SP
☆

India,
2019-07-29 14:31

Posting: # 20465
Views: 389

## suggest suitable Sequence for Reference replicate and Two Different Test? [Design Issues]

Hello Helmut/All,

Can anyone help me with your experience or suggestions. Which sequence should i prefer for crossover study design to Reference Replicate and Two Different Test product (T1 and T2).

Thank You!!!!

Helmut
★★★

Vienna, Austria,
2019-07-29 17:25

@ SP
Posting: # 20466
Views: 348

## Not sure whether it makes sense

Hi SP,

» Can anyone help me with your experience or suggestions. Which sequence should i prefer for crossover study design to Reference Replicate and Two Different Test product (T1 and T2).

I have seen this one: T1RT2R | RT1RT2
Evaluation was done after excluding the respective other T-treatment, which gave two partial replicates with incomplete blocks (the pooled analysis will lead to limbo for unequal variances):
T1R• R | RT1R•  and
• RT2R | R• RT2
As usual with partial replicates, the FDA’s covariance specification (in SAS-lingo FA0(2)) did not converge for PK metrics with sWR <0.294 (no RSABE). Furthermore, one has to assume lacking period effects, since neither R nor the two test are administered in all periods. The evaluation was not easy. Since nobody knows whether or not there were true period effects, the outcome was doubtful at least. I would not go there.

Maybe it is better to opt for a modified Williams’ design T1T2RR | T2RT1R | RT1RT2 | RRT2T1 which gives
T1• RR | • RT1R | RT1R•  | RR• T1 and
• T2RR | T2R• R | R• RT2 | RRT2•
At least balanced for T1 and T2 (once in every period).
However, we have R twice in periods 1&2 and only once in periods 3&4.

If you really want to have everything balanced, you might end up with even more sequences. The FDA argues against more than two sequences (confounded effects) anyway. Duno. Never have been there.

I would perform two separate three period full replicate studies:
T1RT1 | RT1R and T2RT2 | RT2R
No statistical pitfalls. As a bonus you get also the intra-subject variabilities of T1 and T2. If T1/R and T2/R are similar, select the one with lower variability for the pivotal study (full replicate, please – the partial replicate is crap).

Cheers,
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. ☼
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abhimanyu
☆

Banglore,
2019-08-03 13:54

@ Helmut
Posting: # 20469
Views: 212

## Not sure whether it makes sense

Hi Helmut/SP,

» Maybe it is better to opt for a modified Williams’ design T1T2RR | T2RT1R | RT1RT2 | RRT2T1 which gives
» T1• RR | • RT1R | RT1R•  | RR• T1 and
» • T2RR | T2R• R | R• RT2 | RRT2•
» At least balanced for T1 and T2 (once in every period).
» However, we have R twice in periods 1&2 and only once in periods 3&4.

If we consider modified Williams’ design with this sequence T1T2RR | T2RT1R | RT1RT2 | RRT2T1 Then,

What would be change in Proc GlM / Proc Mixed for Calculate Swr, 95% Upper bound (Scaled), and 90% CI (Unscaled).

Abhimanyu
d_labes
★★★

Berlin, Germany,
2019-08-03 19:35

@ abhimanyu
Posting: # 20470
Views: 198

## Not sure whether it makes sense

Dear Abhimanyu,

» ...
» What would be change in Proc GlM / Proc Mixed for Calculate Swr, 95% Upper bound (Scaled), and 90% CI (Unscaled).

Nothing since the effects in GLM or mixed are not dependent from the used sequences, only the number of levels of the effect "sequence" or "period" changes. But this has not to be specified in the code (SAS or others). It will be taken automatically from the dataset you use.
Thus you have:
  log(PK) ~ period + sequence + subject(sequence) - for calculation of sWR
  log(PK) ~ treatment + period + sequence + subject(sequence) - for 90% CI
in R lingo.
In SAS you have to modify the model statement in Proc GLM accordingly.

Regards,

Detlew
abhimanyu
☆

Banglore,
2019-08-05 09:27

@ d_labes
Posting: # 20471
Views: 177

## Not sure whether it makes sense

Dear Detlew,

»   log(PK) ~ period + sequence + subject(sequence) - for calculation of sWR
»   log(PK) ~ treatment + period + sequence + subject(sequence) - for 90% CI

Thank you for providing valuable information.

Moreover, how to validate answers? Kindly suggest available method and References for the same.

Thanking you

Regards,
Abhimanyu
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