The goal of EndoTools is to provide helper tools for calculating commonly used variables in endometrial cancer projects such as:
- MMR
- ProMisE
- ESMO
There are different versions for each molecular variable.
Installation
You can install EndoTools from GitHub with:
# install.packages("remotes")
remotes::install_github("TalhoukLab/EndoTools")Example
This is a basic example which shows you how to assign and compare different ESMO risk groups:
library(EndoTools)
library(dplyr)
df <- emdb |>
mutate(
eclass2 = assign_promise2019(mmr_ihc_2, pole_mut, p53),
esmo2013 = assign_esmo2013(stage_full, grade_rev, hist_rev_gr),
esmo2016 = assign_esmo2016(stage_full, grade_rev, hist_rev_gr, myo, lvi),
esmo2020 = assign_esmo2020(stage_full, grade_rev, hist_rev_gr, myo, lvi, eclass2,
residual)
)
df |>
count(esmo2013)
#> # A tibble: 4 × 2
#> esmo2013 n
#> <fct> <int>
#> 1 low 89
#> 2 intermediate 117
#> 3 high 425
#> 4 <NA> 169
df |>
count(esmo2016)
#> # A tibble: 8 × 2
#> esmo2016 n
#> <fct> <int>
#> 1 low 46
#> 2 intermediate 21
#> 3 high-intermediate 99
#> 4 high 370
#> 5 advanced/metastatic 51
#> 6 advanced 12
#> 7 metastatic 6
#> 8 <NA> 195
df |>
count(esmo2020)
#> # A tibble: 8 × 2
#> esmo2020 n
#> <fct> <int>
#> 1 low 75
#> 2 intermediate 60
#> 3 high-intermediate 81
#> 4 high 201
#> 5 advanced/metastatic 37
#> 6 advanced 25
#> 7 metastatic 6
#> 8 <NA> 315
df |>
count(esmo2013, esmo2016, esmo2020)
#> # A tibble: 56 × 4
#> esmo2013 esmo2016 esmo2020 n
#> <fct> <fct> <fct> <int>
#> 1 low low low 24
#> 2 low low intermediate 1
#> 3 low low <NA> 11
#> 4 low intermediate low 14
#> 5 low intermediate <NA> 2
#> 6 low high-intermediate low 3
#> 7 low high-intermediate intermediate 2
#> 8 low high-intermediate high-intermediate 18
#> 9 low high-intermediate high 1
#> 10 low high-intermediate <NA> 6
#> # ℹ 46 more rows
