Bioequivalence and Bioavailability Forum • Cross-over 3x6 WNL x SAS

Maura
☆

2010-09-02 19:09
(4984 d 02:49 ago)

Posting: # 5876
Views: 5,816

Cross-over 3x6 WNL x SAS [Software]

I'm trying to get the same results with SAS, for the WinNonlin output, for a cross-over design 3x6 (Chow & Liu, page 321, PURICH's data), without success.
Someone tell me how to get the same results with SAS code?
Following the data, the SAS program and output, and the WinNonlin output.

Subj    Per     SEQ     Droga   asc     Carry   lnasc

1       1       RTS     1       5.68    1       1.736951

2       1       RTS     1       3.6     1       1.280934

3       1       SRT     2       3.55    1       1.266948

4       1       SRT     2       7.31    1       1.989243

5       1       TSR     3       6.59    1       1.885553

6       1       TSR     3       9.68    1       2.270062

7       1       STR     2       4.63    1       1.532557

8       1       STR     2       8.75    1       2.169054

9       1       TRS     3       7.25    1       1.981001

10      1       TRS     3       5       1       1.609438

11      1       RST     1       4.63    1       1.532557

12      1       RST     1       3.87    1       1.353255

1       2       RTS     3       4.21    1       1.437463

2       2       RTS     3       5.01    1       1.611436

3       2       SRT     1       5.07    2       1.623341

4       2       SRT     1       7.42    2       2.004179

5       2       TSR     2       7.72    3       2.043814

6       2       TSR     2       8.91    3       2.187174

7       2       STR     3       7.23    2       1.978239

8       2       STR     3       7.59    2       2.026832

9       2       TRS     1       7.88    3       2.064328

10      2       TRS     1       7.84    3       2.059239

11      2       RST     2       6.77    1       1.912501

12      2       RST     2       7.62    1       2.030776

1       3       RTS     2       6.83    3       1.921325

2       3       RTS     2       5.78    3       1.754404

3       3       SRT     3       4.49    1       1.501853

4       3       SRT     3       7.86    1       2.061787

5       3       TSR     1       7.26    2       1.98238

6       3       TSR     1       9.04    2       2.201659

7       3       STR     1       5.06    3       1.621366

8       3       STR     1       4.82    3       1.572774

9       3       TRS     2       9.02    1       2.199444

10      3       TRS     2       7.79    1       2.052841

11      3       RST     3       5.72    2       1.743969

12      3       RST     3       6.74    2       1.90806

WinNonlin output:


Partial Tests of Model Effects

              Hypothesis    Numer_DF    Denom_DF      F_stat     P_value

------------------------------------------------------------------------

                int            1           6       335.277        0.0000

                seq            5           6.27      1.66382      0.2711

                droga          2          18         3.69067      0.0454

                Per            2          18         3.28399      0.0608

                Carry          2          18         1.21341      0.3204

SAS Program:


PROC GLM DATA=purich;

CLASS seq subj per droga carry;

MODEL lnauc =  droga per seq subj(seq) carry  /SS3;

RANDOM subj(seq)/test;

RUN;

QUIT;

SAS Output:

The GLM Procedure

Tests of Hypotheses for Mixed Model Analysis of Variance



Dependent Variable: lnauc



Source                      DF     Type III SS     Mean Square    F Value    Pr > F



Droga                        2        0.230110        0.115055       3.44    0.0543

Per                          2        0.085202        0.042601       1.27    0.3037

Subj(SEQ)                    6        0.702524        0.117087       3.50    0.0179

Carrytest                    2        0.081128        0.040564       1.21    0.3204



Error: MS(Error)            18        0.601883        0.033438





Source                      DF     Type III SS     Mean Square    F Value    Pr > F



SEQ                          5        0.874041        0.174808       1.58    0.2896



Error                   6.3004        0.695535        0.110395

Error: 0.92*MS(Subj(SEQ)) + 0.08*MS(Error)

Mainly the period effect is very different!
Thanks and sorry about my English!!

Edit: Category changed. Please don't use tabulators in you post (see here on how to use BBCodes) - use the Preview before posting. [Helmut]

d_labes
★★★

Berlin, Germany,
2010-09-03 10:58
(4983 d 11:01 ago)

@ Maura
Posting: # 5879
Views: 4,782

WNL partial F vs. SAS type III F

Post reply

Dear Maura,

I don't own WNL therefore I can't verify your WNL results.
But from the form of output I guess that you have done a mixed model analysis in WNL?

