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[NMusers] RE: BLQ Data

From: Vong, Camille <>
Date: Fri, 2 Oct 2015 16:16:38 +0000

Hi Brady,

I think there are three main articles you can refer to in terms of using M3=
 method for BLQ data:

Likelihood based approaches to handling data below the quantification limit=
 using NONMEM VI.

Impact of low percentage of data below the quantification limit on paramete=
r estimates of pharmacokinetic models.

Handling data below the limit of quantification in mixed effect models.

As a general rule of thumb, most people tend to ignore(=exclude) the data=
points (not the whole ID) if BLQ data are less than 10%.
However, I think it is important to look at where these BLQ data occur main=
ly to know if they can bring more info into your model and sometimes,
having these extra BLQ data left in the analysis and using the M3 method ca=
n be better for parameter estimation. Nonetheless beware that M3 method doe=
s not always help in terms of run convergence (covariance step).

Hope it helps!

Best regards,

From: [] On=
 Behalf Of Moffett, Brady S.
Sent: Friday, October 2, 2015 10:23 AM
Subject: [NMusers] BLQ Data

I am working with TDM data and am wondering when to use the M3 method for d=
ealing with BLQ data, or, when to just exclude data?

For instance: If I have <1% BLQ data in a large dataset (~1000 patients), =
should I just exclude those patients/values? If I just have one patient wi=
th one value BLQ, is it worth using the M3 method for that one patient? Is=
 there a breakpoint for which using these methods does/does not make a diff=

Thanks in advance...

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Received on Fri Oct 02 2015 - 12:16:38 EDT

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