Babe_Ruth ☆ USA, 20180713 21:36 (1288 d 00:38 ago) (edited by Babe_Ruth on 20180713 22:19) Posting: # 19053 Views: 6,520 

I noticed something peculiar with how WNL (currently using v 6.3) calculates partial areas where BQL is imputed with 0 for samples after Tlast. Let's say my partial area to be calculated is AUC 024hr. Tlast is 12h, and every sample taken after 12h was BQL (16, 24, 48, 72 hr). I've noticed that in the 024hr partial area calculation, there are differences between imputing BQL with 0 and setting it as no value. When I set BQL to "no value," then it uses the rules stated in documentation: WNL rules for partial areas are stated here. Most notably: "If ... end time falls after the last numeric observation and λz is not estimable, the partial area will not be calculated." Requiring λz suggests that WNL does not default to another calculation method in case loglinear isn't available. However, when I set BQL to 0, it uses a lineartrapezoidal rule: (Clast + 0)*(T16  Tlast) Nowhere in the documentation does it say that this was the plan. In summary, when I set BQL to 0, calculation method for partial area changes and the values slightly differ. Is this intended? Is this normal practice? In general, the differences between the two methods of calculation is less than 1% Edit: Please follow the Forum’s Policy. Category changed; see also this post #1. [Helmut] 
ElMaestro ★★★ Denmark, 20180713 22:25 (1287 d 23:49 ago) @ Babe_Ruth Posting: # 19054 Views: 5,922 

Hi Babe_Ruth, » When I set BQL to "no value," then it (blah) » » However, when I set BQL to 0, it uses a lineartrapezoidal rule: (Clast + 0)*(T16  Tlast) » Nowhere in the documentation does it say that this was the plan. Do you mean it uses AUC_{partial}=0.5*(Clast + 0)*(T16  Tlast) ? If yes, then this is expected behaviour: Remember that you distinguish between BLQ, missing and a zero. If you set it to zero then it means you tell WNL to believe that the value is really zero in contrast to not measured. Thus, it was quantifiable so now the last quantifiable value is no longer at t=12 but at t=16. The residual area will naturally also be zero, so the extrapolated area is zero percent. I'd say you are within expectations and specifications. — Pass or fail! ElMaestro 
Helmut ★★★ Vienna, Austria, 20180713 23:28 (1287 d 22:47 ago) @ Babe_Ruth Posting: # 19058 Views: 5,957 

Hi Babe_Ruth, » […] WNL (currently using v 6.3) … Your version is four releases behind the current one (v8.1). High time to update. » I've noticed that in the 024hr partial area calculation, there are differences between imputing BQL with 0 and setting it as no value. As expected. » When I set BQL to "no value," then it uses the rules stated in documentation: WNL rules for partial areas are stated here. Most notably: "If ... end time falls after the last numeric observation and λz is not estimable, the partial area will not be calculated." Requiring λz suggests that WNL does not default to another calculation method in case loglinear isn't available. Correct (note that this post referred to v7.0 of 2016). » However, when I set BQL to 0, it uses a lineartrapezoidal rule: (Clast + 0)*(T16  Tlast) Also correct. » Nowhere in the documentation does it say that this was the plan. See the last bullet point of the linked post:
» In summary, when I set BQL to 0, calculation method for partial area changes and the values slightly differ. Is this intended? As designed and explained by ElMaestro above. » Is this normal practice? Bad practice to force BQLs after t_{max} to zero. I have seen many “rules” (e.g., first BQL to BQL/√2 or BQL/2, keep subsequent ones at BQL, whatsoever…). IMHO, that’s all crap. AFAIK, Martin Wolfsegger and Alexander Bauer are working on a NCAmethod dealing with terminal BQLs. In the meantime I suggest to keep BQLs as they are. — Diftor heh smusma 🖖 Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Babe_Ruth ☆ USA, 20180716 15:02 (1285 d 07:13 ago) (edited by Babe_Ruth on 20180716 15:12) @ Helmut Posting: # 19066 Views: 5,775 

Thank you Helmut! and everybody else. You are correct, I just doublechecked; the documentation in v6.3 is missing the clarification for usage of linear trapezoidal rule if BQL imputed with "0" after Tlast. This is what sparked my initial question of whether this was an intended behavior within WNL or not. » Bad practice to force BQLs after tmax to zero What about for sparse sampling methods? If there are 3 samples/time point, wouldn't we want to use 3 values for the calculation of the mean concentration? In which case imputing BQL concentrations with a value of 0 or close to 0 would be more favorable than not including the value altogether? Sorry if my questions seem trivial! I went to Pharmacy school, and there was only 12 classes on PK, nothing indepth. I've just started in this industry. Right now I'm writing TK reports and Phase I/II stuff and I'm interested in learning more about what I'm doing. Browsing these forums in my spare time really helps me see where others are in environment of the Ba/Be world :) Searching old topics have answered most of the questions I have had, which is super helpful. 
Helmut ★★★ Vienna, Austria, 20180716 16:02 (1285 d 06:12 ago) @ Babe_Ruth Posting: # 19067 Views: 6,019 

