Ribba2012: Ribba2012 RxODE model

In nlmixrdevelopment/rxModels: RxODE model library

Description

A tumor growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy

Usage

Ribba2012

Format

An RxODE model with 9 parameters, 4 ODE states, and 1 calc vars.

Parameters (Ribba2012$params)

Typical parameters:

tk

Maximum tumor size (default=100) mm

tkde

Decay rate of PCV concentration in plasma (default=0.3)

tkpq

Transition rate of proliferative tissue to quiescence tissue (default=0.025)

tkqpp

Rate constant for damaged quiescent tissue transferring x1to proliferative tissue (default=0.004)

tlambdap

Rate of tissue growth for proliferative tissue (default=0.12)

tgamma

Damage rate in all tissue (default=1)

tdeltaqp

Rate constant for elimination of the damaged quiescent tissue (default=0.01)

tpt0

Initial proliferative tissue amount (default=5)

tq0

Initial quiescent tissue level (default=40)

Eta parameters are all zero by default.

State Ribba2012$state

c

Concentration compartment (=1)

pt

Proliferative Tissue (=2)

q

Nonproliferative or quiescent tissue (=3)

qp

DNA-Damaged quiescent tissue (=4)

Calculated Variables Ribba2012$lhs

pstar

The total tumor tissue ie p + pt + q

A tumor growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy

References

Ribba B, Kaloshi G, et al. A. tumor growth inhibition model for low-grade glioma treated with chemotherapy or radiotherapy. Clin Cancer Res. 2012 Sep 15;18(18):5071-80. Epub 2012 Jul 3.

https://www.ncbi.nlm.nih.gov/pubmed/22761472 http://simulx.webpopix.org/videos/simulx-video2/

See Also

eventTable, et, rxSolve, RxODE

Examples

## Showing the model code
summary(Ribba2012)

## Model without doses

Ribba2012 %>%
  et(time.units="months") %>%
  et(0, 250, by=0.5) %>%
  rxSolve() %>%
  plot(pt, q, qp, pstar)

## Add dose of "1" from 50 to 57.5 months by 1.5

Ribba2012 %>%
  et(time.units="months") %>%
  et(0, 150, by=0.5) %>%
  et(amt=1, time=50, until=58, ii=1.5) %>%
  rxSolve() %>%
  plot(pt, q, qp, pstar)

## Add CVs from paper for individual simulation
## Uses exact formula:

lognCv = function(x){log((x/100)^2+1)}

library(lotri)
## Now create omega matrix
omega <- lotri(eta.pt0 ~ lognCv(94),
               eta.q0 ~ lognCv(54),
               eta.lambdap ~ lognCv(72),
               eta.kqp ~ lognCv(76),
               eta.qpp ~ lognCv(97),
               eta.deltaqp ~ lognCv(115),
               eta.kde ~ lognCv(70))
set.seed(3708)

## simulate 3 subjects
Ribba2012 %>%
  et(time.units="months") %>%
  et(0, 150, by=0.5) %>%
  et(amt=1, time=50, until=58, ii=1.5) %>%
  rxParams(omega=omega, nSub=3) %>%
  rxSolve() %>%
  plot(pt, q, qp, pstar)

## simulate 3 subjects w/ 3 studies
Ribba2012 %>%
  et(time.units="months") %>%
  et(0, 150, by=0.5) %>%
  et(amt=1, time=50, until=58, ii=1.5) %>%
  rxParams(omega=omega, nSub=3, nStud=3, dfSub=24) %>%
  rxSolve() %>%
  plot(pt, q, qp, pstar)

nlmixrdevelopment/rxModels documentation built on March 26, 2021, 9:17 a.m.