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Dear All,
I am working on determining dose proportionality in Cmax and AUC
using SAS, for a dose range finding study in humans.
The doses used are 500, 750, 1000, 1250 and 1500 mg (n=8).
We have used power model to determine dose proportionality. Kindly
explain the results we obtained:
1. For AUC0-inf, we are getting the 95% CI as -0.02 - 1.38. Can any
body explain what are the implications of getting negative lower CI
value.
AUC0-inf seems to be dose proportional as it includes 1, but what is
the importance of getting zero value in the Confidence Interval.
Thanking you in advance.
Tausif Ahmed, Ph.D.
Research Scientist
Metabolism and PK Department
Ranbaxy Research Laboratories, India
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The following message was posted to: PharmPK
If your 95% CI includes 0 then that means that exposure does not
increase with dose - it's a flat line. Did you do Ln-transformation?
Something doesn't look right? Double check your SAS code.
Peter L. Bonate, PhD
Genzyme Corporation
Senior Director, Pharmacokinetics
4545 Horizon Hill Blvd
San Antonio, TX 78229 USA
peter.bonate.-a-.genzyme.com
phone: 210-949-8662
fax: 210-949-8219
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The following message was posted to: PharmPK
Peter,
I cannot agree with your flat line interpretation.
> If your 95% CI includes 0 then that means that exposure does not
> increase with dose - it's a flat line. Did you do Ln-transformation?
> Something doesn't look right? Double check your SAS code.
I can't see the earlier part of the thread (thanks to the PharmPk
censoring policy) but in general if the 95% CI includes 0 it means
the evidence is not strong enough with the traditional alpha level to
reject the null hypothesis. All too often dose-response trials are
underpowered and a dose-response may well exist.
Ln-transformation?? Why on earth do that? There is no pharmacological
basis for this. Pharmacodynamics has been based on the theory of the
law of mass action for over 100 years -- hyperbolic models are
preferred e.g. Emax or sigmoid Emax.
Nick
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
email:n.holford.-a-.auckland.ac.nz tel:+64(9)373-7599x86730 fax:373-7556
http://www.health.auckland.ac.nz/pharmacology/staff/nholford/
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The following message was posted to: PharmPK
Nick,
The original question had to do with the power model. Under that
formulation for dose proportionality you model Ln(AUC) against Ln
(Dose) and
check to see if the slope is equal to 1. Here is the generally
recognized
reference for the power model:
Assessment of dose proportionality : report from the statisticians in
the
pharmaceutical industry/pharmacokinetics UK joint working party
Auteur(s) / Author(s)
GOUGH K. (1) ; HUTCHISON M. ; KEENE O. ; BYROM B. ; ELLIS S. ; LACEY
L. ;
MCKELLAR J. ; SHEIN-CHUNG CHOW (a1) ; Drug Information Association
Affiliation(s) du ou des auteurs / Author(s) Affiliation(s)
(1) Fisons Pharmaceutical Division, Loughborough, ROYAUME-UNI
(a1) Bristo-Myers Squibb Co ; biostatistics data management,
Plainsboro NJ
08536, ETATS-UNIS
Revue / Journal Title
Drug information journal (Drug inf. j.) ISSN 0092-8615
Source / Source
Congres
BIO-international conference
BIO-international conference, Rockville MD , ETATS-UNIS (19/09/1994)
1995, vol. 29, no 3 (10 ref.), pp. 1039-1048
pete
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The following message was posted to: PharmPK
Pete,
I am aware of the whacky power function used by non-pharmacological
statistians to 'declare dose proportionality'.
Any rational attempt to understand kinetics in relation to dose would
use PK theory not empirical ad hoc 'beat it to death with a P value'
statistics.
Best wishes,
Nick
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
email:n.holford.-at-.auckland.ac.nz tel:+64(9)373-7599x86730 fax:373-7556
http://www.health.auckland.ac.nz/pharmacology/staff/nholford/
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The following message was posted to: PharmPK
Tausif: I guess you are following methodology outlined in Smith BP et
al: CI approach criteria for the assessment of Dose Proportionality;
Pharm. Res 2000, 17, 1278-83 (other paper of use is Drug Info J 1995,
29, 1039-48), In my opinion extreme dose groups have a lot of influence
in biasing the overall conclusion. Our statistician proposed basement of
confidence intervals at every does to see if the confidence intervals
are contained with in some margin +/- X% this way we can identify which
dose group is rocking the dose proportional boat.
We are presenting a paper on dose proportionality evaluation of
hydrocondone in the upcoming AAPS meeting (Monday afternoon), if you are
attending that meeting we can discuss details. Otherwise I will be glad
to e-mail you SAS code and pre-print of the poster and paper (under
preparation), objective of this work is to evaluates various available
analytical tools for investigating dose-proportionality and discuss
which methodology is good under what conditions.
Hope my answer helps.
Prasad
Prasad NV Tata, Ph.D., FCP
Manager-Pharmacokinetics
Mallinckrodt, Inc.
675 McDonnell Blvd.
Saint Louis, MO 63134
Tel: (314) 654-5325
Fax: (314) 654-9325
e-mail: prasad.tata.aaa.tycohealthcare.com
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