Mark, Wow, are we getting off the original subject (which we always do). I'd suggest that oncologists and epileptolgist are exceptions - they have learned to deal with individualized dosing because of the toxicity of the drug they use. Many, many studies have documented the issues of mis-dosing drugs, and estimated the resulting fatalities. Making dosing more complicated is unlikely the help. In addition, each company very much wants their drug to be simpler to use than their competitors.
Mark Sale MD Next Level Solutions, LLC www.NextLevelSolns.com > -------- Original Message -------- > Subject: Re: [NMusers] General question on modeling > From: Nick Holford <[EMAIL PROTECTED]> > Date: Mon, March 19, 2007 9:36 pm > To: nmusers@globomaxnm.com > > Mark, > > > Reality is that the vast majority of providers couldn't > > deal with renal function as a continuous variable in dosing. Writing a > > label requiring them to do so would not result in an optimal outcome. > > The vast majority of providers are perfectly able to deal with renal function > as a continuous variable. They don't do it because they dont appreciate the > mistakes they are encouraged to make by untested labelling strategies. > > Clinical trials have shown clinicians can be encouraged to use quantitative > dosing on a continuous scale with a proven benefit in outcome by ignoring the > drug label advice e.g. > > Evans W, Relling M, Rodman J, Crom W, Boyett J, Pui C. Conventional compared > with individualized chemotherapy for childhood acute lymphoblastic leukemia. > New England Journal of Medicine 1998;338:499-505 > > BTW I'm still waiting to hear if you have an example of finding the Holy > Grail... > > > > > > -------- Original Message -------- > > > Subject: Re: [NMusers] General question on modeling > > > From: Nick Holford <[EMAIL PROTECTED]> > > > Date: Mon, March 19, 2007 8:27 pm > > > To: nmusers@globomaxnm.com > > > > > > Mark, > > > > > > If we are talking about science then we are not talking about regulatory > > > decision making. The criteria used for regulatory approval and labelling > > > are based on pragmatism not science e.g. using intention to treat > > > analysis (use effectiveness rather than method effectiveness), dividing a > > > continuous variable like renal function into two categories for dose > > > adjustment. This kind of pragmatism is more art than science because it > > > does not correctly describe the drug properties (ITT typically > > > underestimates the true effect size) nor rationally treat the patient > > > with extreme renal function values. > > > > > > As Steve reminded us all models are wrong. The issue is not whether some > > > ad hoc model building algorithm is correct or has the right type 1 error > > > properties under some null that is largely irrelevant to the purpose. The > > > issue is does the model work well enough to satisfy its purpose. Metrics > > > of model performance should be used to decide if a model is adequate not > > > a string of dubiously applied P values. > > > > > > The search process is up to you. I think from your knowledge of computer > > > search methods you will appreciate that those methods that involve more > > > randomness/wild jumps in the algorithm generally have a better chance of > > > approaching a global minimum. > > > > > > IMHO the covariate search process is like the search for the Holy Grail. > > > Its fundamentally a process for those with a religious belief that there > > > is some special set of as yet unidentified covariates that will explain > > > between subject variability. As a non believer I think that all the major > > > leaps in explaining BSV comes from prior knowledge (weight, renal > > > function, drug interactions, genetic polymorphisms) and none have been > > > discovered by trying all the available covariates during a blind search. > > > If you have a counter example then please let me know and tell me how > > > much the BSV variance was reduced when this unsuspected covariate was > > > added to a model with appropriate prior knowledge covariates. > > > > > > Nick > > > > -- > Nick Holford, Dept Pharmacology & Clinical Pharmacology > University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand > email:[EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:373-7556 > http://www.health.auckland.ac.nz/pharmacology/staff/nholford/
