balakotu
★    

India,
2014-01-08 09:14
(3439 d 09:57 ago)

Posting: # 12142
Views: 14,019
 

 Replicate Study designs [Outliers]

Dear All,

We have small statistical problem in one BE partial replicate study data, and this study having 48 subjects data with this data BE acceptance criteria is not meeting due to two subject showing low concentrations

Subject I-Test has shown low concentration (1/10 times) when compared with Reference formulations (R1&R2).

Subject II-one Reference has shown low concentration (1/10 times) when compared with test & other Reference formulation.

If we are excluding these two subjects, variability observed is<30% and met the 90% CI.

If we are including these two subject, variability observed is >30% and not met the 95% bound.

So, how can we justify those two subjects data as outliers/anomalous and how to perform statistical analysis in such a case?

Please clarify


Edit: Category changed. [Helmut]
Dr_Dan
★★  

Germany,
2014-01-08 10:54
(3439 d 08:17 ago)

@ balakotu
Posting: # 12143
Views: 12,853
 

 Replicate Study designs

Dear balakotu
Unbiased assessment of results from randomised studies requires that all subjects are observed and treated according to the same rules. These rules should be independent from treatment or outcome. In consequence, the decision to exclude a subject from the statistical analysis must be made before bioanalysis. Exclusion of data cannot be accepted on the basis of statistical analysis or for pharmacokinetic reasons alone, because it is impossible to distinguish the formulation effects from other effects influencing the pharmacokinetics. Replicate designs are mostly used in case of highly variable drugs (CV%>30) in order to widen the acceptance range. If you exclude subjects with extreme values the variability decreases but who tells you that the data then obtained reflect reality? Which is the "true" variability, the one with subjects included or the one with subjects excluded? As long as you can not provide evidence that the subjects under discussion are true outliers you will not be able to exclude them. For the FDA it would be possible to perform an outlier study.
I hope this helps.
Kind regards
Dan

Kind regards and have a nice day
Dr_Dan
Mahesh M
★    

India,
2014-01-08 14:18
(3439 d 04:52 ago)

@ Dr_Dan
Posting: # 12145
Views: 12,855
 

 Replicate Study designs

Dear balakotu

I agree with Dr. Dan, if those two subjects data pass outliers test then only you exclude the subjects and in that condition you have to submit excluded and included PK analysis data to regulatory agency.
Regards
Mahesh M
Dr_Dan
★★  

Germany,
2014-01-08 16:24
(3439 d 02:47 ago)

@ Mahesh M
Posting: # 12149
Views: 12,866
 

 Replicate Study designs

Dear Mahesh M
Just for clarification: when I talked about outlier verification I did not mean a statistical test but rather a re-dose study (you administer test and reference in a cross-over design in the outlying subjects together with a certain number of other study participants). However this is only possible for FDA submissions. For EU submissions Ohlbe is right, the study failed.
Kind regards
Dan

Kind regards and have a nice day
Dr_Dan
jag009
★★★

NJ,
2014-01-08 16:33
(3439 d 02:38 ago)

@ Dr_Dan
Posting: # 12150
Views: 12,779
 

 Replicate Study designs

I agree with Dr. Dan if the study is for FDA submission.

John
Helmut
★★★
avatar
Homepage
Vienna, Austria,
2014-01-08 17:16
(3439 d 01:55 ago)

@ Dr_Dan
Posting: # 12151
Views: 13,205
 

 Re-testing

Hi Dan & all,

❝ […] but rather a re-dose study (you administer test and reference in a cross-over design in the outlying subjects together with a certain number of other study participants). However this is only possible for FDA submissions.


See FDA’s guidance, Section VII.C:

[…] deletion of outlier values is generally discouraged, particularly for nonreplicated designs. With replicated crossover designs, the retest character of these designs should indicate whether to delete an outlier value or not. Sponsors or applicants with these types of data sets may wish to review how to handle outliers with appropriate review staff.


I have strong doubts whether the FDA would accept a re-testing study following a replicate study. In Balakotu’s case Subject II might be excluded, but not Subject I. Don’t be tempted to try that without talking to the OGD’s review staff before – keep RTR in mind!
Only fully replicated 4-period studies (RTRT|TRTR) are “fool-proof”.

If you are interested in a statistical approach (not recommended for beginners):

Schall R, Endrényi L, Ring A. Residuals and Outliers in Replicate Design Crossover Studies. J Biopharm Stat. 2010;20(4):835–49. doi 10.1080/10543401003618876


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Ohlbe
★★★

France,
2014-01-08 15:24
(3439 d 03:47 ago)

@ balakotu
Posting: # 12146
Views: 12,810
 

 Replicate Study designs

Dear Balakotu,

❝ So, how can we justify those two subjects data as outliers/anomalous and how to perform statistical analysis in such a case?


For which authority ?

In the EMA guideline (§4.1.8.) the answer is clear:

Exclusion of data cannot be accepted on the basis of statistical analysis or for pharmacokinetic reasons alone, because it is impossible to distinguish the formulation effects from other effects influencing the pharmacokinetics.

The exceptions to this are:

1) A subject with lack of any measurable concentrations or only very low plasma concentrations for reference medicinal product. A subject is considered to have very low plasma concentrations if its AUC is less than 5% of reference medicinal product geometric mean AUC (which should be calculated without inclusion of data from the outlying subject). The exclusion of data due to this reason will only be accepted in exceptional cases and may question the validity of the trial.


So looking at your case, the conclusion for an EU submission is simple: the study fails.

Regards
Ohlbe
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