Hi Babe_Ruth, » » Bad practice to force BQLs after tmax to zero » » What about for sparse sampling methods? Sparse sampling is another cup of tea. Sounds trivial but actually isn’t. » If there are 3 samples/time point, wouldn't we want to use 3 values for the calculation of the mean concentration? In which case imputing BQL concentrations with a value of 0 or close to 0 would be more favorable than not including the value altogether? Some ideas:
» […] I'm interested in learning more about what I'm doing. Basic research is what I’m doing when I don’t know what I’m doing. Wernher von Braun » Browsing these forums in my spare time really helps me see where others are in environment of the Ba/Be world :) Searching old topics have answered most of the questions I have had, which is super helpful. Maybe you can convince your employer to browse the forum in your payed time…
— Diftor heh smusma 🖖 Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
martin ★★ Austria, 20180716 20:03 (1285 d 02:11 ago) @ Helmut Posting: # 19071 Views: 5,783 

Dear all, I am happy to share my thoughts regarding handling of values BLQ in sparse sampling design: 1) In such cases I would recommend using a modeling approach using M3 method of Beal for handling values BLQ. a. For serial sampling designs (i.e. only one sample per subject): this is just a straightforward modeling exercise (i.e. no random effects) including model selection techniques / approaches b. For a batch design (more than one sample per subject): this would require a NLME modeling approach where it’s tricky to include Beal’s M3 but possible (I think Alex did this also in SAS ) 2) If you have to stick with NCA the following heuristic approach may be useful. Lets’ assume there are n time points: t_{1} < t_{2} < t_{3} < t_{i} < … < t_{n}. At each time point there are k samples where the first value BLQ is observed at time point t_{j} < t_{n} a. At time point t_{j}: set all individual values BLQ to zero and calculate the mean at this time Point t_{j} i. If mean <BLQ omit this and all subsequent time points ii. If mean > BLQ find adequate imputations for individual BLQ values iii. Adequate imputations for individual values BLQ can be for example derived by fitting a loglinear regression on previous sample time points (e.g. based on time points t_{j3}, t_{j2}, t_{j1} < t_{j}) and use the corresponding predictions at time point t_{j}. This requires some thoughts regarding adequate selection of time points and likely a linear mixed model in case of batch design. Please note also that this Approach is valid only on the premise of linear PK (e.g. no concentration dependent clearance). Handling of values BLQ at the next time point t_{j+1} could be derived subsequently on a similar approach. Please be aware that in case of more than one value BLQ at time point t_{j}, the above imputation impacts the total variability of concentration at this time point and likely adding some variability on the individual predicted values should be advantages (e.g. as sensitivity analysis). Best regards & hope this helps Martin 
martin ★★ Austria, 20180716 20:43 (1285 d 01:31 ago) @ Helmut Posting: # 19072 Views: 5,740 

Dear Helmut, » […] IMHO, that’s all crap. AFAIK, Martin Wolfsegger and Alexander Bauer are working on a NCAmethod dealing with terminal BQLs […] Yes this is correct and we have already all the maths available. However, due to some lack of resources/time this project has slowed down. However, if some forum members would have some interest in generating a corresponding manuscript they may contact me. We would just need some simulation illustrating the performance in reasonable settings where generation corresponding scenarios turned out beeing rather complex (we thought about using Beals' M3 as competitor) best regards Martin 
mittyri ★★ Russia, 20180713 23:31 (1287 d 22:44 ago) @ Babe_Ruth Posting: # 19059 Views: 5,871 

Hi Babe_Ruth, » However, when I set BQL to 0, it uses a lineartrapezoidal rule: (Clast + 0)*(T16  Tlast) well... let me try to cite it again If a start or end time falls within the range of the data but does not coincide with an observed data point, then a linear or logarithmic interpolation is done to estimate the corresponding Y, according to the AUC Calculation method selected in the NCA Options. (See “NCA Options tab” on page 42.) Note that logarithmic interpolation is overridden by linear interpolation in the case of a nonpositive endpoint. A question: is 0 a positive endpoint? PS: nice to see you are using good oldie 6.3 (decennary next year) — Kind regards, Mittyri 
Helmut ★★★ Vienna, Austria, 20180713 23:58 (1287 d 22:16 ago) @ mittyri Posting: # 19060 Views: 5,879 

Hi mittyri, » A question: » is 0 a positive endpoint? Nope. 0 is by definition neither positive nor negative.* sgn(x < 0) = –1 x = sgn(x)·x Logarithms are defined only for ℝ^{>0}.
— Diftor heh smusma 🖖 Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Babe_Ruth ☆ USA, 20180716 14:49 (1285 d 07:26 ago) @ mittyri Posting: # 19064 Views: 5,772 

» Note that logarithmic interpolation is overridden by linear interpolation in the case of a nonpositive endpoint. » A question: » is 0 a [non]positive endpoint? 0 is nonpositive, but the original BQLs after Tlast is probably positive. Seems like I shouldn't be substituting BQL as 0 then. » PS: nice to see you are using good oldie 6.3 (decennary next year) We're in the process of upgrading to 8.1, haha. Many new fancy functions! A lot more expensive licensure too... I'll miss the floating license discount :P 