Re: Reporting and handling values below the limit of quantification

> On 2013/11/11 12:17, [email protected] wrote: > > > Hi Paolo, > > > > Considering 2A: > > > > The residual error model always should already account for a possible larger > > residual error at lower concentrations. I think a combined proportional and > > additive error model willfor this. If an additive component can't be estimated, > > my gut feeling tells me fixing the additive component to 1/2BLQ is reasonable. > > > > Cheers, > > Rob On 2013/11/09 06:55, Nick Holford wrote: > Paulo, > > I wish you luck in trying to do this. I also spend some time trying to persuade the people in your lab to do intelligent things with their measurements when I was in Cape Town. > > I suggest you might try looking at this: > http://holford.fmhs.auckland.ac.nz/docs/censored-observations-with-nonmem.pdf > > I discuss the FDA Guidance that is usually used by the chemical analysts to support their deliberate attempts to make our life difficult. > > Unfortunately this is largely an issue of belief not science. It is essentially impossible to win religious battles with wisdom. The usual strategy to win a religious war is with guns and bombs. I don't recommend that. But perhaps you might try drugs -- e.g. your excellent South African wine. > > In Auckland I was able to persuade one LC-MS chemical analyst to see the light and he reported his measurements honestly (including some negative concentration measurements). A complex PK model was published based on these truthful observations (Patel et al. 2011). > > Once you have honest observations I think it is much easier to decide how to model the residual error. The additive error component can then be a realistic description of assay background noise. > > Best wishes, > > Nick > > Patel K, Choy SS, Hicks KO, Melink TJ, Holford NH, Wilson WR. A combined pharmacokinetic model for the hypoxia-targeted prodrug PR-104A in humans, dogs, rats and mice predicts species differences in clearance and toxicity. Cancer Chemother Pharmacol. 2011;67(5):1145-55. > > On 7/11/2013 4:33 a.m., Paolo Denti wrote: > > > Dear all, > > I know I am opening a bit of a can of worms here, and one that has been > > opened before, but please bear with me.. > > > > We are trying to make our case with our analytical laboratory to > > convince them to release to us (pharmacometrics) the values below the > > limit of quantification (BLQ), which they normally define as the level > > below which they can't guarantee 20% CV on the measurement. > > > > So far, they have been quite reluctant, because they say that this would > > go against their SOPs, quality assurance policies, some FDA and EMA > > guidelines, and what not. However, after months of insisting, it seems > > like they may finally be open for discussion and asked us to present as > > much supporting evidence and experience from other labs as possible. > > > > Our main argument is that censoring BLQ values may be a reasonable > > policy when the data needs to be used for other purposes or by > > clinicians, but for us modelers it is a terrible waste of information, > > because we have tools to properly deal with the additional level of > > uncertainty, > > > > My first question to the group is then the following - Nick, I > > explicitly count on you for this one... :) > > 1. Can you suggest any literature/guidelines/references in support of > > our cause? > > a. Any literature clearly advocating for/supporting the release of the > > BLQ values for pharmacometric modelling. > > b. Any official guidelines providing/justifying an exception to the > > standard practice of censoring when the data is handled with modelling > > c. Any personal experience with your lab or the regulatory authority > > about this topic > > > > So far, I've found some previous threads here on NMUsers and the > > conclusion section in this paper: > > Byon W, Fletcher C V, Brundage RC. Impact of censoring data below an > > arbitrary quantification limit on structural model misspecification. J. > > Pharmacokinet. Pharmacodyn. 35: 101–16, 2008. > > > > The second question is about how to handle these values if we manage to > > get them (fingers crossed). > > The released data will have some actual values below the assay > > validation limit (that we can call "low precision"), and some that will > > be NA, because sometimes the mass-spec will not be able to identify a > > peak in the elution profile. > > > > 2. What error structure would you recommend to handle a dataset > > including uncensored BLQ values? > > a. Should one fix the additive component of the error to a fraction of > > the LLOQ (say 50%)? And if so, for all samples, even the ones above > > LLOQ, or only the BLQ ones? > > b. How would you handle the NAs? Would you impute 0? Impute the lowest > > value reported? Half of it? > > c. If you have a series of NAs to impute, would you retain only the > > first one and exclude the following, or would include them all? Would > > you have the proportional component of the error apply also to the > > imputed NAs or not? > > > > Any input and help is greatly appreciated! > > > > Greetings from Cape Town, > > Paolo > > > > -- > > ------------------------------------------------ > > Paolo Denti, PhD > > Pharmacometrics Group > > Division of Clinical Pharmacology > > Department of Medicine > > University of Cape Town > > > > K45 Old Main Building > > Groote Schuur Hospital > > Observatory, Cape Town > > 7925 South Africa > > phone: +27 21 404 7719 > > fax: +27 21 448 1989 > > email: [email protected] > > ------------------------------------------------ > > > > ________________________________ > > UNIVERSITY OF CAPE TOWN > > > > This e-mail is subject to the UCT ICT policies and e-mail disclaimer published on our website at http://www.uct.ac.za/about/policies/emaildisclaimer/ or obtainable from +27 21 650 9111. This e-mail is intended only for the person(s) to whom it is addressed. If the e-mail has reached you in error, please notify the author. If you are not the intended recipient of the e-mail you may not use, disclose, copy, redirect or print the content. If this e-mail is not related to the business of UCT it is sent by the sender in the sender's individual capacity. > > -- > 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:[email protected] > http://holford.fmhs.auckland.ac.nz/ > > Holford NHG. Disease progression and neuroscience. Journal of Pharmacokinetics > and Pharmacodynamics. > 2013;40:369-76 http://link.springer.com/article/10.1007/s10928-013-9316-2 > Holford N, Heo Y-A, Anderson B. A pharmacokinetic standard for babies and > adults. J Pharm Sci. > 2013: http://onlinelibrary.wiley.com/doi/10.1002/jps.23574/abstract > Holford N. A time to event tutorial for pharmacometricians. CPT:PSP. > 2013;2: http://www.nature.com/psp/journal/v2/n5/full/psp201318a.html > Holford NHG. Clinical pharmacology = disease progression + drug action. British > Journal of Clinical Pharmacology. > 2013: http://onlinelibrary.wiley.com/doi/10.1111/bcp.12170/abstract -- ------------------------------------------------ Paolo Denti, PhD Pharmacometrics Group Division of Clinical Pharmacology Department of Medicine University of Cape Town K45 Old Main Building Groote Schuur Hospital Observatory, Cape Town 7925 South Africa phone: +27 21 404 7719 fax: +27 21 448 1989 email: [email protected]