jag009
★★★

NJ,
2013-05-17 00:15
(4376 d 17:31 ago)

Posting: # 10595
Views: 7,686
 

 Interesting Data from HVD study [Study As­sess­ment]

Hi everyone,

I am back with some more interesting data from a 3-period 2-treatment SD partial replicate study.

Out of academic curiosity, I analyzed the data (T vs 2xR) using the HVD SAS code from FDA's progesterone guidance to compute both RASBE (Proc GLM) and ABE (Proc Mixed) for 3 parameters. Here are the results for ln(AUCt). I also (back) computed the intra-subject CV ABE's 90% CI using PowerTost (Thanks Helmut :-)).

RASBE (Within sub SD of R > 0.294)
T/R Ratio  95% Upper Bnd    Within-Sub SD of R  Within-Sub var of R
110.49 %     -0.068367              0.37848             0.14325 


ABE
T/R Ratio%    90% CI        Intra-sub CV%
110.15      101.84-119.14     28.08%


Anyone smells something fishy here? sWR is greater than the RASBE criteria and yet intra-CV from ABE is less than 30%

Here is the data. (Sequence 1 = ABB, 2=BAB, 3=BBA)
Order = Subject, Sequence, Period, Treatment, ln(AUCt)

1 BAB 2 A 8.526364803
2 BBA 3 A 8.901327473
3 ABB 1 A 9.153578468
4 BAB 2 A 9.130386469
5 ABB 1 A 8.486726767
6 BBA 3 A 9.98972066
7 BBA 3 A 9.56024076
8 BAB 2 A 10.64495896
9 ABB 1 A 8.832284476
10 ABB 1 A 8.481898601
11 BBA 3 A 9.194738899
12 BAB 2 A 8.860335987
14 BBA 3 A 10.67923567
15 ABB 1 A 9.4955436
17 ABB 1 A 9.652140174
18 BAB 2 A 8.573445917
19 BAB 2 A 10.30715187
20 BBA 3 A 9.082060651
21 ABB 1 A 9.169269492
22 BAB 2 A 8.418482296
23 BBA 3 A 9.338015651
24 ABB 1 A 9.821022589
25 ABB 1 A 9.582700852
26 BAB 2 A 9.223865888
27 BBA 3 A 9.126999088
28 ABB 1 A 7.929657495
29 BAB 2 A 10.91749854
30 BBA 3 A 9.21363145
31 BBA 3 A 9.128995926
32 BAB 2 A 8.357795269
33 ABB 1 A 9.328466282
34 ABB 1 A 8.630376866
35 BBA 3 A 9.710710911
36 BAB 2 A 9.30272783
37 ABB 1 A 9.321031743
38 BBA 3 A 9.286129987
41 BAB 2 A 9.781225903
42 BBA 3 A 8.1607148
43 BAB 2 A 8.576749384
45 ABB 1 A 8.976525459
46 ABB 1 A 9.15652052
47 BBA 3 A 9.188639298
48 BAB 2 A 9.190315302
49 BBA 3 A 9.795318653
50 ABB 1 A 9.094317549
51 BAB 2 A 9.391310766
52 ABB 1 A 9.666499735
54 BBA 3 A 9.583939029
55 BAB 2 A 9.567490903
57 BBA 3 A 9.25718932
58 BBA 3 A 9.162218884
60 ABB 1 A 10.21590309
1 BAB 1 B 8.128370428
1 BAB 3 B 9.232100885
2 BBA 1 B 8.913664375
2 BBA 2 B 8.694680247
3 ABB 2 B 8.712547946
3 ABB 3 B 9.049999305
4 BAB 1 B 9.389423441
4 BAB 3 B 8.437263661
5 ABB 2 B 7.927401919
5 ABB 3 B 7.371860296
6 BBA 1 B 8.984416334
6 BBA 2 B 9.872628729
7 BBA 1 B 9.137144
7 BBA 2 B 9.651882989
8 BAB 1 B 10.40810379
8 BAB 3 B 10.40664461
9 ABB 2 B 9.159555685
9 ABB 3 B 9.238137818
10 ABB 2 B 8.100759144
10 ABB 3 B 8.507708352
11 BBA 1 B 9.136908986
11 BBA 2 B 9.174733298
12 BAB 1 B 9.069308003
12 BAB 3 B 8.537458261
14 BBA 1 B 10.44572858
14 BBA 2 B 10.0967258
15 ABB 2 B 10.01642415
15 ABB 3 B 9.739416183
16 BBA 1 B 9.969207781
16 BBA 2 B 9.736936328
17 ABB 2 B 9.012349449
17 ABB 3 B 9.306178322
18 BAB 1 B 9.293136578
18 BAB 3 B 8.625187855
19 BAB 1 B 9.372302406
19 BAB 3 B 9.864295271
20 BBA 1 B 9.295328094
20 BBA 2 B 9.324642155
21 ABB 2 B 10.08151921
21 ABB 3 B 10.005803
22 BAB 1 B 8.452870114
22 BAB 3 B 8.193471283
23 BBA 1 B 8.950218861
23 BBA 2 B 8.977336871
24 ABB 2 B 10.31081978
24 ABB 3 B 10.21149531
25 ABB 2 B 9.08623425
25 ABB 3 B 9.191435496
26 BAB 1 B 9.034482759
26 BAB 3 B 9.334309125
27 BBA 1 B 9.033644123
27 BBA 2 B 9.123255829
28 ABB 2 B 7.808661067
28 ABB 3 B 8.738043555
29 BAB 1 B 10.95621305
29 BAB 3 B 10.57611899
30 BBA 1 B 9.150339274
30 BBA 2 B 9.404113443
31 BBA 1 B 8.918796988
31 BBA 2 B 8.423870815
32 BAB 1 B 8.06601163
32 BAB 3 B 8.006084194
33 ABB 2 B 9.098076975
33 ABB 3 B 9.433090406
34 ABB 2 B 8.946951873
34 ABB 3 B 8.649585611
35 BBA 1 B 9.457030435
35 BBA 2 B 8.995962663
36 BAB 1 B 8.462264666
36 BAB 3 B 8.809359694
37 ABB 2 B 9.19471442
37 ABB 3 B 9.314370783
38 BBA 1 B 9.141800791
38 BBA 2 B 9.634033601
41 BAB 1 B 8.671999142
41 BAB 3 B 9.626654087
42 BBA 1 B 8.031307629
42 BBA 2 B 8.597653658
43 BAB 1 B 9.186942463
43 BAB 3 B 8.344736813
44 BBA 1 B 9.755382826
44 BBA 2 B 9.678213671
45 ABB 2 B 9.39361947
45 ABB 3 B 8.857977973
46 ABB 2 B 9.176185478
46 ABB 3 B 9.267847386
47 BBA 1 B 8.898346208
47 BBA 2 B 9.222175065
48 BAB 1 B 9.065841398
48 BAB 3 B 9.330146959
49 BBA 1 B 9.839313018
49 BBA 2 B 9.044184602
50 ABB 2 B 9.462267435
50 ABB 3 B 9.26260943
51 BAB 1 B 9.273340053
51 BAB 3 B 10.3761868
52 ABB 2 B 9.665386633
52 ABB 3 B 10.01370072
54 BBA 1 B 8.985289378
54 BBA 2 B 8.859758116
55 BAB 1 B 9.331189192
55 BAB 3 B 9.577132564
57 BBA 1 B 8.988994828
57 BBA 2 B 8.888606944
58 BBA 1 B 9.09638413
58 BBA 2 B 8.769625373
60 ABB 2 B 10.85349463
60 ABB 3 B 9.224646746


