- On 25 Apr 2000 at 21:41:28, jw5886.aaa.cnsvax.albany.edu sent the message

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I will appreciate it if anyone could elaborate on the simulation needed

for the sample size, or point to a good reference. I have been reading

the CDER 1999 August guidance on BE study, and sort of got the feeling

that the average approach now has to be replaced by population/individual

approach. Is it correct? Thanks in advance.

Jun - On 26 Apr 2000 at 21:26:29, David_Bourne (david.at.boomer.org) sent the message

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[A few replies - db]

Date: Wed, 26 Apr 2000 00:38:22 -0400

From: Laszlo Endrenyi

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To: PharmPK.-at-.boomer.org

CC: Multiple recipients of PharmPK - Sent by

Subject: Re: PharmPK Sample size estimate for Population/Individual approach

This is only a draft guidance and is marked as "not for implementation". FDA

is currently reviewing the comments that it has received. So, evaluation of

average bioequivalence is still the basis for submissions. This may well

change in the future if and when the guidance is implemented.

Laszlo Endrenyi

University of Toronto

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Date: Wed, 26 Apr 2000 01:44:21 -0700 (MST)

X-Sender: ml11439.aaa.pop.goodnet.com

To: PharmPK.at.boomer.org

From: ml11439.at.goodnet.com (Michael J. Leibold)

Subject: Re: PharmPK Sample size estimate for Population/Individual approach

Jun,

The concept of statistical power is one way statistical computation

deals with the sample size. The probability of making a type I error

(i.e. detecting a significant treatment effect when there is none) is

considered less than .05 when alpha= .05. The probability of making a

type II error (not detecting a significant treatment effect when one

does exists) is beta. The chance of detecting a significant treatment

effect when one exists is equal to (1-beta) which referred to as

statistical power. (2)

Statistical power for a given statistical test can be estimated

from: 1)the standard deviation of the measured variable (treatment effect)

in the population of interest, 2) the size of the change in the measured

variable (treatment effect), 3) the level of significance chosen (alpha=.05),

4) the nature of the statistical test, and 5)the sample size. This power

analysis can be accomplished with the above information and a power chart.

The same power chart can also be used to estimate the necessary sample size

to obtain an acceptable level of statistical power, which should be in the

area of .80-.90. (1) Some texts also provide the formulae useful for

calculating statistical power and sample size.(2)

One standard example is detecting the effects of diuretics in a

population. If the standard deviation in urine ouput in the population

of interest is 200ml/day, and the expected change in urine output is

200ml/day with diuretic treatment, then the ratio phi= delta/sigma =1.0

is used with the power chart appropriate for the statistical test to

determine the statistical power.(1)

Mike Leibold, PharmD, RPh

ML11439.aaa.goodnet.com

References

1) Glantz, S.A., Primer of Biostatistics 4th ed., New York, McGraw-Hill

1997: 151-183

2) Freidman, L.M., Furberg, C.D., DeMets, D.L., Sample Size in:

Fundamentals of Clinical Trials, Littleton, PSG :Publishing Company

1985:83-107

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X-Lotus-FromDomain: QUINTILES

From: peter.bonate.-at-.quintiles.com

To: PharmPK.at.boomer.org

Date: Wed, 26 Apr 2000 07:39:31 -0500

Subject: Re: PharmPK Sample size estimate for Population/Individual

approach

Jun,

The proposed guidance on BE has not been finalized. Word on the street is that

there was so much criticism to the original version that the FDA is completely

overhauling the guidance. To gain a good understanding of this approach see

Chen and Liu's second edition of their book.

Pete Bonate

Quintiles - On 27 Apr 2000 at 20:03:07, jw5886.-a-.cnsvax.albany.edu sent the message

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Thanks for your help. I do have the Chow and Liu's book pulished around

either 1991 or 1992, although I did not find much elaboration on the topic

of individual or population approach. I have also noticed Mr. Endreyni's

long list of publication in the draft guidance reference section. I will

definitely try to net the articles. I hope I did not misuse this PK

oriented forum by asking too much statistical question, please protest or

recommend a Pharmaceutical/clinical trial forum/listserv, I will

appreciate it in either case.

Now suppose estimating sample size for a BE study is of interest, as

specified in the 1992, a two one sided ttest procedure will be used to

test the ratio of averages, now do people even try to log transform

available AUC or Cmax data from previous studies before they work out the

inter and intra subject coefficient? I have seen example of doing the

sample size estimate on the original scale, but analyze AUC and Cmax on

the log scale, is it what people are doing? BE statistical analysis is

new to me, my major is Biometry and statistics, please bear with my

ignorance. Thanks a lot.

Jun

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