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Covariate effect explanation


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#1 Davidq8

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Posted 03 August 2023 - 10:59 PM

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Hello, I have a question about communicating the covariate impact to people who are unfamiliar with the Nonlinear mixed effect methodology used in PopPk analysis.

So, suppose we have body weight influencing drug (X) clearance, and an increase in body weight is associated with a decrease in CL, with the impact estimated by the model (- 0.5).

Can we say that increasing body weight by 10 kg intervals results in a 5% reduction in drug clearance?


Thanks     


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#2 bwendt@certara.com

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Posted 04 August 2023 - 09:56 AM

Hi David,

 

if you define your covariate relationship with a linear model, the reduction would be adjusted by -0.5*10 = -5 

To determine a percentage reduction, you would need to know the typical value of clearance.

 

Bernd



#3 smouksassi1

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Posted 04 August 2023 - 09:57 AM

Hi it depends how your wrote your equation and many times we have multiple covariate affecting the parameter

Also more often than not we want to compute the effects on PK parameters of interest: AUC and Cmax.

 

I wrote this tutorial:
https://ascpt.online...1002/psp4.12829

 

and built this R package:
https://cran.r-proje...plot/index.html

To help you with the process.

 

Suppose:

CL = 5 *(WT/70^0.75

the weight effect is a power function and is nonlinear so a 10 kg increase from 60 to 70 is not the same from 70 to 80

(50/70)^0.75
[1] 0.7769695

> (60/70)^0.75
[1] 0.8908199

> (80/70)^0.75
[1] 1.105335

> (90/70)^0.75
[1] 1.20742

 

think of the above as multipliers as compared to the ref value of 70 kg ( ref = 1)

 

Bests,

Samer



#4 Davidq8

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Posted 19 September 2023 - 10:04 PM

Thanks Bernd and Samer for your answers!!






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