Bioequivalence and Bioavailability Forum • Phoenix WNL to handle 2x2 crossover study with multip group

zan
☆

US,
2014-06-28 01:29
(3947 d 08:02 ago)

Posting: # 13161
Views: 29,308

Phoenix WNL to handle 2x2 crossover study with multip group [Software]

Hi All,
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). I have come across several discussion threads in the forum regarding the use of SAS model to deal with this issue, however, I would like to see how is this modeled correctly in Phoenix Winnonlin 6.3 as I only have WNL available.
Per FDA guidance the model should reflect that the periods in the first group are different from the periods in the second group. I immediately have two thoughts about this:

is it acceptable to just assign 4 periods to the 4 dosing days? If so,
In the model specification: Treatment+Sequence+Period
and in the variance structure--Random effect: Subject(Sequence).
Is there any issue with this approach? It looks to me these periods are independent occasions, which might not really separate each two periods for the same group.
Can we still keep these 2 periods and add a Group term to these subjects (eg. Group 1 and Group 2)?. If so, in the model specification:
Treatment+Sequence+Period+Group
but in the variance structure, I dont know what is appropriate to be added in the Random effect field. Should it be Subject(Sequence*Group).

I wanted to make sure I choose the correct procedure in PHX Winnonlin so that when FDA asks whether we properly deal with the issue with multiple dosing groups.

Really appreciate for any help.

Zan

Edit: Category changed. [Helmut]

ElMaestro
★★★

Denmark,
2014-06-29 01:23
(3946 d 08:07 ago)

@ zan
Posting: # 13166
Views: 27,295

Phoenix WNL to handle 2x2 crossover study with multip group

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Hello Zan,

I don't speak WNL but:

❝ 1. is it acceptable to just assign 4 periods to the 4 dosing days? If so,

❝ In the model specification: Treatment+Sequence+Period

❝ and in the variance structure--Random effect: Subject(Sequence).

That would be a little untraditional with four period levels. But it can be done and it is a little like working with period in group. What's the title of your study? (If it is something like "A two-treatment, two-period, two-sequence bioequivalence study blah blah" then you almost have the answer right there).

❝ 2. Can we still keep these 2 periods and add a Group term to these subjects (eg. Group 1 and Group 2)?. If so, in the model specification:

❝ Treatment+Sequence+Period+Group

Yes, much better, this is what I would do.

❝ but in the variance structure, I dont know what is appropriate to be added in the Random effect field. Should it be Subject(Sequence*Group).

Oh here we go again: Depending on your data listing you can probably just write Subject.

—
Pass or fail!
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Helmut
★★★

Vienna, Austria,
2014-06-30 18:55
(3944 d 14:36 ago)

@ zan
Posting: # 13174
Views: 27,737

Group effect commonly not relevant

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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:

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.

Like any between-subject test the one for Treatment-by-Group is lacking power (therefore, testing at α 0.10). However, you could expect then a false-positive rate in 10% of studies!

❝ 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? :cherry picking:

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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zan
☆

US,
2014-06-30 21:18
(3944 d 12:13 ago)

@ Helmut
Posting: # 13175
Views: 27,216

Group effect in 2x2 BE study

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Thanks very much for the useful reply, ElMaestro and Helmut! Yes I am using Phoenix Winnonlin to work on this analysis. If there is a significant treatment*Group effect, is the overall (all subject) ratio (CI90%) still valid, or we have to adopt the ratio (CI90%) from separate groups?

Regarding FDA's requirement below (equivalence be demonstrated in one of the groups), do we have a link to the source of the letter? I am hoping to keep it as a reference for study files.

❝ 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).

Best regards
zan

ElMaestro
★★★

Denmark,
2014-06-30 22:36
(3944 d 10:55 ago)

@ zan
Posting: # 13176
Views: 27,187

Group effect in 2x2 BE study

Post reply

Hi Zan,

❝ Thanks very much for the useful reply, ElMaestro and Helmut! Yes I am using Phoenix Winnonlin to work on this analysis. If there is a significant treatment*Group effect, is the overall (all subject) ratio (CI90%) still valid, or we have to adopt the ratio (CI90%) from separate groups?

