| plotCIN2Incidence {mSimCC} | R Documentation |
Calculates and plots the CIN2 incidence.
Description
Calculates and plots the CIN2 incidence for one or several prevention strategies.
Usage
plotCIN2Incidence(..., current=NULL, labels=NULL)
Arguments
... |
one or several microsimulated cohort corresponding to one or several microsimulated cohorts. |
current |
real CIN 2 incidence in the population of interest. |
labels |
labels to be used in the plot. |
Value
Returns a list with CIN 2 incidence for each age group.
Author(s)
David Moriña (Universitat de Barcelona), Pedro Puig (Universitat Autònoma de Barcelona) and Mireia Diaz (Institut Català d'Oncologia)
References
Georgalis L, de Sanjosé S, Esnaola M, Bosch F X, Diaz M. Present and future of cervical cancer prevention in Spain: a cost-effectiveness analysis. European Journal of Cancer Prevention 2016;25(5):430-439.
Moriña D, de Sanjosé S, Diaz M. Impact of model calibration on cost-effectiveness analysis of cervical cancer prevention 2017;7.
See Also
mSimCC-package, microsim, costs, le,
bCohort, plotCIN1Incidence, plotCIN3Incidence,
plotIncidence, plotMortality, plotPrevalence,
qalys, yls
Examples
data(probs)
nsim <- 3
p.men <- 0
size <- 20
min.age <- 10
max.age <- 84
#### Natural history
hn <- microsim(seed=1234, nsim, probs, abs_states=c(10, 11), sympt_states=c(5, 6, 7, 8),
prob_sympt=c(0.11, 0.23, 0.66, 0.9),
size, p.men, min.age, max.age,
utilityCoefs = c(1, 1, 0.987, 0.87, 0.87, 0.76, 0.67, 0.67, 0.67, 0.938, 0, 0),
costCoefs.md = c(0, 0, 254.1, 1495.9, 1495.9, 5546.8, 12426.4, 23123.4,
34016.6, 0, 0, 0),
costCoefs.nmd = c(0, 0, 81.4, 194.1, 194.1, 219.1, 219.1, 219.1, 219.1, 0, 0, 0),
costCoefs.i = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), disc=3,
treatProbs=c(0,0,1,1,1,0.9894,0.9422,0.8262,0.5507,0,0,0),
nCores=1) ### individual level
hn_c <- bCohort(hn)
plotCIN2Incidence(hn_c) ### Aggregated level