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Re: Meta-analysis with Nonmem

From: Nick Holford <n.holford>
Date: Thu, 04 Mar 2010 07:45:14 +0200


Change from baseline (CFB) is commonly done -- but like other common
statistical practices such as LOCF -- it is not a good idea if you
really want to learn something (see Chan & Holford 2001). CFBis a naive
approach focussed on getting small P values rather than understanding
how disease changes with time and how treatments might modify it.

One key issue that CFB ignores is the correlation between the baseline
value and the rate of progression. This is often quite an important
random effect correlation and should not be ignored (e.g. see Holford et
al 2006).


1. Chan PLS, Holford NHG. Drug treatment effects on disease
progression. Annu Rev Pharmacol Toxicol. 2001;41:625-59.
2. Holford NHG, Chan PL, Nutt JG, Kieburtz K, Shoulson I. Disease
progression and pharmacodynamics in Parkinson disease - evidence for
functional protection with levodopa and other treatments. J
Pharmacokinet Pharmacodyn. 2006 Jun;33(3):281-311.

Guangli Ma wrote:
> Dear Dirk,
> I haven't fully understood your idea. Mean value, SD, and N can be
> collected from literature. But if we don't have a model, how can we
> simulate one individual with many observations?
> I met a problem and haven't got a solution. I chose change from
> baseline as endpoint. But some literatures didn't provide CFB. The CFB
> and SD of CFB calculated from mean value and SD are different from
> the values calculated from individual data. Your suggestion will be
> highly appreciated. Thanks.
> Best regards,
> Guangli

Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53
email: n.holford

Received on Thu Mar 04 2010 - 00:45:14 EST

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