Re: Meta-analysis with Nonmem

Guangli, 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). Nick 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: [email protected] http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford