mittyri ★★ Russia, 20190316 14:41 Posting: # 20038 Views: 625 

Dear All, some time ago I was pleased to be invited on the session with Roger Jelliffe. Some cites from one of the lectures: Labs have been used to presenting a result only to generate a number, with a percent error, for evaluation by themselves or a clinician. I've also seen some similar opinion on nmusers maillist (may be it was Nick Holford). My question is are there any steps forward in that direction? Even in analytical methodology (say QC samples): isn't possible to handle that values (as they are) for example for the mean evaluation for some level of QC sample? PS: sorry, my bioanalytics skills are far away from acceptable level — Kind regards, Mittyri 
Helmut ★★★ Vienna, Austria, 20190316 15:39 @ mittyri Posting: # 20039 Views: 587 

Hi Mittyri, » some time ago I was pleased to be invited on the session with Roger Jelliffe. Congratulations! Roger is a guy of strong opinions. When David Bourne’s PK/PDList was still active, Roger regularly ranted about the LLOQ (examples). In PK modeling nobody simply ignores BLOQs. We still have no method dealing with “BQLs” in NCA (Martin ). Essentially Roger is absolutely right (speaking also from my background in analytical chemistry). BTW, on a similar note the best weighting scheme in calibration is 1/s^{2} – and not 1/x, 1/x^{2}, 1/y, 1/y^{2}. They are all arbitrary and lack any justification. OK, in between those lines of the EMA’s BMV guideline … A relationship which can simply and adequately describe the response of the instrument with regard to the concentration of analyte should be applied. … it seems that it is recommended not only to assess calibration functions themselves (chromatography: linear, quadratic, …; LBA: 4, 5parameter logistic, …) but also different weighting schemes (based on the backcalculated concentrations’ accuracy & precision). Rarely done.Of course, 1/s^{2} requires at least duplicates (even after rejecting a measurement). In our lab we had this procedure: Validate the method with 1/s^{2} and also the weighting scheme which gave the 2^{nd} best outcome. Sometimes sponsors didn’t like triplicate standards (money, money). Then – if we ended up with a singlet – we switched to the other weighting scheme. Regulators didn’t like that (“subjects are not treated equally”). » My question is are there any steps forward in that direction? I strongly doubt it. » Even in analytical methodology (say QC samples): isn't possible to handle that values (as they are) for example for the mean evaluation for some level of QC sample? Not sure what you mean here. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
ElMaestro ★★★ Denmark, 20190316 22:35 @ Helmut Posting: # 20041 Views: 552 

Ladies and gentlemen, I present to you the Philadelphia variation: The smartest and most empirical solution to a very, very small (and mainly theoretical?) problem. Let us apply weights 1/C^z in such a fashion that the sum of relative absolute residuals is smallest. Idea borrowed from ISR. And it may make good sense to look at the relative magnitude of residuals since this is what runs pass criteria are based on. Therefore, here is something to play around with:
Conc=c(1, 2, 4, 8, 20, 50, 100, 150, 200, 300) Note: the fit is not very good, r squared is rather low, but that is besides the point. You get my drift, I hope. z then defines the weighting scheme which can be said to give the smallest overall amount of percentwise prediction error on the calibration curve. Not a bad place to start. You can modify the idea as you please, perhaps you want to define ObjF via the Ratio and not via the Conc, or perhaps you want to return another type of objective altogether. Various things that don't work include but aren't limited to abs sum of residuals, sum of residuals, and more. Thank me later. — if (3) 4 Best regards, ElMaestro “(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures.” New York Times (ed.), June 9, 2018. 
Helmut ★★★ Vienna, Austria, 20190316 23:05 @ ElMaestro Posting: # 20042 Views: 548 

Hi ElMaestro, » […] The smartest and most empirical solution to a very, very small (and mainly theoretical?) problem. Theoretical? Yes. Really relevant? Very, very rarely. Changing the weighting for all subjects to 1/y^{2} (we got two deficiency letters) altered the 90% CI in the second decimal place. » Let us apply weights 1/C^z in such a fashion that () Congratulations for an obvious solution (aka, reinventing the wheel). See what Ohlbe wrote here and there. PS: Typo? Didn’t you want Ratio[1]=0.05303 ?— Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
ElMaestro ★★★ Denmark, 20190319 08:26 @ Helmut Posting: # 20049 Views: 330 

Hi Hötzi, » Congratulations for an obvious solution (aka, reinventing the wheel). See what Ohlbe wrote here and there. Is the proposal really old and is it really obvious? I see there was in the past a proposal or two about 1/(Conc^z) where z is not an integer, but I am not sure if there was ever anyone who: 1. Defined an objective function which seeks to minimize a relevant measure of departure from predictability (that same predictability which maps into the criteria of guidelines). 2. Showed the existence of a minimum of that function. Novelty here is not the existence of a funky value of z, but the way of finding it, the nature of it. — if (3) 4 Best regards, ElMaestro “(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures.” New York Times (ed.), June 9, 2018. 
Helmut ★★★ Vienna, Austria, 20190317 01:56 @ ElMaestro Posting: # 20043 Views: 543 

Hi ElMaestro, played with an example of a study I have on my desk. Chiral GC/MS, quadratic model, w=1/x^{2}. ObjF1 < function(x) { I got:
Akaike & Bayesian Information Critera (smaller is better) Hey, yours with w=1/x^{1.3355} is the winner! Duno why the ICs of 1/s_{y}² are that bad. Coding error? The accuracy looks fine. Try a plot: plot(Conc, Ratio, type="n", log="xy", las=1) — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
mittyri ★★ Russia, 20190318 22:20 @ Helmut Posting: # 20047 Views: 375 

Hi Helmut, Thank you so much for the detailed answer! » » Even in analytical methodology (say QC samples): isn't possible to handle that values (as they are) for example for the mean evaluation for some level of QC sample? » Not sure what you mean here. Sorry for incomplete/incorrect question. Say ADA, getting cutoff point (IV B FDA) What would be a best tactics for cutoff point selection? Say the data of healthy volunteers is {100, BLOQ, BLOQ} Edit: Guidance linked. [Helmut] — Kind regards, Mittyri 
Helmut ★★★ Vienna, Austria, 20190319 01:34 @ mittyri Posting: # 20048 Views: 363 

Hi mittyri, » Say ADA, getting cutoff point (IV B FDA) » What would be a best tactics for cutoff point selection? » Say the data of healthy volunteers is {100, BLOQ, BLOQ} No idea. That’s a minefield and beyond my competence. I prefer these Adas: #1, #2. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 
Ohlbe ★★★ France, 20190317 14:32 @ mittyri Posting: # 20044 Views: 497 

Dear Mittyri, » Labs have NOT been used to having their data FITTED using modern quantitative modeling methods which require one to evaluate credibility of a measurement correctly. That is the problem. Labs have been used to CV% only. CV% is simply not suitable for today’s modern quantitative modeling methods. » They invent the LLOQ. LLOQ is their ILLUSION! » NO NEED for this! » [So need to know, or have a good estimate, of the SD of every serum level. » Labs always get SD anyway, to get the CV%. » Then, Var = SD^{2} Mmmm. It is true that bioanalysts don't know how their data will be processed later. And they just don't care. But PK scientists should also realise that the SD is not in any way a constant feature of a bioanalytical method. It can vary over time. From one run to the next (ion source getting dirty, sleepy or sloppy analyst etc.). And from one instrument to the next, should you have several involved in your study. Not only that: precision is just one of the problems. Accuracy is another. Where does it come into Roger's picture ? The LLOQ is the lowest concentration you can measure with an acceptable precision and accuracy. Problem is, you can't really have a reliable estimate of accuracy below the LLOQ. Question: where do you get your SD from ? Withinrun ? Betweenrun ? Most importantly, from how many replicates ? In his response Helmut mentions SD calculated from 2 or 3 replicates. Sorry Helmut, but I would consider any such value as meaningless. To me, that would be the same thing as running a ttest or Chisquare on 5 values. » My question is are there any steps forward in that direction? Looking at the draft M10 guidance: nope. — Regards Ohlbe 
nobody nothing 20190318 08:14 @ Ohlbe Posting: # 20045 Views: 435 

» In his response Helmut mentions SD calculated from 2 or 3 replicates. Sorry Helmut, but I would consider any such value as meaningless. Exactly. Trash in trash out. SD is not erwartungstreu. Start with n=20+... — Kindest regards, nobody 
Helmut ★★★ Vienna, Austria, 20190318 11:19 @ nobody Posting: # 20046 Views: 423 

Hi nobody, Ohlbe and everybody, » » In his response Helmut mentions SD calculated from 2 or 3 replicates. Sorry Helmut, but I would consider any such value as meaningless. » » Exactly. Trash in trash out. SD is not erwartungstreu. Start with n=20+... I stand corrected – you are both right. Is a stupid idea. — Cheers, Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. ☼ Science Quotes 