I personally find it very difficult to address a significant group x treatment interaction. To help visual interpretation you could plot the four effects in a bar diagram. A low p-value for group x treatment means you think the four bars all not of equal height. Where does that leave us?
ABE is all about the treatment performance in itself and not treatment in summer versus treatment in winter (the latter just to make it a little extreme, hope you get the general idea). Sure, if there is a pronounced difference in stability of T and R, respectively, and the two groups are well separated in time then we could observe group x treatment, but this is speculation and besides if such stability differences would exist they should be caught and handled well before any study is kicked off cf. GMP and GCP.
I am inclined to say a significant group x treatment should be considered a mere nuisance just like Conchita Wurst or nail fungus.

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Helmut
★★★

Vienna, Austria,
2014-06-30 22:51
(3944 d 10:40 ago)

@ zan
Posting: # 13177
Views: 27,072

To pool or not to pool

Post reply

Hi Zan,

❝ […] If there is a significant treatment*Group effect, is the overall (all subject) ratio (CI90%) still valid, or we have to adopt the ratio (CI90%) from separate groups?

If you pool groups you’ll end up with common estimates of between- and within-subject variances. If groups are different in their responses to the treatments you will not get pooled unbiased estimates. AFAIK, there is not corrective method. Theoretically – if you would know (!) the correlations between intra-/inter-subject variances, take the group sizes into account, :blahblah:

– maybe some fancy weighting is possible. But: Estimates of these effects are not accessible in a simple 2×2 cross-over. Too many questions asked to poor little data.

❝ Regarding FDA's requirement below (equivalence be demonstrated in one of the groups), do we have a link to the source of the letter? I am hoping to keep it as a reference for study files.

Nope. I have seen similar wordings in confidential letters (and Detlew as well). Most phrases were identical to the letter. Copy/paste at the FDA?

❝ ❝ 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.

At least a similar quote in this post. I’m not in the office; will check tomorrow whether the significance level (0.05 different to FDA’s 0.1) is not a typo.

Do you have any good reasons to walk this dirty road at all? Multi-site study or the like? A split due to logistic reasons is very (very) common in BE. I have limited experience with the FDA, but in 30+ years I have neither seen a single BE study in Europe including group term(s) nor heard of any assessor asking for one. All trouble I experienced came from MENA-countries & Gulf states.

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zan
☆

US,
2014-06-30 23:02
(3944 d 10:29 ago)

@ Helmut
Posting: # 13178
Views: 27,118

To pool or not to pool

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Thank you for all good comments (ElMaestro and Helmut)!

Helmut,
I just found a link to an FDA reviewer letter to a BE study where multiple groups were conducted, and one of the groups demonstrated a significant group by treatment effect. The criteira the reviewer cited was 0.1.

http://www.accessdata.fda.gov/drugsatfda_docs/anda/2008/077570Orig1s000BioeqR.pdf

Best regards

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

Helmut
★★★

Vienna, Austria,
2014-06-30 23:38
(3944 d 09:53 ago)

@ zan
Posting: # 13179
Views: 27,459

To pool or not to pool

Post reply

Hi Zan,

THX for the reference! With one week between groups I would never ever thought a millisecond of setting up a group model. Obviously this was also the approach of the applicant. In Table 9 (page 19) we read:

┌──────────────────────────┬──────────────────────────────────────┐

│ Do you agree or disagree │ Do not agree. Firm analyzed the data │

│ with firm’s decision?    │ as one group, the reviewer analyzed  │

│                          │ data as two separate groups.         │

└──────────────────────────┴──────────────────────────────────────┘

Without knowing the original data I will not comment on the reviewers comments. Do you think that she is aware of “false positives”?

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zan ☆ US, 2014-06-30 23:46 (3944 d 09:45 ago) @ Helmut Posting: # 13180 Views: 26,983	To pool or not to pool Post reply
	Hi Helmut, Was it due to significant effect observed for Group x Treatment that resulted in the reviewer's decision to run final analysis by separate groups (on Page 5)? Best Regards zan Edit: Full quote removed (again!). Please delete everything from the text of the original poster which is not necessary in understanding your answer; see also this post! [Helmut]

Helmut
★★★

Vienna, Austria,
2014-07-01 00:22
(3944 d 09:09 ago)

@ zan
Posting: # 13182
Views: 27,282

To pool or not to pool

Post reply

Hi Zan,

❝ Was it due to significant effect observed for Group x Treatment that resulted in the reviewer's decision to run final analysis by separate groups (on Page 5)?

Sure. The text contains a reference:

In control #98-392 (see attachment), it is stated that “if the Group-by-Treatment interaction is statistically significant (p<0.1), DBE requested that equivalence be demonstrated in one of the groups, provided that the group meets minimum requirements for a complete bioequivalence study”.

