microsim: Generate microsimulated cohorts

In mSimCC: Micro Simulation Model for Cervical Cancer Prevention

Generate microsimulated cohorts

Description

Generates several microsimulated cohorts with desired specifications.

Usage

  microsim(seed=1234, nsim, transition, abs_states, sympt_states, prob_sympt, size, 
           p_men, min_age, max_age, utilityCoefs, costCoefs.md, costCoefs.nmd, 
           costCoefs.i, disc=3, vacc=FALSE, vacc.age=NULL, ndoses=NULL, vacc.cov=NULL, 
           vacc.eff=NULL, vacc.type=NULL, vacc.prop=NULL, vaccprice.md=NULL, 
           vaccprice.nmd=NULL, vaccprice.i=NULL, screening=FALSE, screenType=0, 
           scrSchema=0, screenPeriod=NULL, cytoType=NULL, screenPrice.md=NULL, 
           screenPrice.nmd=NULL, screenPrice.i=NULL, colpoPrice.md=NULL, 
           colpoPrice.nmd=NULL, colpoPrice.i=NULL, hpvTestPrice.md=NULL, 
           hpvTestPrice.nmd=NULL, hpvTestPrice.i=NULL, cytoHpvPrice.md=NULL, 
           cytoHpvPrice.nmd=NULL, cytoHpvPrice.i=NULL, biopsPrice.md=NULL, 
           biopsPrice.nmd=NULL, biopsPrice.i=NULL, screenCoverage=NULL, screenSensi=NULL,
           screenSensi2=NULL, screenSensi3=NULL, colpoSensi=NULL, biopSensi=NULL, 
           hpvTestSensi=NULL, treatProbs, nAnnualVisits=0, nAnnualVisitsLSIL=0, 
           nAnnualVisitsHSIL=0, cytoHPVPeriod=0, cytoHPVPostColpo=0, 
           cytoHPVPostBiop=NULL, cytoLSILperiod=0, cytoHSILperiod=0, switchAge=0, 
           C_period=NULL, hpvPeriod=0, nCores=1)

