MGR
★    

India,
2021-09-30 09:35
(423 d 02:10 ago)

Posting: # 22605
Views: 1,268
 

 Inter-subject variability in Full replicate design [RSABE / ABEL]

Dear All,

Need help on formula/procedure to find out the Intersubject Variability for a Full replicate design using SAS.

Based on the Program given in the progesterone guideline below:

PROC MIXED
 data=pk;
 CLASSES SEQ SUBJ PER TRT;
 MODEL LAUCT = SEQ PER TRT/ DDFM=SATTERTH;
 RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G;
 REPEATED/GRP=TRT SUB=SUBJ;
 ESTIMATE 'T vs. R' TRT 1 -1/CL ALPHA=0.1;
 ods output Estimates=unsc1;
 title1 'unscaled BE 90% CI - guidance version';
 title2 'AUCt';


As there is no subj(seq) in the random statement, I am not able to calculate the inter-subject variabilities for test and reference treatments. Please help me with this calculation.

But when I use the proc varcomp procedure in SAS, I am able to generate the Variabilities (Inter and Intra) for test and reference treatments. My doubt is that whether it is acceptable by FDA regulatory?

Thanks in Advance,

Regards,
MGR
ElMaestro
★★★

Denmark,
2021-09-30 16:04
(422 d 19:41 ago)

@ MGR
Posting: # 22606
Views: 1,101
 

 Inter-subject variability in Full replicate design

Hi MGR,

❝ RANDOM TRT/TYPE=FA0(2) SUB=SUBJ G;


Once you've run the model, the G matrix holds your between-subject variability.
I am not a SAS user, so the syntax for printing and processing G is outside my area of competence (like pretty much anything is).

Pass or fail!
ElMaestro
Helmut
★★★
avatar
Homepage
Vienna, Austria,
2021-09-30 17:25
(422 d 18:20 ago)

@ MGR
Posting: # 22607
Views: 1,205
 

 Inter-subject variability in Full replicate design

Hi MGR,

like ElMaestro I’m not a SASian and my knowledge is limited.

❝ […] I am not able to calculate the inter-subject variabilities for test and reference treatments. Please help me with this calculation.


With the EMA’s example ‘Data set I’ (download CSV) you should get sumfink like:

        Covariance Parameter Estimates
Cov Parm     Subject    Group    Estimate
FA(1,1)      SUBJ                0.8530
FA(2,1)      SUBJ                0.8284
FA(2,2)      SUBJ                8.339e-07
Residual     SUBJ       TRT R    0.2021
Residual     SUBJ       TRT T    0.1174


In Phoenix/WinNonlin slightly different terms.

Final variance parameter estimates:
           lambda(1,1)_11  0.852995
           lambda(1,2)_11  0.828407
           lambda(2,2)_11  8.33919e-007
Var(PER*TRT*SUBJ)_21       0.202118
Var(PER*TRT*SUBJ)_22       0.117394


The first two lines give \(\small{\widehat{s_\textrm{bR}^2}}\) and \(\small{\widehat{s_\textrm{bT}^2}}\) and the last two \(\small{\widehat{s_\textrm{wR}^2}}\) and \(\small{\widehat{s_\textrm{wT}^2}}\). Ignore the third, which is the Subject-by-Formulation Interaction. Then as usual \(\small{100\sqrt{\exp \left ( \widehat{s_{\ldots}^2} \right )-1}}\).
Here \(\small{CV_\textrm{bR}=116.0\%,\;CV_\textrm{bT}=113.6\%,\;CV_\textrm{wR}=47.3\%,\;CV_\textrm{wT}=35.3\%}\).

As ElMaestro wrote, you can get the estimated between-subject variances also from Col1 of the estimated G matrix, where the 1st Row is for R and 2nd for T.

❝ But when I use the proc varcomp procedure in SAS, I am able to generate the Variabilities (Inter and Intra) for test and reference treatments.


Out of curiosity: Do they are agree with the results of Proc Mixed as outlined above?

❝ My doubt is that whether it is acceptable by FDA regulatory?


The between-subject variabilities are not required for RSABE (in the FDA’s Summary Table 3B you have to give only the within-subject variance and standard deviation of the reference).

[image]

For ABE (Table 3A) variances are not required at all.

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