Missing sample(s) [Regulatives / Guidelines]
welcome to the BEBA-Forum!
❝ I have been scouring the relevant EMA/FDA guidance but haven’t come across anything too useful in relation to assessing the impact of missing samples in a bioequivalence study.
Correct. A weak point of a guideline which was written in order to serve as a kind of “cookbook”.
❝ During one of the study periods a protocol non-compliance has resulted in the 480 min time point not being available for 2 out of 22 subjects.
❝ Given where the 480 h time point lies in the profile, my instinct tells me that the missing samples should have minimal/negligible impact on the study objectives (i.e. to test for bioequivalence) and should not introduce an unacceptable amount of bias into the estimation of AUCt for the 2 subjects in question.
I agree with what your ‘instinct’ tells you.
❝ However, I would like to check if there are any guidelines/best practices etc that reinforce my ‘instinct’?
Which trapezoidal method did you state in the protocol? With the linear-up/logarithmic-down trapezoidal the impact of a missing sample in the elimination phase will be negligible. With the (IMHO outdated) linear trapezoidal you will get a small positive bias (i.e., AUC overestimated). See also this rather lengthy thread.
I’m not aware of any current guideline recommending a particular method. The WHO’s GL (2006) stated “The method of calculating AUC-values should be specified. In general AUC should be calculated using the linear/log trapezoidal integration method.” The second sentence was dropped in the current (2015) version for unfathomable reasons.
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- Missing data analyses Astea 2016-04-11 10:33 [Regulatives / Guidelines]
- Data imputation Helmut 2016-04-11 13:13
- Data imputation Astea 2016-04-11 17:53
- Missing data analyses Hutchy_7 2016-04-12 13:38
- Missing sample(s)Helmut 2016-04-12 14:06
- Missing sample(s) Hutchy_7 2016-04-12 15:29
- Missing sample(s)Helmut 2016-04-12 14:06
- Data imputation Helmut 2016-04-11 13:13