wxp
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China,
2013-05-27 12:34
(4366 d 05:04 ago)

Posting: # 10661
Views: 14,680
 

 Add more subjects after a failed BE study of a HVD [Study As­sess­ment]

Dear all,

We did a typical 2×2 cross-over study for BE study in 23 subjecct. But the results was not BE. We handled the data by PHX 6.3 and got its inter- and intra-subject CV(>30%) (see below). We considered it is a highly variable drug (HVD) and also realized the sample size was not enough. So, we want to add some more subjects and evaluate the BE again with all the data. I am confusing about the sample size calculation.

Dependent   Units    Parameter        Estimate
Ln(Cmax)    ng/mL    Var(SEQUENCE*ID) 0.07
Ln(Cmax)    ng/mL    Var(Residual)    0.35
Ln(Cmax)    ng/mL    Intersubject CV  0.22
Ln(Cmax)    ng/mL    Intrasubject CV  0.65
Ln(AUClast) hr*ng/mL Var(SEQUENCE*ID) 0.38
Ln(AUClast) hr*ng/mL Var(Residual)    0.17
Ln(AUClast) hr*ng/mL Intersubject CV  0.67
Ln(AUClast) hr*ng/mL Intrasubject CV  0.41


1. Which PK parameter should I use to calculate the sample size? I chose the intra-sub CV of AUClast and used PowerTOST to calculate the sample size (see results below):

sampleN.TOST(CV=0.41)
+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  2x2 crossover
log-transformed data (multiplicative model)

alpha = 0.05, target power = 0.8
BE margins        = 0.8 ... 1.25
Null (true) ratio = 0.95,  CV = 0.41

Sample size (total)
 n     power
70   0.810715


As I understand n=70 means that there are actually only 35 subjects participate the study. So we only need 35-23=12 subjects more to perform a 2-way cross design. Is it correct?

2. If I consider it as a two-stage design, should I use alpha=0.0294 to calculate the sample size (see below)? If so, we need more subjects(40-23=17).
sampleN.TOST(alpha=0.0294,CV=0.41)
+++++++++++ Equivalence test - TOST +++++++++++
            Sample size estimation
-----------------------------------------------
Study design:  2x2 crossover
log-transformed data (multiplicative model)

alpha = 0.0294, target power = 0.8
BE margins        = 0.8 ... 1.25
Null (true) ratio = 0.95,  CV = 0.41

Sample size (total)
 n     power
82   0.802106


3. Is the Null (true) ratio the one calculated from the first 23-subject study? PHX 6.3 results below. If so, I should set "theta0=0.98" in the sampleN.TOST function.
Dependent    Ratio_%Ref_
Ln(Cmax)     102
Ln(AUClast)  98


Thank you in advance for any comments.


Edit: Category changed. [Helmut]

Best regards,

Xipei
China
Dr_Dan
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Germany,
2013-05-27 14:28
(4366 d 03:10 ago)

@ wxp
Posting: # 10662
Views: 13,467
 

 bad luck

Dear wxp
a BE study is a pivotal study and so unfortunately it will not be possible to add another group of subjects since this has to be pre-specified in the protocol. Furthermore appropriate steps to preserve the overall type I error (patient’s risk) have to be considered.
For further information please see Potvin D, Diliberti CE, Hauck WW, Parr AF, Schuirmann DJ, and RA Smith: Sequential design approaches for bioequivalence studies with crossover designs. Pharmaceut Statist 7/4, 245–62 (2008)
Kind regards
Dan

Kind regards and have a nice day
Dr_Dan
wxp
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China,
2013-05-27 16:19
(4366 d 01:20 ago)

@ Dr_Dan
Posting: # 10664
Views: 13,426
 

 bad luck

❝ a BE study is a pivotal study and so unfortunately it will not be possible to add another group of subjects since this has to be pre-specified in the protocol. ...


Thank you, Dr_Dan! :-)

Best regards,

Xipei
China
Helmut
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2013-05-27 15:51
(4366 d 01:48 ago)

@ wxp
Posting: # 10663
Views: 13,975
 

 Beware of Add-on Studies!