However, #98-392 is not attached. I failed to dig it out at the FDA (controlled correspondence not covered by FOI?). Note the wording almost identical to my post above.

Please no more TOFU in future posts. THX.

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zan ☆ US, 2014-07-01 03:15 (3944 d 06:16 ago) @ Helmut Posting: # 13183 Views: 27,063	To pool or not to pool Post reply
	Hi Helmut, The document #98-392 is hidden in page 52 of the PDF file (took me a while to dig it out). Also, in PHX winnonlin, should partial test or sequential test the best approach to look for all the stat test results (eg. Group, treatment, period effect)? I tend to go with partial test as it is tested independent of order but not sure if I am correct. zan

Helmut
★★★

Vienna, Austria,
2014-07-01 14:26
(3943 d 19:05 ago)

@ zan
Posting: # 13187
Views: 27,334

Partial vs. sequential tests in WNL

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Hi Zan,

❝ The document #98-392 is hidden in page 52 of the PDF file […].

It took the FDA until Sep 1999 to answer a letter received in Oct 1998. Note that this was well before the 2001 Stat. Guidance. Amazingly the letter deals with a one-week (!) washout and the same interval between groups.

┌───────────────┬──────────┬──────────┬──────────┬──────────┐

│ Dosing Scheme │   11/1   │   11/8   │   11/15  │   11/22  │

├───────────────┼──────────┼──────────┼──────────┼──────────┤

│       1       │  Group 1 │  Group 1 │  Group 2 │  Group 2 │

│               │ Period 1 │ Period 2 │ Period 1 │ Period 2 │

├───────────────┼──────────┼──────────┼──────────┼──────────┘

│       2       │  Group 1 │  Group 1 │          │

│               │ Period 1 │ Period 2 │          │

│               │          │  Group 2 │  Group 2 │

│               │          │ Period 1 │ Period 2 │

└───────────────┴──────────┴──────────┴──────────┘

It’s interesting that the FDA stated:

1. Both Dosing Schemes are acceptable to the Division of Bioequiva-
lence.

With the second scheme you’ll have the entire bunch of subjects at the clinical site on the second day. That’s bizarre; I don’t get it. If the CRO is large enough, why deal with two groups at all?

I would not bother about #1–8 and rather concentrate on

9. If ALL of the following criteria are met, it may not be necessary to
include Group-by-Treatment in the statistical model:

the clinical study takes place at one site;
all study subjects have been recruited from the same enrollment pool,
all of the subjects have similar demographics;
all enrolled subjects are randomly assigned to treatment groups at study outset.

In this latter case, the appropriate statistical model need include only the factors Sequence, Period, Treatment, and Subject (nested within Sequence).

❝ Also, in PHX winnonlin, should partial test or sequential test the best approach to look for all the stat test results (eg. Group, treatment, period effect)? I tend to go with partial test as it is tested independent of order but not sure if I am correct.

‘Partial Tests’ are expected to agree with SAS’ Type III LSMs in most of cases (whereas ‘Sequential Tests’ ≡ SAS’ Type I). See the “Phoenix User’s Guide” Table 17-13 (p448–50 = p478–80 of the PDF).

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zan
☆

US,
2014-07-01 20:03
(3943 d 13:28 ago)

@ Helmut
Posting: # 13196
Views: 26,974

Partial vs. sequential tests in WNL

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❝ I would not bother about #1–8 and rather concentrate on

❝ 9. If ALL of the following criteria are met, it may not be necessary to

❝ include Group-by-Treatment in the statistical model:

❝ ● the clinical study takes place at one site;

❝ ● all study subjects have been recruited from the same enrollment pool,

❝ ● all of the subjects have similar demographics;

❝ ● all enrolled subjects are randomly assigned to treatment groups at study outset.

❝ In this latter case, the appropriate statistical model need include only the factors Sequence, Period, Treatment, and Subject (nested within Sequence).