Then the appropriate SAS code will be:


Proc mixed data=maura;

  class seq subj per droga carry;

  model lnasc=seq per droga carry/DDFM=satterth;

  random subj(seq);

run;

This gives among the output:

...

                   The Mixed Procedure



                   Covariance Parameter

                       Estimates



                 Cov Parm      Estimate



                  Subj(SEQ)      0.02788

                  Residual       0.03344

...

             Type 3 Tests of Fixed Effects



                   Num     Den

     Effect         DF      DF    F Value    Pr > F



     Droga           2      18       3.44    0.0543

     Per             2      18       1.27    0.3037

     SEQ             5    6.32       1.56    0.2956

     Carry           2      18       1.21    0.3204

This is very close to your results with Proc GLM, as I had expected.

Thus I can't figure out why WNL gives distinct F-tests.
Check your model specifications and data thoroughly.

Maybe that WNL partial F-tests do not correspond to SAS type III tests? Any of the WNL owners out there with an opinion?

❝ Thanks and sorry about my English!!

(emphasis by me) Welcome to the club. :-D

—
Regards,

Detlew

Helmut
★★★

Vienna, Austria,
2010-09-03 13:13
(4983 d 08:45 ago)

@ d_labes
Posting: # 5880
Views: 5,025

WNL partial F vs. SAS type III F

Post reply

Dear D. Labes & Maura,

❝ This gives among the [SAS Proc mixed] output:

❝ ...

❝ The Mixed Procedure

❝

❝ Covariance Parameter

❝ Estimates

❝

❝ Cov Parm Estimate

❝

❝ Subj(SEQ) 0.02788

❝ Residual 0.03344

❝ ...

❝ Type 3 Tests of Fixed Effects

❝

❝ Num Den

❝ Effect DF DF F Value Pr > F

❝

❝ Droga 2 18 3.44 0.0543

❝ Per 2 18 1.27 0.3037

❝ SEQ 5 6.32 1.56 0.2956

❝ Carry 2 18 1.21 0.3204

❝ This is very close to your results with Proc GLM, as I had expected.

❝

❝ Thus I can't figure out why WNL gives distinct F-tests.

❝ Check your model specifications and data thoroughly.

OK, here my results (Phoenix/WinNonlin 6.1):

Model Specification and User Settings

       Dependent variable : lnAUC

                Transform : Data already ln-transformed

              Fixed terms : int+Sequence+Droga+Period+Carry

    Random/repeated terms : Sequence*Subject



Final variance parameter estimates:

    Var(Sequence*Subject)    0.0278831

            Var(Residual)    0.0334379

          Intersubject CV    0.168153

          Intrasubject CV    0.1844



     REML log(likelihood)      2.96255

 -2* REML log(likelihood)     -5.92511

 Akaike Information Crit.     22.0749

   Schwarz Bayesian Crit.     38.5676



Partial Tests of Model Effects

              Hypothesis    Numer_DF    Denom_DF      F_stat     P_value

------------------------------------------------------------------------

                     int           1        7.78     920.601      0.0000

                Sequence           5        6.31     1.55832      0.2957

                   Droga           2          18     3.44086      0.0543

                  Period           2          18     1.27404      0.3037

                   Carry           2          18     1.21312      0.3204



Partial Sum of Squares

              Hypothesis          DF          SS          MS      F_stat     P_value

------------------------------------------------------------------------------------

                Sequence           5           2         0.4   0.0852022      1.2740

        Sequence*Subject        6.31     4.04403    0.640933     19.1678      0.0000

                   Droga           2     0.23011    0.115055     3.44086      0.0543

                  Period           2   0.0852022   0.0426011     1.27404      0.3037

                   Carry           2   0.0852022   0.0426011     1.27404      0.3037

                   Error          18    0.601883   0.0334379

❝ Maybe that WNL partial F-tests do not correspond to SAS type III tests?

They are almost (!) the same. ;-)

❝ Any of the WNL owners out there with an opinion?