Dear Xipei,

shit happens. You can’t simply add subjects to a failed study since the patients’s risk will not be maintained at ≤5%. Translating statistics into simple words: You have already “consumed” the entire 5% in the first study and nothing is “left” for the add-on.

Some remarks for the future:
  • Always plan for the PK metric with the higher CV (in most cases Cmax). It doesn’t make sense to plan for BE of AUC (CV 41%) since you will fail with Cmax (CV 65%). With your CVs you would need 70 subjects for AUC but 154 for Cmax. If you run the study in 70 subjects, power to show BE for Cmax would be only 38%! Try power.TOST(CV=0.65, n=70).
  • Allow for a safety margin. The CV is only an estimate carrying some degree of uncertainty (depending on the sample size). You can get an upper confidence limit of the CV from PowerTOST (df for a 2×2 cross-over = n-2). With your CV of Cmax:
      CVCL(CV=0.65, df=21)
      lower CL upper CL
      0.000000 0.9452972
    ← nightmare!
  • If you want to perform a Two-Stage method in the next study, you have to prespecify this intention in the protocol and state the framework you want to follow.
  • With one exception1 all Two-Stage methods2–4 are using a fixed T/R-ratio (0.95 or 0.90) – not the ratio observed in stage 1. Note that Karalis & Macheras limit the total sample size with 150 subjects. It will be a close shave even if you find exactly the same results like in the failed study. Try sampleN.TOST(alpha=0.0294, theta0=1.02, CV=0.65). If either the ratio or the CV is only 1% worse you will fail in stage 1 (since ntotal >150).
  • In sample size re-estimation for stage 2 always use the adjusted α (e.g., 0.0294 for Potvin’s methods).
  • PowerTOST gives the total sample size – not sample sizes per sequence. See help(sampleN.TOST).
  • IMHO with such high CVs Two-Stage designs do not make any sense. Have a look at Potvin’s Table II for a CV of 100%: With already 60 subjects in the first stage you always will have to proceed to the second stage. Average total sample size is 359 (95% CI: 258–474). Crazy.
    Talk to your agency whether reference-scaling is acceptable. If yes, ask which method they would accept (FDA’s or EMA’s). You would need a replicate design (preferably a full replicate: RTR|TRT or RTRT|TRTR). For the required sample sizes see sampleN.RSABE (FDA) and sampleN.scABEL (EMA).
  • Learn from the failed study. Did you sample frequently enough in order to “catch” Cmax in all subjects? This is a very important aspect especially for delayed release formulations.
Maybe you find these presentions useful: Two-Stage Designs, Reference-Scaled ABE. Good luck.


    References:
  1. Karalis V, Macheras P. An Insight into the Properties of a Two-Stage Design in Bioequivalence Studies. Pharm Res. 2013;30(7):1824–35. doi 10.1007/s11095-013-1026-3
  2. Potvin D et al. Sequential design approaches for bioequivalence studies with crossover designs. Pharm Stat. 2008;7(4):245–62. doi 10.1002/pst.294
  3. Montague TH et al. Additional results for ‘Sequential design approaches for bio-equivalence studies with crossover designs’. Pharm Stat. 2011;11(1):8–13. doi 10.1002/pst.483
  4. Fuglsang A. Sequential Bioequivalence Trial Designs with Increased Power and Controlled Type I Error Rates. AAPS J. 2013;15(3):659–61. doi 10.1208/s12248-013-9475-5

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Shuanghe
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Spain,
2013-05-27 17:59
(4365 d 23:40 ago)

@ Helmut
Posting: # 10666
Views: 13,500
 

 Beware of Add-on Studies!

Hi Helmut,

❝ It doesn’t make sense to plan for BE of AUC (CV 41%) since you will fail with Cmax (CV 65%).


From the Xipei's habit of estimating sample size with AUC I assume this is a study for Chinese regulation. If so, the Chinese BE guideline reads that criterion for AUC is 80-125 but for Cmax, hold-on, deep breath, …, 70-143% (and the study doesn't even have to be of replicate design :-D)

OK, now you can pick the draw you just dropped on the ground. :lol3:

All the best,
Shuanghe
Helmut
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2013-05-27 18:21
(4365 d 23:17 ago)

@ Shuanghe
Posting: # 10667
Views: 13,507
 

 Oh wow!