Hi Helmut,
On page 6 of the document (http://www.accessdata.fda.gov/drugsatfda_docs/anda/2008/077570Orig1s000BioeqR.pdf) we discussed above, reviewer provided the justification why the two dosing groups needed to be separated (looks stringent):

Although the subjects in the study were from the same geographic region and have the same demographic profiles, they were not enrolled in the study at the same time. The subjects enrolled in group 2 were screened after the beginning of the fasting study for group 1. There were 15 days in between the dosing of the two groups.
Therefore, individual statistical analysis is performed for each group.

zan

Helmut
★★★

Vienna, Austria,
2014-07-01 20:23
(3943 d 13:08 ago)

@ zan
Posting: # 13197
Views: 26,940

Loosing patience

Post reply

Hi Zan,

the company asked the FDA in October 1998 for a comment and – if I interpret the table correctly – planned the study for November. I’m too lazy to browse through the document, but I guess that sooner or later they gave up waiting and performed the study anyhow. Almost one year later the company received FDA’s answer. Too bad that they didn’t have a crystal ball (which would have told them to go with option #9).
As one of my friends use to say:

Don’t worry, it’s too late.

But we know better now.

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ElMaestro
★★★

Denmark,
2014-07-01 00:11
(3944 d 09:20 ago)

@ Helmut
Posting: # 13181
Views: 26,973

To pool or not to pool

Post reply

Hi Helmut and Zan,

❝ Without knowing the original data I will not comment on the reviewers comments. Do you think that she is aware of “false positives”?

Considering that the reviewer is Bing Li, I'd say the dossier had a very competent review.
However, the review is from 2005. That was around the time when ordinary sequence effects were proposed to be tested with 10% alpha and not considered nuisance. It might be the same phenomenon applied here to group which is also a between-subject term.
Today I think the policy has informally changed. As usual I could be wrong; at least I am not aware of any formalised guidance.

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zan ☆ US, 2014-07-01 03:18 (3944 d 06:13 ago) @ ElMaestro Posting: # 13184 Views: 26,992	To pool or not to pool Post reply
	In looking at the BE test results, should we all use 0.1 as significance level? Does FDA require level of 0.05 for these tests? Thanks, zan

zan ☆ US, 2014-07-02 21:56 (3942 d 11:34 ago) @ ElMaestro Posting: # 13202 Views: 26,843	To pool or not to pool Post reply
	I am still wondering does FDA have any guidance regarding what significant level is recommended (0.05 or 0.1) for assessing all effects. What if I observe a period or sequence effect at 0.06. zan

ElMaestro
★★★

Denmark,
2014-07-03 02:17
(3942 d 07:14 ago)

@ zan
Posting: # 13204
Views: 26,864

To pool or not to pool

Post reply

Hello Zan,

❝ I am still wondering does FDA have any guidance regarding what significant level is recommended (0.05 or 0.1) for assessing all effects. What if I observe a period or sequence effect at 0.06.

As mentioned above, I do not think there is any formal guidance. If you have a reason to analyse a factor at 0.05 then do that. If you have a reason to analyse it at 0.1 then do that. I can't give you the optimal reason or the right alpha as it could come down to the specifics associated with your product/API. It all makes little sense to discuss alpha if you are not going to react to significance anyway. So this discussion is more than just the choice of alpha, it is also about what to do with tests that are significant.
Do what you think is right, fair, ethical and decent and what your SOP tells you to do.
At the end I think the principal distinction of BE versus not BE is made on basis of the confidence interval so the decision is not directly associated to the P-values of the ANOVA (that's unless you are a Danish regulator but we'll leave it out of this discussion for now).

Bear in mind that in the ANOVA you are testing hypothesis of equality.
This stands in contrast to the null hypothesis we evaluate when we test for bioequivalence.
Therefore, to me most anova p-values (regardless of alphas) are of secondary importance. If your randomisation was not effective (all the fat guys ended up in seq TR and all the slim ones in RT) then you might well see a sequence effect. If your first period was in the summer and the second period was in the winter then you might see a period effect. Etc. It will not necessarily have much to do with product performance.

—
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ElMaestro

zan ☆ US, 2014-07-03 02:36 (3942 d 06:54 ago) @ ElMaestro Posting: # 13205 Views: 26,924	To pool or not to pool Post reply
	Thank you, ElMaestro. This makes sense to me. Looks like as long as the significant level is chosen consistently throughout the analysis. zan

Helmut
★★★

Vienna, Austria,
2014-07-03 12:05
(3941 d 21:26 ago)

@ zan
Posting: # 13208
Views: 26,903

sequence- / period effect #666

Post reply

zan,

❝ What if I observe a period or sequence effect …

though actual number might be lower, it feels like we had similar questions a hundred times. Please search the forum. You will find not only answers but a lot of references as well.

