Group effect commonly not relevant [Software]
Hi Zan,
first I agree with what ElMaestro wrote. Two groups are no issue generally (same protocol, same site, not too large interval [months!] between groups).
Maybe you are interested in this thread and some quotes from the FDA. I don’t have WinNonlin any more (consider upgrading to Phoenix; release 6.4 is expected this summer). My setup in Phoenix / WinNonlin 6.3:
IMHO, a 1:1 split is not optimal. Let’s assume the worst, i.e., for any wacky reasons FDA insist on model I and there is a significant Treatment-by-Group Interaction. No pooling; go with one of the groups. In your design both have a size of 27. Let’s assume a T/R of 0.95, CV 30.5%, and target power 90%. You end up with 54 subjects (power 90.38%). BTW, your 1:1 split results in imbalanced sequences in both groups. Let’s further assume that in both groups the T/R-ratio and CV come out exactly as planned and you have no drop-outs. Power will be just 60.97% in both. If both groups are equally sized the questions also arises on which one you will base the assessment of BE. The nicer one?
I would suggest to split subjects in such a way that one of the groups is the maximum capacity of the clinical site. Which power can we expect in the groups?
first I agree with what ElMaestro wrote. Two groups are no issue generally (same protocol, same site, not too large interval [months!] between groups).
Maybe you are interested in this thread and some quotes from the FDA. I don’t have WinNonlin any more (consider upgrading to Phoenix; release 6.4 is expected this summer). My setup in Phoenix / WinNonlin 6.3:
- Group model I:
fixed: Group+Sequence+Sequence(Group)+Period(Group)+Treatment+Treatment×Group
random: Subject(Sequence×Group)
If the Treatment-by-Group term is not significant (p ≥0.1) this term can be dropped from the model, proceeding to Group Model II.
If the Treatment-by-Group term is significant (p <0.1), FDA’s Division of Bioequivalence requests that equivalence be demonstrated in one of the groups, provided that the group meets minimum requirements for a complete BE study (i.e., 12).
- Group model II:
fixed: Group+Sequence+Sequence(Group)+Period(Group)+Treatment
random: Subject(Sequence×Group)
- Conventional model:
fixed: Sequence+Period+Treatment
random: Subject(Sequence)
If all conditions stated in FDA’s letters are fulfilled (most cases), that’s the way to go.
❝ I am working on a 2x2 crossover BE study with large N (N=54). Due to limited clinical capacity the site separated subjects into two dosing groups (N=27 each).
IMHO, a 1:1 split is not optimal. Let’s assume the worst, i.e., for any wacky reasons FDA insist on model I and there is a significant Treatment-by-Group Interaction. No pooling; go with one of the groups. In your design both have a size of 27. Let’s assume a T/R of 0.95, CV 30.5%, and target power 90%. You end up with 54 subjects (power 90.38%). BTW, your 1:1 split results in imbalanced sequences in both groups. Let’s further assume that in both groups the T/R-ratio and CV come out exactly as planned and you have no drop-outs. Power will be just 60.97% in both. If both groups are equally sized the questions also arises on which one you will base the assessment of BE. The nicer one?

I would suggest to split subjects in such a way that one of the groups is the maximum capacity of the clinical site. Which power can we expect in the groups?
G1 % power G2 % power
────────────────────────
27 60.97 27 60.97
28 63.13 26 58.63
30 66.92 24 53.92
32 70.27 22 48.33
34 73.25 20 41.98
36 75.89 18 34.91
────────────────────────
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Complete thread:
- Phoenix WNL to handle 2x2 crossover study with multip group zan 2014-06-27 23:29
- Phoenix WNL to handle 2x2 crossover study with multip group ElMaestro 2014-06-28 23:23
- Group effect commonly not relevantHelmut 2014-06-30 16:55
- Group effect in 2x2 BE study zan 2014-06-30 19:18
- Group effect in 2x2 BE study ElMaestro 2014-06-30 20:36
- To pool or not to pool Helmut 2014-06-30 20:51
- To pool or not to pool zan 2014-06-30 21:02
- To pool or not to pool Helmut 2014-06-30 21:38
- To pool or not to pool zan 2014-06-30 21:46
- To pool or not to pool Helmut 2014-06-30 22:22
- To pool or not to pool zan 2014-07-01 01:15
- Partial vs. sequential tests in WNL Helmut 2014-07-01 12:26
- Partial vs. sequential tests in WNL zan 2014-07-01 18:03
- Loosing patience Helmut 2014-07-01 18:23
- Partial vs. sequential tests in WNL zan 2014-07-01 18:03
- Partial vs. sequential tests in WNL Helmut 2014-07-01 12:26
- To pool or not to pool zan 2014-07-01 01:15
- To pool or not to pool Helmut 2014-06-30 22:22
- To pool or not to pool ElMaestro 2014-06-30 22:11
- To pool or not to pool zan 2014-07-01 01:18
- To pool or not to pool zan 2014-07-02 19:56
- To pool or not to pool ElMaestro 2014-07-03 00:17
- To pool or not to pool zan 2014-07-03 00:36
- sequence- / period effect #666 Helmut 2014-07-03 10:05
- To pool or not to pool ElMaestro 2014-07-03 00:17
- To pool or not to pool zan 2014-06-30 21:46
- To pool or not to pool Helmut 2014-06-30 21:38
- To pool or not to pool zan 2014-06-30 21:02
- Group effect commonly not relevant AngusMcLean 2014-07-06 16:19
- Group effect commonly not relevant Helmut 2014-07-06 20:32
- Group effect commonly not relevant AngusMcLean 2014-07-06 22:52
- Group effect commonly not relevant Helmut 2014-07-06 23:57
- PHX: Parameter mapping AngusMcLean 2014-07-07 15:04
- PHX: Parameter mapping Helmut 2014-07-07 15:45
- PHX: Parameter mapping Shuanghe 2014-07-07 17:35
- Great hint! Helmut 2014-07-07 17:54
- PHX: Parameter mapping AngusMcLean 2014-07-07 20:49
- PHX: Parameter mapping AngusMcLean 2014-07-07 18:46
- PHX: Parameter mapping Shuanghe 2014-07-07 17:35
- PHX: Parameter mapping Helmut 2014-07-07 15:45
- PHX: Parameter mapping AngusMcLean 2014-07-07 15:04
- Group effect commonly not relevant Helmut 2014-07-06 23:57
- Group effect commonly not relevant AngusMcLean 2014-07-06 22:52
- Group effect commonly not relevant Helmut 2014-07-06 20:32
- Group effect in 2x2 BE study zan 2014-06-30 19:18