Hi Two Rivers!

❝ From the Xipei's habit of estimating sample size with AUC I assume this is a study for Chinese regulation. If so, the Chinese BE guideline reads that criterion for AUC is 80-125 but for Cmax, hold-on, deep breath, …, 70-143% (and the study doesn't even have to be of replicate design :-D)


Oh wow! With such limits AUC is really the win-loose-metric. Are you referring to the 2005 GL?

等效判断标准,一般规定,经对数转换后的受试制剂的AUC0→t 在参比 制剂的80%-125%范围,受试制剂的Cmax 在参比制剂的70%-143%范围。


I wish him good luck in setting up simulations to find a suitable αadj. for [0.70–1.43]. None of the published methods would work.

❝ OK, now you can pick the draw you just dropped on the ground. :lol3:


Well, hundreds of products were approved in the EU with those limits – but decades ago…

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China,
2013-05-28 08:10
(4365 d 09:28 ago)

@ Helmut
Posting: # 10670
Views: 13,609
 

 The same criterion of Cmax in China now

Hi, Shuanghe and Helmut,

❝ ❝ From the Xipei's habit of estimating sample size with AUC I assume this is a study for Chinese regulation. If so, the Chinese BE guideline reads that criterion for AUC is 80-125 but for Cmax, hold-on, deep breath, …, 70-143% (and the study doesn't even have to be of replicate design :-D)


❝ Oh wow! With such limits AUC is really the win-loose-metric. Are you referring to the 2005 GL?

等效判断标准,一般规定,经对数转换后的受试制剂的AUC0→t 在参比 制剂的80%-125%范围,受试制剂的Cmax 在参比制剂的70%-143%范围。


The Chinese criteria of Cmax changed in 2010 to 75%~133% according to the latest guideline (Appendix XIXB in Chinese Pharmacopoeia (version 2010)). The criteria of AUC is still 80%~125%.

Helmut, it really surprised me that you can read Chinese.

❝ Well, hundreds of products were approved in the EU with those limits – but decades ago…


Chinese regulation improved these years, but there is still no specific guidelines on the BE of HVD. However,Chinese experts are very interested in it.

P.S. Chinese FDA changed the name to China Food and Drug Administration (CFDA) :-D

Best regards,

Xipei
China
Helmut
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2013-05-28 15:02
(4365 d 02:36 ago)

@ wxp
Posting: # 10674
Views: 13,634
 

 SFDA ⇒ CFDA

Hi Xipei!

❝ The Chinese criteria of Cmax changed in 2010 to 75%~133% according to the latest guideline (Appendix XIXB in Chinese Pharmacopoeia (version 2010)).


THX, good to know!

❝ Helmut, it really surprised me that you can read Chinese.


I can’t. I only know how to copy/paste and work with Google-translate. ;-)

❝ P.S. Chinese FDA changed the name to China Food and Drug Administration (CFDA) :-D


THX again. I updated the Guideline-collection accordingly.

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Shuanghe
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Spain,
2013-06-14 13:05
(4348 d 04:34 ago)

@ Helmut
Posting: # 10789
Views: 13,108
 

 Helmut, updated Chinese BE guideline here

Thank you Xipei, I didn't know there was update of the 2005 Chinese guidance. :ok: Last time I checked it is in 2008.

❝ THX again. I updated the Guideline-collection accordingly.


Helmut, i don't know how to upload to your web but you can download the pdf file here:

http://wenku.baidu.com/view/e641f7fdc8d376eeaeaa3171.html

Shuanghe

All the best,
Shuanghe
Helmut
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2013-06-14 16:22
(4348 d 01:17 ago)

@ Shuanghe
Posting: # 10792
Views: 13,182
 

 BE in Chinese Pharmacopoeia

Hi Shuanghe!

❝ Helmut, i don't know how to upload to your web


Doesn’t work. Only image-uploads are possible here.

