Re: [NMusers] PRED for BLQ-like observations

Pavel Belo Thu, 26 Nov 2015 05:23:52 -0800

It is a good point in general and I'll try to use it for simple cases ofBLQ values. In this particular case, Y is a function of more than 1PHI, which requires a numerical method to get IPRED back (assuming inthis case it is PRED).


 
 
 On Sat, Nov 21, 2015 at 10:23 AM, Leonid Gibiansky wrote:

> As we always do post-processing any way, one option is to use PREDprovided by Nonmem to compute inverse cumulative distribution function(qnorm in R, for example) and then restore PRED value


  IPRED = ...
  W     = ...
  LLOQ  = ...
  IF(BQL.EQ.1) Y=PHI((LLOQ-IPRED)/W)

If you have PRED LLOQ and W in the Nonmem output file (that you readto the R data frame "data"), you can re-define

if(BQL == 1) data$PRED = data$LLOQ - qnorm(data$PRED)*data$W # Rcode


(I have not tested it; use on your own risk :) )

Leonid


--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web:    www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel:    (301) 767 5566



On 11/20/2015 5:15 PM, Pavel Belo wrote:

That is perfect!
  P.
On Fri, Nov 20, 2015 at 04:04 PM, Bauer, Robert wrote:

    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 DuringEstimation

    (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

    Mobile: (925) 286-0769

    robert.ba...@iconplc.com
    www.iconplc.com
    *From:*owner-nmus...@globomaxnm.com
    [mailto:owner-nmus...@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 inthe

    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-nmus...@globomaxnm.com
[mailto:owner-nmus...@globomaxnm.com] *On Behalf Of *Pavel Belo
*Sent:* Friday, November 20, 2015 11:47 AM

*To:* nmusers@globomaxnm.com *Subject:* [NMusers] PRED for BLQ-likeobservations


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,NewZealand

    office:+64(9)923-6730 mobile:NZ+64(21)46 23 53

email: n.holf...@auckland.ac.nzhttp://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 assumptionsand

    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.



    ICON plc made the following annotations.

------------------------------------------------------------------------------

    This e-mail transmission may contain confidential or legally

privileged information that is intended only for the individualor

    entity named in the e-mail address. If you are not the intended
    recipient, you are hereby notified that any disclosure, copying,
    distribution, or reliance upon the contents of this e-mail is

strictly prohibited. If you have received this e-mailtransmissionin error, please reply to the sender, so that ICON plc canarrange

    for proper delivery, and then please delete the message.

    Thank You,

    ICON plc
    South County Business Park
    Leopardstown
    Dublin 18
    Ireland
    Registered number: 145835

Re: [NMusers] PRED for BLQ-like observations

Reply via email to