risk.mpc: Predict the risks of developing multiple primary cancers

In wwylab/LFSPRO: TP53 germline mutation carrier estimation and cancer risk predictions

Predict the risks of developing multiple primary cancers

Description

Calculate the future cancer risk of each counselee who has had one primary cancer before using the MPC model (this model is not built to predict the cancer risks for patients who have had multiple primary cancer)

Usage

  risk.mpc(fam.cancer.data, cid, parameter)

Arguments

fam.cancer.data	Data frame storing family and cancer information. See fam.cancer.data for details.
cid	Individual id for the counselee. If you want to estimate multiple samples at the same time, just set counselee.id as a vector of IDs for all the samples.
parameter	See parameter.mpc for details.

Value

Matrix, family ID, personal ID and the cancer risks in 5, 10 and 15 years.

Author(s)

Nam Nguyen

References

Shin SJ, Li J, Ning J, Bodjadzieva J, Strong LC and Wang W. A Bayesian estimation of semiparametric recurrent event model with applications to the penetrance estimation of multiple primary cancers in Li-Fraumeni syndrome. Biostatistics

Examples

fam.id <- unique(fam.data$fam.id) 
famdata <- fam.data[fam.data$fam.id == fam.id[1], c(1:6)] 
cancerdata <- cancer.data[cancer.data$fam.id == fam.id[1],] 
cid <- c(0,1,5,10)
fam.cancer.data <- combinedata(fam.data, cancer.data)
risk.mpc(fam.cancer.data[[1]], cid, parameter.mpc)

wwylab/LFSPRO documentation built on Feb. 1, 2023, 1:05 a.m.