❝ but you can download the pdf file here:

http://wenku.baidu.com/view/e641f7fdc8d376eeaeaa3171.html


THX; I will add the link to the Guideline-collection. BTW, is calculation of AUC0→∞ as AUC0→tn+Ctn/λz (given on page 5) mandatory or just a suggestion, i.e., can one use the estimated Ctn instead?

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Shuanghe
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Spain,
2013-06-14 16:56
(4348 d 00:43 ago)

@ Helmut
Posting: # 10794
Views: 13,030
 

 BE in Chinese Pharmacopoeia

❝ BTW, is calculation of AUC0→∞ as AUC0→tn+Ctn/λz (given on page 5) mandatory or just a suggestion, i.e., can one use the estimated Ctn instead?


It read that Ctn is the concentration at the last point. No mention of observed or predicted; but from the context I'd say that they are asking for the observed.

All the best,
Shuanghe
Helmut
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2013-06-14 18:11
(4347 d 23:28 ago)

@ Shuanghe
Posting: # 10798
Views: 13,114
 

 BE in Chinese Pharmacopoeia

Hi Shuanghe!

❝ […] but from the context I'd say that they are asking for the observed.


Correct. I is not clear to me whether the observed Ctn is mandatory to be used.

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China,
2013-05-28 07:13
(4365 d 10:26 ago)

@ Helmut
Posting: # 10668
Views: 13,356
 

 Add more subjects after a failed BE study of a HVD

❝ ... Translating statistics into simple words: You have already “consumed” the entire 5% in the first study and nothing is “left” for the add-on.

❝ Some remarks for the future:Always plan for the PK metric with the higher CV (in most cases Cmax)...


Thank you, Helmut, for your explanation and answers to my questions. I learnt a lot from the failed BE study. It is worth the time to make a deliberate plan (protocol) before the study.

❝ ... You would need a replicate design (preferably a full replicate: RTR|TRT or RTRT|TRTR). For the required sample sizes see sampleN.RSABE (FDA) and sampleN.scABEL (EMA).


I tried both with CV=0.68. 42 subjects are needed for EMA, while only 27 subjects are needed for FDA. We plan to redo the BE study with a RSABE or SCABEL design.

Learn from the failed study. Did you sample frequently enough in order to “catch” Cmax in all subjects? This is a very important aspect especially for delayed release formulations...


It was a BE study of an old drug's conventional tablet. We sampled frequently enough to "catch" the Cmax. :-)

Thanks a lot for the slides and references.

Best regards,

Xipei
China
Helmut
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2013-05-28 14:56
(4365 d 02:43 ago)

@ wxp
Posting: # 10673
Views: 13,390
 

 Still many subjects…

Hi Xipei,

❝ ❝ ... You would need a replicate design (preferably a full replicate: RTR|TRT or RTRT|TRTR). For the required sample sizes see sampleN.RSABE (FDA) and sampleN.scABEL (EMA).


❝ I tried both with CV=0.68. 42 subjects are needed for EMA, while only 27 subjects are needed for FDA. We plan to redo the BE study with a RSABE or SCABEL design.


Ok, but only if CFDA accepts scaling! I would rather opt for a four period full replicate design (sample sizes for ABEL 30 and for RSABE 20), if
  • your analytical method can handle small sample volumes (limited by total blood loss) and
  • you don’t expect too many drop-outs (more likely in four periods).
The partial replicate is statistically tricky. Another option would be a full replicate three period design (RTR|TRT), but it is not implemented in PowerTOST yet (though I expect similar sample size like in the partial replicate) and you have to adapt FDA’s and EMA’s code (easy).

If CFDA does not accept scaling and 75–133% is applicable for Cmax (your other post) you would need (T/R 0.95, CV 0.68, 80% power):
design       PowerTOST  n   treatments    power
RT|TR          2×2      92     184      0.805498
RRT|RTR|TRR    2×3×3    69     207      0.807633
RTR|TRT        2×2×3    68     204      0.801400
RTRT|TRTR      2×2×4    46     184      0.807602

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