TG(1-7):TS(8-9) CTYPE=3 CINTERVAL=10
> I guess the best future way is modify something in NONMEM so there is
> an option to provide only PRED in the PRED column (version 7.4?).
> Thanks!
> Pavel
> On Fri, Nov 20, 2015 at 01:06 PM, Denney, William S. wrote:
>
> Hi Pavel,
>
> The easiest way that I know is to generate your data file with one
> set of rows for estimation with M3 and another row just above or
> below with MDV=1. NONMEM will then provide PRED and IPRED in the
> rows with MDV=1.
>
> Thanks,
>
> Bill
>
> *From:*owner-nmusers_at_globomaxnm.com
> [mailto:owner-nmusers_at_globomaxnm.com] *On Behalf Of *Pavel Belo
> *Sent:* Friday, November 20, 2015 11:47 AM
> *To:* nmusers_at_globomaxnm.com<mailto:nmusers_at_globomaxnm.com>
> *Subject:* [NMusers] PRED for BLQ-like observations
>
> Hello The NONMEM Users,
>
> When we use M3-like approach, the outputs has PRED for non-missing
> observations and something else for BLQ (is that PRED=CUMD?). As
> in the diagnostic figures PRED for BLQs looks like noise, I remove
> them. It is not always perfect, but OK in for most frequent cases.
>
> When we use count data such as a scale with few possible values
> (for example, 0, 1, 2, 3, 4, 5), it makes more sense to use PHI
> function (home-made likelihood) for all observations rather than
> to treat the count as a continuous variable an apply M3-like
> approach to 1 and 5 while only (as we know, they are like LLOQ and
> ULOQ). In this case, all PRED values look like noise. A hard way
> to replace the noise with PRED value is to simulate PRED for each
> point and merge them with the DV and IPRED data. Is there an easy
> way?
>
> (The model runs well and better than when the count is treated as
> a continuous variable.)
>
> Thanks!
>
> Pavel
>

--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology, Bldg 503 Room 302A
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
office:+64(9)923-6730 mobile:NZ+64(21)46 23 53
email: n.holford_at_auckland.ac.nz<mailto:n.holford_at_auckland.ac.nz>
http://holford.fmhs.auckland.ac.nz/<http://holford.fmhs.auckland.ac.nz/>

Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop, B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models - tests of assumptions and predictions. Journal of Pharmacology & Clinical Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin Pharmacol. 2015;79(1):18-27.
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Received on Fri Nov 20 2015 - 16:04:19 EST

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