Missing data analyses [Regulatives / Guidelines]
Impeccable timing as have just had a very similar situation arise myself that I would be extremely grateful for any input on:
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.
The scenario is:
4 way cross BE study; test vs ref in fed and fasted states
N = 22 HVs
Tmax ~60 mins
T1/2 ~120 min
Sampling: 0, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 105, 120, 180, 240, 360, 480 and 720 mins
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.
However, I would like to check if there are any guidelines/best practices etc that reinforce my ‘instinct’?
Any thoughts most welcome!
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.
The scenario is:
4 way cross BE study; test vs ref in fed and fasted states
N = 22 HVs
Tmax ~60 mins
T1/2 ~120 min
Sampling: 0, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 105, 120, 180, 240, 360, 480 and 720 mins
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.
However, I would like to check if there are any guidelines/best practices etc that reinforce my ‘instinct’?
Any thoughts most welcome!
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 analysesHutchy_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