I would say wrong coding. The model should be specified with:
Fixed Effects Sequence+Droga+Period+Carry
Variance Structure / Random 1 Subject(Sequence) Type Variance Components

Chow/Liu reported carryover effects at p=0.32 and further results (3^rd ed. 2009, Tables 10.3.15/16, p322):

Carryover   R      T      S

  Yes      5.67   7.24   6.30

  No       6.01   7.06   6.45



Comparison  Carryover       90% CI

T vs R        Yes      107.20%, 134.41%

              No       104.75%, 129.92%

S vs R        Yes       94.47%, 119.68%

              No        92.62%, 119.79%

T vs S        Yes      101.63%, 129.83%

              No        97.54%, 122.72%

I followed Maura's coding here; R=solution (R), T=domestic tablet (T₁), S=European tablet (T₂). According to footnote (a): Calculations were based upon [...] an estimate of solution formulation mean which is 5.97 (??) in the presence of carryover effects and is 6.01 in the absence of carryover effects.

I got:

Carryover   R      T      S

  Yes      5.77   7.16   6.22

  No       5.77   6.83   6.26



Comparison  Carryover       90% CI

T vs R        Yes      107.35%, 143.40%

              No       103.95%, 134.86%

S vs R        Yes       93.30%, 124.63%

              No        95.29%, 123.62%

No idea whether the LSM of the reference in Chow/Liu contains another typo (5.67 ↔ 5.97) - and which value they have actually used in calculating the 90% CI.

@Maura: Where did you get the coding of carryover from?

—
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes

d_labes
★★★

Berlin, Germany,
2010-09-03 14:10
(4983 d 07:49 ago)

@ Helmut
Posting: # 5881
Views: 4,770

WNL almost the same as SAS

Post reply

Dear Helmut!

❝ OK, here my results (Phoenix/WinNonlin 6.1):

❝ ...

❝ They are almost (!) the same. ;-)

Very fine

❝ Chow/Liu reported carryover effects at p=0.32 and further results

❝ (3^rd ed. 2009, Tables 10.3.15/16, p322):

❝ Carryover R T S

❝ Yes 5.67 7.24 6.30

❝ No 6.01 7.06 6.45

❝ ...

From the values and a short look into the book it seems they have analyzed the AUC values un-transformed! Not a very good idea with respect to nearly all guidances around the world :no:

.

@Maura: I agree with Helmut. There is a coding error in your carry-over factor. In the first period there is no carry-over possible.
BTW: I would not take a model with carry-over if no very strong arguments are present that such an effect could have occured. An sufficient wash-out period should have avoided that.
If not the simple first order carry-over model is not an efficient tool to deal with.
See
Stephen Senn
"Cross-over Trials in Clinical Research"
Chapter 10
Second edition
Wiley, Chichester, 2002

—
Regards,

Detlew

Maura
☆

2010-09-03 16:07
(4983 d 05:51 ago)

@ d_labes
Posting: # 5883
Views: 4,806

WNL almost the same as SAS

Post reply

Dear all,

First I am very thank you for help!!
Where did I get the coding of carryover from? This was removed from the forum itself. I found the encoding of an example of a book (C5300.zip):

/***SAS code for examples in Chapter 4 of                              ***/

/*** Bioequivalence and Statistics in Clinical Pharmacology,           ***/

/*** by Scott Patterson and Byron Jones,***/

/*** Chapman and Hall/CRC Press: Boca Raton, London and New York, 2005

In example 4.5 the data is arranged in the same way. I create the column “Carry” based on this example.

Those results from WNL was a friend who showed me, because I don't have the software. The results achieved through the SAS I get well.
I am very happy to have achieved these results with the help of you, but what I really need is to estimate the effect of "carryover" with one degree of freedom (ANOVA in Chow & Liu page 366 - second edition), when this same model is used to drug interaction (with x alone), and so I would not know how to create the column "Carry".
Recalling that in Brazil, ANVISA is criticizing this design, so we are trying to estimate the carryover effect and determining its significance, trying to justify the design. ANVISA wants it done a study for bioequivalence between "A + I" and "A" and another for "A + I" and "I".
Does anyone know how to do this parameterization??!

Thank you all.

Edit: Full quote removed. Please delete anything from the text of the original poster which is not necessary in understanding your answer; see also this post! [Helmut]