ICCI

• This is an R package that calculates the Charlson Comorbidity Index (CCI) on longitudinal ICD data, using the R package comorbidity.
  • The data should have at least the columns ID and PRIMARY_ICD, and ICD_VERSION.
  • If you want to restrict the exposure period to calculate the index on, the data needs an additional column EVENT_AGE.
• The package can handle different ICD-versions for the same individual.
  • Possible entries for the column ICD_VERSION are "10", "10CM", "9", or "9CM".
• Can also be used to calculate a medication score for data with ATC codes and associated weights.

R package Dependencies

• assertthat (For testing)
• comorbidity (>= 1.0.0, For calculating the CCI)
• dplyr (For data manipulation)
• tibble (For better data.frames)

Installation

You can install the development version of ICCI from GitHub with:

# install.packages("devtools")
devtools::install_github("dsgelab/ICCI")

In FinnGen you can find the ICCI and comorbidity packages at /finngen/shared/icci_pckg_share/20241108_090028/files/detrois_share/packages or alternatively upload the package from this repository through green uploads.

Then in the Sandbox use i.e.

# In case the default R version is not the same as the one for which the package was build.
rpkgs_path <- "/path/to/installed/rpackges/for/this/version/" i.e. /home/ivm/R/x86_64-pc-linux-gnu-library/4.4
.libPaths(c(rpkgs_path, .libPaths()))  
libpath <- .libPaths()[1]
install.packages("/finngen/shared/icci_pckg_share/20241108_090028/files/detrois_share/packages/ICCI_2.3.1.tar.gz",
                 rpkgs_path,
                 repos = NULL, 
                 type="source")

Also see: How to install a R package into Sandbox?.

Do the same for the comorbidity package. In FinnGen you can find it at /finngen/shared/icci_pckg_share/20241108_090028/files/detrois_share/packages/comorbidity_1.1.0.tar.gz.

Example

The data frame icd_data needs to contain the columns EVENT_AGE, PRIMARY_ICD, and ICD_VERSION.

library(dplyr)
library(tibble)
library(comorbidity)
library(ICCI)

file_name <- "/path/to/file/longitudinal_icd_data.txt"
icd_data <- readr::read_delim(file_name)
score_data <- ICCI::calc_cci(icd_data)
score_data_age_20_to_30 <- ICCI::calc_cci(icd_data, 
                                          exp_start=20,
                                          exp_end=30)

For variable exposure windows for different individuals there are two options:

1. Give either or both exp_start, and exp_end vectors of the exact same length as the original data with the different exposure periods. This is the ideal option if the start and end of the expsoure period are already part of the same data.frame as the ICD data.

mock_data <- tibble::tibble(ID=c("KT0000001", "KT0000002", "KT0000001"), 
                            EVENT_AGE=c(12.3, 89, 23.4), 
                            PRIMARY_ICD=c("Y728", "M797", "E283"), 
                            ICD_VERSION=c("10", "10", "10"),
                            EXP_START=c(10, 40, 10),
                            EXP_END=c(50, 70, 50))
ICCI::calc_cci(icd_data=mock_data,
               exp_start=mock_data$EXP_START,
               exp_end=mock_data$EXP_END)

2. Give both exp_start and exp_end a data.frame with each a column ID, and then EXP_START for the exp_start argument and EXP_END, for the exp_end argument. This way ensures that the exposures are mapped to the correct IDs. Thus, this is the better option if the information on the exposure window comes from another data source.

mock_data <- tibble::tibble(ID=c("KT0000001", "KT0000002", "KT0000001"), 
                            EVENT_AGE=c(12.3, 89, 23.4), 
                            PRIMARY_ICD=c("Y728", "M797", "E283"), 
                            secondary_ICD=c(NA, NA, NA), 
                            ICD_VERSION=c("10", "10", "10"))
EXP_START <- tibble::tibble(ID=c("KT0000001", "KT0000002"),
                            EXP_START=c(10, 40))
EXP_END <- tibble::tibble(ID=c("KT0000001", "KT0000002"),
                          EXP_END=c(50, 70))

ICCI::calc_cci(icd_data=mock_data,
               exp_start=EXP_START,
               exp_end=EXP_END)