- On 12 Jun 2005 at 19:28:57, David Bourne (david.-a-.boomer.org) sent the message

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Dear All,

I have a question regarding the definition of bioequivalence.

According to generally accepted criteria, the 90% CI's for determination of

bioequivalence are 80-125%. We have a situation where the product has been

demonstrated to be bioequivalent, although the lower CI for Cmax is sitting

on 80% when using ANOVA (Ln transforming prior to performing the test).

When using the method of Hauschke et al., this CI is shifted down to 77%.

This is also the case for AUCI and AUCT. The power of the tests is well

above 80%. T-testing using parametric and non-parametric tests has not

shown any differences of statistical significance.

Is this product bioinequivalent?

Regards,

Jennifer Norman

University of Cape Town - On 13 Jun 2005 at 18:56:27, Laszlo Endrenyi (l.endrenyi.-at-.utoronto.ca) sent the message

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The parametric procedure determining bioequivalence should be used for

AUCT, AUCI and Cmax. A nonparametric method could be applied, when

desired, for discrete measures such as Tmax. t-tests evaluating the

significance of differences are not relevant in determinations of

bioequivalence.

Laszlo Endrenyi

University of Toronto - On 14 Jun 2005 at 08:56:08, Helmut (helmut.schuetz.-at-.bebac.at) sent the message

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Dear Jennifer,

/one/ possibility for wider CIs after nonparametric testing compared to

their parametric counterparts is the underlying discrete probability function.

Alpha set to 0.05 in a parametric sense is only asymptotically 0.05 (0.05

or smaller), whereas nonparametric alphas are exact - and dependent on

sample size (n).

Below you will find some exact alphas (and resulting CIs) for Hauschke's

method (hoping the table renders in your mail client):

..n....alpha.....CI..

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

..6...0.0465...0.9070

12...0.0444...0.9112

16...0.0469...0.9062

20...0.0482...0.9036

24...0.0486...0.9028

28...0.0499...0.9002

32...0.0487...0.9026

The nonparametric method is a conservative one (alpha is always <0.05, CIs

are always >0.90).

You can get an idea whether this is the reason for a wider CI, if you

calculate the /parametric/ CI with alpha set to the alpha of the

nonparametric method (e.g. for 12 subjects calculate the the t-tests with

alpha 0.0444 instead of 0.05).

> Is this product bioinequivalent?

I don't think so.

If your statistical protocol stated parametric analyses (which I asume...),

you already have shown BE.

You are not supposed to do sequential testing; your alpha is already

"spent", therefore the outcome of the "second stage" is statistically

speaking of "undefined alpha".

best regards,

Helmut

--

Helmut Sch=FCtz

BEBAC

Consultancy Services for Bioequivalence and Bioavailability Studies

Neubaugasse 36/11

1070 Vienna/Austria

tel/fax +43 1 2311746

http://BEBAC.at

Bioequivalence/Bioavailability Forum at http://forum.bebac.at

http://www.goldmark.org/netrants/no-word/attach.html

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