LARisk (version 1.0.0)

LAR: Estimate Lifetime Attributable Risk for one person

Description

LAR is used to estimate lifetime attributable radiation-related cancer risk for data with one person.

Usage

LAR(
  data,
  basedata,
  sim = 300,
  seed = 99,
  current = as.numeric(substr(Sys.Date(), 1, 4)),
  ci = 0.9,
  weight = NULL,
  DDREF = TRUE,
  basepy = 1e+05
)

Arguments

data

data frame containing demographic information and exposure information. See 'Details'.

basedata

a list of the data of lifetime table and incidence rate table. The first element is lifetime table and the second is incidence rate table.

sim

number of iteration of simulation.

seed

a random seed number.

current

a current year. default is year of the system time.

ci

confidence level of the confidence interval.

weight

a list containing the value between 0 and 1 which is a weight on ERR model. See 'Details'.

DDREF

logical. Whether to apply the dose and dose-rate effectiveness factor.

basepy

number of base person-years

Value

LAR returns an object of "LAR" class.

An object of class "LAR" is a list containing the following components:

LAR

Lifetime attributable risk (LAR) from the time of exposure to the end of the expected lifetime.

F_LAR

Future attributable risk from current to the expected lifetime.

LBR

Lifetime baseline risk.

BFR

Baseline future risk.

LFR

Lifetime fractional risk.

TFR

Total future risk.

current

Current year.

ci

Confidence level.

pinfo

Information of the person.

Details

The maximum age in LAR is set as 100. If the data contains birth which makes attained age (=current - birth) exceed 100, the result has no useful value.

data should include information which includes gender, year of birth, year of exposure, sites where exposed, exposure rate, distribution of dose and dose parameters of exosed radiation. The name of each variables must be sex, birth, exposure, site, exposure_rate, dosedist, dose1, dose2, dose3.

For some variables, there is a fixed format. sex can have the component 'male' or 'female'. site can have the component 'stomach', 'colon', 'liver', 'lung', 'breast', 'ovary', 'uterus', 'prostate', 'bladder', 'brain/cns', 'thyroid', 'remainder', 'oral', 'oesophagus', 'rectum', 'gallbladder', 'pancreas', 'kidney', 'leukemia'. exposure_rate can have the component 'acute' or 'chronic'. dosedist can have the component 'fixedvalue', 'lognormal', 'normal', 'triangular', 'logtriangular', 'uniform', 'loguniform'.

dose1, dose2, dose3 are parameters of dose distribution. The parameters for each distribution are that:

fixedvalue

dose value (dose1)

lognormal

median (dose1), geometric standard deviation (dose2)

normal

mean (dose1), standard deviation (dose2)

triangular or logtriangular

minimum (dose1), mode (dose2), maximum (dose3)

uniform or loguniform

minimum (dose1), maximum (dose2)

weight

References

Berrington de Gonzalez, A., Iulian Apostoaei, A., Veiga, L., Rajaraman, P., Thomas, B., Owen Hoffman, F., Gilbert, E. and Land, C. (2012). RadRAT: a radiation risk assessment tool for lifetime cancer risk projection. Journal of Radiological Protection, 32(3), pp.205-222.

National Research Council (NRC) and Committee to Assess Health Risks from Exposure to Low Levels of Ionizing Radiation (2005) Health Risks from Exposure to Low Levels of Ionizing Radiation: BEIR VII Phase 2 (Washington, DC: National Academy of Sciences)

See Also

LAR_batch, LAR_group

Examples

# NOT RUN {
## example with lifetime and incidence rate table in 2010 Korea.
organ2 <- split(organ, organ$ID)[[1]]   ## data of one person.

## defualt
lar1 <- LAR(organ2, basedata = list(life2010, incid2010))
summary(lar1)

## change the weight for ERR and EAR models
weight_list <- list("rectum" = 0.5)
lar2 <- LAR(organ2, basedata = list(life2010, incid2010), weight = weight_list)
summary(lar2)

## change the DDREF option (DDREF=FALSE)
lar3 <- LAR(organ2, basedata = list(life2010, incid2010), DDREF = FALSE)
summary(lar3)


# }