Arguments

seed	seed to be used in the simulation. Default value is 1234.
nsim	number of cohorts to be simulated.
transition	transition probabilities matrix.
abs_states	vector with the absorbing states.
sympt_states	vector with the health states that might present symptoms.
prob_sympt	vector with the probability of presenting symptoms for each health state that might present symptoms. Should have the same length of sympt_states.
size	number of individuals on each simulated cohort.
p_men	proportion of men in the simulated cohorts.
min_age	lowest age in the cohort.
max_age	largest age in the cohort.
utilityCoefs	vector with the utilities for each health state.
costCoefs.md	vector with the direct medical costs for each health state.
costCoefs.nmd	vector with the direct non medical costs for each health state.
costCoefs.i	vector with the indirect costs for each health state.
disc	discount rate in percentage. Default value is 3.
vacc	boolean value specifying if the considered scenario includes vaccination. Default value is FALSE.
vacc.age	vector with ages at vaccination if the considered scenario includes vaccination. Default value is NULL.
ndoses	number of doses of vaccine if the considered scenario includes vaccination. Default value is NULL.
vacc.cov	vaccine coverage if the considered scenario includes vaccination. Default value is NULL.
vacc.eff	vaccine effectivity if the considered scenario includes vaccination. Default value is NULL.
vacc.type	type of vaccine if the considered scenario includes vaccination, character with values biv for bivalent, quad for quadrivalent and nona for nonavalent vaccines. Default value is NULL.
vacc.prop	proportion of vaccinated women on each age group if the considered scenario includes vaccination. Default value is NULL.
vaccprice.md	vaccine direct medical costs if the considered scenario includes vaccination. Default value is NULL.
vaccprice.nmd	vaccine direct non medical costs if the considered scenario includes vaccination. Default value is NULL.
vaccprice.i	vaccine indirect if the considered scenario includes vaccination. Default value is NULL.
screening	boolean specifying if the considered scenario includes screening of any type. Default value is FALSE.
screenType	type of screening. 1 stands for organized screening, 2 stands for opportunistic screening. Default value is 0 (no screening).
scrSchema	screening schema. 1 stands for cytology alone with repeat cytology for triage, 2 stands for cytology with HPV triage, 3 stands for HPV with cytology triage and 4 stands for HPV genotyping with cytology triage. Default value is 0 (no screening).
screenPeriod	screening period (in years). Default value is NULL (no screening).
cytoType	type of cytology. 0 stands for conventional cytology, 1 stands for Liquid Based Cytology (LBC). Default value is NULL (no cytology).
screenPrice.md	medical direct cost of cytology. Default value is NULL.
screenPrice.nmd	non-medical direct cost of cytology. Default value is NULL.
screenPrice.i	indirect cost of cytology. Default value is NULL.
colpoPrice.md	medical direct cost of colposcopy. Default value is NULL.
colpoPrice.nmd	non-medical direct cost of colposcopy. Default value is NULL.
colpoPrice.i	indirect cost of colposcopy. Default value is NULL.
hpvTestPrice.md	medical direct cost of HPV test. Default value is NULL.
hpvTestPrice.nmd	non-medical direct cost of HPV test. Default value is NULL.
hpvTestPrice.i	indirect cost of HPV test. Default value is NULL.
cytoHpvPrice.md	medical direct cost of HPV reflex test, in case cytoType=1. Default value is NULL.
cytoHpvPrice.nmd	non-medical direct cost of HPV reflex test, in case cytoType=1. Default value is NULL.
cytoHpvPrice.i	indirect cost of HPV reflex test, in case cytoType=1. Default value is NULL.
biopsPrice.md	medical direct cost of biopsy. Default value is NULL.
biopsPrice.nmd	non-medical direct cost of biopsy. Default value is NULL.
biopsPrice.i	indirect cost of biopsy. Default value is NULL.
screenCoverage	cytology coverage for each age group. Default value is NULL.
screenSensi	cytology sensitivity for each age group. Default value is NULL.
screenSensi2	cytology sensitivity after cytology for each age group. Default value is NULL.
screenSensi3	cytology sensitivity after HPV test for each age group. Default value is NULL.
colpoSensi	colposcopy sensitivity for each age group. Default value is NULL.
biopSensi	biopsy sensitivity for each age group. Default value is NULL.
hpvTestSensi	HPV test sensitivity for each age group. Default value is NULL.
treatProbs	probability of recuperation after treatment for each FIGO I - FIGO IV states.
nAnnualVisits	number of annual visits after colposcopy for screening schema 1. Default value is 0.
nAnnualVisitsLSIL	number of annual visits after LSIL for screening schema 2. Default value is 0.
nAnnualVisitsHSIL	number of annual visits after HSIL for screening schema 2. Default value is 0.
cytoHPVPeriod	cytology and HPV test protocol period for screening schemas 3 and 4. Default value is 0.
cytoHPVPostColpo	cytology and HPV test protocol period after colposcopy protocol for screening schemas 3 and 4. Default value is 0.
cytoHPVPostBiop	cytology and HPV test protocol period after biopsy protocol for screening schemas 2. Default value is NULL.
cytoLSILperiod	period for cytology after LSIL detection for screening schame 2. Default value is 0.
cytoHSILperiod	period for cytology after HSIL detection for screening schame 2. Default value is 0.
switchAge	age at which screening protocol changes for screening schemas 3 and 4. Default value is 0.
C_period	vector with screening periods (in years) before and after switch age for screening schemas 3 and 4. Default value is NULL.
hpvPeriod	period for HPV test in screening schema 2. Default value is 0.
nCores	number of cores of the computer. Default value is 1.

Value

Data frame containing the simulated cohorts and the individual history for each person in each simulated cohort.

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, bCohort, costs, le, plotCIN1Incidence, plotCIN2Incidence, 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

mSimCC documentation built on Aug. 22, 2023, 5:07 p.m.