Re: Covariate modelling, covaraite effects

From: Marc Gastonguay Date: April 14, 2010 technical Source: mail-archive.com
Dear Joann, If your goal is to learn about the the effect of CLCR on CLM2, you'll need to keep this effect in the model. If your goal is to reduce IIV, then it appears you could exclude this effect, but you won't learn anything about the effect of CLCR on CLM2. Keep in mind that your estimate of IIV may be biased or imprecise, and using the estimated value of this parameter as the only criterion for exclusion of a covariate effect is risky and leads to a model that is not very useful... especially when goodness of fit and clinical interest would lead you to include the covariate effect in the model. Marc
Quoted reply history
On Apr 13, 2010, at 5:07 PM, joan hern wrote: > Dear NMusers, > > I would like to have your help on the following issue: > > I am trying to model the PK of a parent compound and two metabolites (M1 is > the major and M2 is the minor metabolite), both metabolites are mainly > eliminated by renal excetion although a minor biliar excretion pathway > exists. Creatinine clearance (CLCR) values in the studied population range > form 10 to 100 mL/min. The plots of eta vs CLCR show a relationship in both > cases The inclusion of CLCR on CLM1 as covariate decreases significantly the > OFV value in 1779 units with respect to the base model, and a decrease of > about 30% is observed in the IIV of this parameter (CLM1). > > In the case of the second metabolite (M2) the inclusion of CLCR on CLM2 > decreases the OFV around 700 units but no reduction of IIV of CLM2 is > observed when compared with the base model. For the second metabolite, > reduction in the residual error with respect to the base model is very low > (around 10%). > > The way I entered the covariates was in both cases > TVCL= theta(x)*(CLCR/mean population CLCR value)**(theta(y)). > > In both cases, all the model parameters were estimated correctly. Then my > question is if I should leave CLCR in CLM2 or I should remove it. I would > appreciate your comments and suggestions about how to deal with this and > about what could be the reasons of this. > Best regards > joann >
Apr 13, 2010 Joan Hern Covariate modelling, covaraite effects
Apr 13, 2010 Marc Gastonguay Re: Covariate modelling, covaraite effects
Apr 14, 2010 Marc Gastonguay Re: Covariate modelling, covaraite effects