❝ … at 0.06.

0.05 < 0.06 < 0.10…

<irony>

The “Box and whiskers plot” was introduced* by John W. Tukey. He suggested the quartiles ±1.5× the interquartile range (IQR) as warning limits (aka “inner fences”) for “mild” outliers (and 3×IQR aka “outer fences” for “severe” ones).
At a conference he was asked “Why 1.5, Mr Tukey?” and replied “Well, that’s larger than one and smaller than two.”

</irony>

JW Tukey
Exploratory Data Analysis
Addison-Wesley Publishing Co., Reading, MA (1977)

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AngusMcLean
★★

USA,
2014-07-06 18:19
(3938 d 15:11 ago)

@ Helmut
Posting: # 13219
Views: 26,837

Group effect commonly not relevant

Post reply

❝ […] (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)

Helmut: I saw above post focusing on performing studies in a large number of subjects so it is convenient to split the subjects into 2 groups. I created a data set with two groups (2 way crossover study with 2 treatments and two periods and two sequences) to try out above code in Phoenix WinNonlin 6.3 (V6.4 will be available in August).

I tried to set up the model from above, but I found the program rejected the code I put it in (text turns red). I do not know what boxes to check to get the program to accept the code, which includes "Group".

Group+Sequence+Sequence(Group)+Period(Group)+Treatment+Treatment*Group

Please can you advise accordingly,

Angus

Helmut
★★★

Vienna, Austria,
2014-07-06 22:32
(3938 d 10:59 ago)

@ AngusMcLean
Posting: # 13221
Views: 26,841

Group effect commonly not relevant

Post reply

Hi Angus,

❝ I tried to set up the model from above, but I found the program rejected the code I put it in (text turns red). I do not know what boxes to check to get the program to accept the code, which includes "Group".

Sorry; Phoenix insists in Formulation, not Treatment. In the setup you have to map Group to Classification. Try:

fixed:  Group+Sequence+Sequence(Group)+Period(Group)+Formulation+Formulation*Group

random: Subject(Sequence*Group)

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AngusMcLean
★★

USA,
2014-07-07 00:52
(3938 d 08:39 ago)

@ Helmut
Posting: # 13222
Views: 26,798

Group effect commonly not relevant

Post reply

Hello Helmut: Yes; I did see that Formulation not Treatment later after lunch, but it still did not work. Then following your direction about Group being a classification variable (and including subject in model) I did get it to work.

Dependent hyothesis     NumDF Denomin     Fstat       p value

Ln(AUC)   int               1   64    11226.673       0

Ln(AUC)   Group             1   64        0.006028186 0.93835554

Ln(AUC)   Sequence          1   64        3.4513852   0.067800018

Ln(AUC)   Group*Sequence    1   64        0.000321727 0.9857451

Ln(AUC)   Group*Period      2   64        0.064946799 0.937179

Ln(AUC)   Formulation       1   64        0.36503556  0.54785867


Ln(AUC)   Formulation*Group 1   64        0.002630007 0.95925927

The formulation by group interaction p value was 0.95 for this composed data set.

Many thanks and also your sample size program in R works well: I have almost zero experience in R, but the reference you provided was easy to follow.

Here is the setup I used in Phoenix: Subject has to be mapped to get it to work (see link below)
http://screencast.com/t/EpJVIvdBr

Angus

Edit: BBCoded and a later post merged. [Helmut]

Helmut
★★★

Vienna, Austria,
2014-07-07 01:57
(3938 d 07:34 ago)

@ AngusMcLean
Posting: # 13224
Views: 26,726

Group effect commonly not relevant

Post reply

Hi Angus,

❝ I did see that Formulation not Treatment later after lunch,

For years I try to convince Pharsight to switch from “Formulation” to the more general “Treatment”.

❝ Then following your direction about Group being a classification variable…

Yep, in the BE-module standard mappings are Subject, Sequence, Period, and Formulation. Any additional Classification variables (aka factors = categorical independent variables) have to be manually mapped. The same is true for regressors (aka continuous covariates like body weight).

❝ … (and including subject in model) I did get it to work.

Hhm, I think that Subject should have been mapped automatically. :confused:

❝ Many thanks and also your sample size program in R works well: I have almost zero experience in R, but the reference you provided was easy to follow.