Thanks
John


Edit: Category changed. [Helmut]
Helmut
★★★
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Homepage
Vienna, Austria,
2013-05-17 04:03
(4376 d 13:44 ago)

@ jag009
Posting: # 10596
Views: 6,178
 

 Detlew?

Hi John!

❝ RASBE (Within sub SD of R > 0.294)


PHX6.3 [image]

Note that from ilat you not only get the PE but also the 90% CI:
102.11–119.55
from s²WR → CVWR 39.24%

❝ ABE

T/R Ratio%    90% CI        Intra-sub CV%

110.15      101.84-119.14     28.08%


PE and CI. [image]
I get a s²WR of 0.139466 (PHX’ terminology: Var(Period*Formulation*Subject)_21) → CVWR 38.69%
Have a look at s²WT. Do you believe in this value? I don’t. Stupid design.

❝ I also (back) computed the intra-subject CV ABE's 90% CI using PowerTost


100*CVfromCI(lower=1.0184, upper=1.1914, n=52, design="2x3x3", robust=TRUE)
28.08115

100*CVfromCI(lower=1.0211, upper=1.1955, n=52, design="2x3x3")
28.51869

:confused:

❝ Anyone smells something fishy here?


Strange. From the ABE model I get a CVWR which is pretty close to the one from RSABE. I think we have to wait for Detlew returning from his vacation in three weeks.


