Data imputation [Regulatives / Guidelines]

posted by Helmut Homepage – Vienna, Austria, 2016-04-11 15:13 (3226 d 09:48 ago) – Posting: # 16183
Views: 5,031

Hi Astea,

❝ Recently I've received a letter from the Customer where it was pointed out that according to the planning regulatory documents we have to include missing data in analyses in a very specific way.


You posted in the category Regulatives / Guidelines. What do you mean by “planning regulatory documents”?

❝ For example in several cases the missing data from one volunteer in one period should be replaced be the mean arithmetic of the other's data.


That’s bizarre. Practically all regulatory documents point out that common PK metrics (except tmax) are assumed to follow a lognormal distribution. Hence, we apply a multiplicative model (log-transformation in order to obtain additive effects). Arithmetic mean is wrong.

❝ Of course this method has a right to exist.


Don’t think so.

❝ It was described in European Pharmacopeia 5.0 p.3.2.6 and in several articles, but it seems to me very strange to use this technic in bioequivalence data analyses. :confused:


The technical term is “imputation”. It is common in clinical studies if a patient drops out midcourse (i.e., Last-Observation-Carried-Forward – LOCF). Here it can be (!) conservative since in a superiority test the estimated mean difference will me smaller and if one assumes that the treatment performs better than placebo. But it is not that easy. ICH E9 states in Section 5.3:

Unfortunately, no universally applicable methods of handling missing values can be recommended.


I never ever have seen it in BE and for good reasons. If you impute the missing by the geometric (!) mean of the other subjects:If you want to work with an incomplete data set (i.e., missing period(s)) you can try a mixed effects-model. See this rather lengthy discussion of the issue.
BTW, the EMA’s GL wants only complete subjects (T and R) in simple crossovers and at least one period with each of T and R in replicate designs. Both the EMA’s and the FDA’s SAS-code for reference-scaling drop incomplete subjects.

Dif-tor heh smusma 🖖🏼 Довге життя Україна! [image]
Helmut Schütz
[image]

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

Complete thread:

UA Flag
Activity
 Admin contact
23,376 posts in 4,912 threads, 1,662 registered users;
113 visitors (0 registered, 113 guests [including 10 identified bots]).
Forum time: 00:02 CET (Europe/Vienna)

There are sadistic scientists who hurry to hunt down errors
instead of establishing the truth.    Marie Curie

The Bioequivalence and Bioavailability Forum is hosted by
BEBAC Ing. Helmut Schütz
HTML5