The flowers should go to Detlew. I wrote maybe <1‰ of the code…

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

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AngusMcLean
★★

USA,
2014-07-07 17:04
(3937 d 16:26 ago)

@ Helmut
Posting: # 13226
Views: 26,609

PHX: Parameter mapping

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Helmut: Below comment is of interest.

❝ Hhm, I think that Subject should have been mapped automatically

Yes; I thought so too. :confused:

I spent quite some time on this but found that I had to check the subject box to map it.

I tried to run the program on a number of occasions and it did not run; it told me to map the subject. So at that point I included in the model by clicking on the orange box. I wonder if there is a sequence of events that must be followed to cause subject to map automatidcally

Angus

Edit: Standard quotes restored and subject line changed. [Helmut]

Helmut
★★★

Vienna, Austria,
2014-07-07 17:45
(3937 d 15:46 ago)

@ AngusMcLean
Posting: # 13227
Views: 26,623

PHX: Parameter mapping

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Angus,

can you try the following:

Create a new Phoenix-project.
Navigate to Data > right-click > Import
Navigate to {your program files}\Pharsight\Phoenix\application\Examples > Select Data 2x2.csv > Open
Keep all default options > Finish and Open
Add a new column > Column Name: Group
Input 1 for subjects PHST-01 to PHST-10 and 2 for PHST-11 to PHST-20.
Right-click Data 2x2 > Send To > NCA and Toolbox > Bioequivalence
In my installation Subject is automatically mapped indeed. See below:

Manual mapping is only needed for AUClast > Dependent and Group > Classification.

Can you check?

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

The quality of responses received is directly proportional to the quality of the question asked. 🚮
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Shuanghe
★★

Spain,
2014-07-07 19:35
(3937 d 13:56 ago)

@ Helmut
Posting: # 13228
Views: 26,608

PHX: Parameter mapping

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Hi Angus, Helmut,

I would suggest to add the usual PK parameters (Cmax/AUCt/AUCinf or whatever you'd usually written in your data set such as logAUCt, ... in Edit>Preferences>Mapping Contexts>Global Contexts and then In ...>Mapping Contexts>Context Associations>Bioequivalence Model mapping them to Dependent so you don't have to manually map them every time you run the BE model.

I would suggest to spend some time to create all PK parameters and depending on the necessity mapped them to different settings such as in BE model, different plots etc. As these are prety routine work, once everything is set, you'll seldom need to adjust them and almost all mappings (be it BE model or different plot model) will be automatically done. :-D

—
All the best,
Shuanghe

Helmut
★★★

Vienna, Austria,
2014-07-07 19:54
(3937 d 13:37 ago)

@ Shuanghe
Posting: # 13229
Views: 26,720

Great hint!

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Hi Shuanghe,

wow, I didn’t know this one! Now I have automatic mapping… It is not necessary to create all possible variables. I added AUC and in the right window of Global Contexts at Potential Column Names I added to AUC the usual suspects (AUClast, AUCinf, AUCtau). Simply great – should have RTFM!

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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

AngusMcLean
★★

USA,
2014-07-07 22:49
(3937 d 10:42 ago)

@ Shuanghe
Posting: # 13233
Views: 26,564

PHX: Parameter mapping

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Shuanghe: Thank you for your suggestion. I tried your approach and it worked well for mapping out the variables including the "group". However when you look at the corresponding code for "Fixed effects" and "random effects" in the tabs you will see that it does not have the correct code (from Helmut's original post) so you will run the incorrect model if you do not provide it.

So you have to enter the these effect manually.

Angus.

AngusMcLean
★★

USA,
2014-07-07 20:46
(3937 d 12:44 ago)

@ Helmut
Posting: # 13230
Views: 26,670

PHX: Parameter mapping

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Thank you; I will try it out. First I just verified that presently it does automatically map.....definitely not.

HELMUT: NO mapping whatsoever!

You have to mp it yourself,

Helmut: I was able to repeat the work by reimporting the example file (2x2CSV) data file: yes; it is only necessary to add the dependent variable AUC plus group variable.

However when add the group variable you have to edit the model and this necessitates virtually rewriting the model to include the new terms outlined in your original post. If you just clicked on group for mapping and the model is automatically organized for you is what you would like top happen,

The need to add "GROUP" as classification variable on mapping is the fly in the ointment.

Angus

Edit: Please don’t open new posts if you want to make only a minor correction or want to add something. I merged two of your follow-ups. You can edit your posts for 24 hours (see also the Forum’s Policy). [Helmut]