BTW, update PowerTOST to the latest version 1.1-03 (published 2013-05-03). See the NEWS.

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

Berlin, Germany,
2013-05-20 19:28
(4372 d 22:19 ago)

@ Helmut
Posting: # 10606
Views: 5,293
 

 What is the question?

Boys!

From my vacation: What is your problem :confused:?

CVfromCI() gives you the CV for the difference T vs. R.
This is some pooled value of the intra-subject variances of T and R 1).
So don't expect to get a value comparable to s2wR!


1) R.J. McNally
Tests for Individual and Population Bioequivalence Using 3-Period Crossover Designs
online here.
gives in the context of appropriate intra-subject contrasts (aka progesterone guidance):
s2I=(s2D + s2wT + s2wR/2)
where s2I is the variance of the difference T-R used for calculating the 90% CI, s2D is the subject-by-formulation interaction, s2wT and s2wR are the intra-subject variabilities of Test or Reference, respectively.

Since you didn't provide me s2wT try it by your own assuming s2D=0 which in many cases could be reasonably assumed for the partial replicate design.
Remember our discussion on specifying compound symmetry in the FDA Proc Mixed code.

Regards,

Detlew
Helmut
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Homepage
Vienna, Austria,
2013-05-20 20:17
(4372 d 21:29 ago)

@ d_labes
Posting: # 10607
Views: 5,281
 

 Answer: forget the partial replicate!

Daddy!

❝ From my vacation:


Do I smell some signs and symptoms of forum-addiction?

CVfromCI() gives you the CV for the difference T vs. R.

❝ This is some pooled value of the intra-subject variances of T and R 1).


Yep.

❝ So don't expect to get a value comparable to s2wR!


OK, OK. Childish boyish.

s2I=(s2D + s2wT + s2wR/2)

❝ where s2I is the variance of the difference T-R used for calculating the 90% CI, s2D is the subject-by-formulation interaction, s2wT and s2wR are the intra-subject variabilities of Test or Reference, respectively.


❝ Since you didn't provide me s2wT try it by your own assuming s2D=0 which in many cases could be reasonably assumed for the partial replicate design.

❝ Remember our discussion on specifying compound symmetry in the FDA Proc Mixed code.


Yessir. PHX gives me a standard error of the difference (FDA’s ABE code) of 0.0468069; s²WR 0.139466 and s²WT 0.0153728 [sic]. Not negligible S×F of 0.166035. As we know SAS will spit out different values for s²WT and the S×F. Stupid enough with John’s data no warning. If I ignore the S×F I get 29.805% for the pooled CVW – close to PowerTOST.
For completeness results of different parameterizations of the variance structure in PHX:
                                          s²WR      s²WT
Banded No-Diagonal Factor Analytic (f=2)  0.139466  0.0153728
(= FDA’s)
Compound Symmetry                         0.139466  0.0833300
Heterogenous Compound Symmetry            0.139466  0.2073849


Enjoy your vacation! :smoke:

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Helmut Schütz
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jag009
★★★

NJ,
2013-06-04 18:04
(4357 d 23:43 ago)

@ d_labes
Posting: # 10726
Views: 5,054
 

 What is the question?

Hi Detlew,

Let me irritate you a bit this morning :-) :waving: :-P

❝ Boys!


❝ From my vacation: What is your problem :confused:?


CVfromCI() gives you the CV for the difference T vs. R.

❝ This is some pooled value of the intra-subject variances of T and R 1).

❝ So don't expect to get a value comparable to s2wR!


If the Intra-CV derived from the pool'd variance is higher/lower than the intra-CV derived from the S2wR, then could one suggest that the difference is attributed to the test formulation (meaning test has larger or smaller variability)?

See some interesting data below. I ran Proc Mixed (FDA progesterone HVD SAS code) to obtain the reference residual variance and computed the corresponding intra-cv. I then used R to back-calculate the intra-cv from the 90% CI generated by Proc Mixed (first column data).
Formulation 1                  
         Pool'd Var      Ref      Ref      
         Intra CV %      Res Var  Intra-CV%   Δ Intra-CV(Pool-Ref)
Cmax        64.94        0.3040   59.60           5.33
AUCt        74.18        0.3006   59.22           14.96
               
Formulaton 2                  
         Pool'd Var      Ref      Ref      
         Intra CV %      Res Var  Intra-CV%   Δ Intra-CV(Pool-Ref)
Cmax        87.25        0.3268      62.17        25.08
AUCt        68.08        0.2641      54.98        13.10


Thanks
John
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