Overview
canregtools is an R package designed to streamline data analysis, visualization, and reporting in Population-Based Cancer Registration (PBCR). It includes five sets of R functions that cover data reading, processing, statistical calculations, visualization, and reporting.
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read_canreg()read data formats required by the National Cancer Center in China to object with class ofcanregorcanregs. The raw data is stored in an Excel file containing three sheets named FB, SW, and POP, where FB represents incidence data, SW represents mortality data, and POP represents population data. -
count_canreg()convert object with class ofcanregorcanregsto object with class offbswicdorfbswicds. -
create_asr()calculate age-standardized rates (ASR), truncated rates and cumulative rates,create_quality()calculate quality indicators such as crude incidence or mortality, mortality to incidence ratio (M:I), percent of pathological verified cases (MV%), and etc. ,create_age_rate()calculate age specific rate. -
draw_pyramid()draw population pyramid,draw_linechart()draw line chart,draw_barchart()draw grouped bar chart. -
create_report()generate cancer registry report based on data of class “canreg” or “canregs”, the output file type can be Word, HTML, or PDF.
Installation
Currently, the package is not available on CRAN, but you can install the development version of canregtools from GitHub. The installation method is as follows:
## Install the remotes package
install.packages("remotes")
library(remotes)
install_github("gigu003/canregtools")Usage
# Load sample data
library(canregtools)
data("canregs")
data <- canregs[[1]]
# Convert `canreg` to `fbswicd`
fbsw <- count_canreg(data, cancer_type = "big")
# 1. Age-standardized rate (ASR)
create_asr(fbsw, year, sex, cancer) |>
add_labels(lang = "en")
#> # A tibble: 84 × 14
#> year sex cancer site icd10 no_cases cr asr_cn2000 asr_wld85
#> <int> <fct> <chr> <fct> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 2021 Total 101 Oral Cavity & Ph… C00-… 38 5.53 3.74 3.79
#> 2 2021 Total 102 Nasopharynx C11 5 0.73 0.71 0.71
#> 3 2021 Total 103 Esophagus C15 59 8.58 4.53 4.85
#> 4 2021 Total 104 Stomach C16 123 17.9 11.1 11.2
#> 5 2021 Total 105 Conlon, Rectum &… C18-… 236 34.3 20.6 20.2
#> # ℹ 79 more rows
#> # ℹ 5 more variables: truncr_cn2000 <dbl>, truncr_wld85 <dbl>, cumur <dbl>,
#> # prop <dbl>, rank <int>
# 2. Quality indicators
create_quality(fbsw, cancer) |>
add_labels(label_type = "abbr", lang = "en")
#> # A tibble: 28 × 16
#> year sex cancer site icd10 rks fbs inci sws mort mi mv
#> <int> <fct> <chr> <fct> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 9000 Total 101 Oral Cavi… C00-… 687356 38 5.53 13 1.89 0.34 73.7
#> 2 9000 Total 102 Nasophary… C11 687356 5 0.73 0 0 0 40
#> 3 9000 Total 103 Esophagus C15 687356 59 8.58 50 7.27 0.85 74.6
#> 4 9000 Total 104 Stomach C16 687356 123 17.9 82 11.9 0.67 71.5
#> 5 9000 Total 105 Colorectum C18-… 687356 236 34.3 103 15.0 0.44 77.5
#> # ℹ 23 more rows
#> # ℹ 4 more variables: dco <dbl>, ub <dbl>, sub <dbl>, m8000 <dbl>
# 3. Age-specific rates
create_age_rate(fbsw) |>
add_labels(lang = "en")
#> # A tibble: 19 × 8
#> year sex cancer site icd10 agegrp cases rate
#> <int> <fct> <chr> <fct> <chr> <fct> <dbl> <dbl>
#> 1 9000 Total 60 All Cancers ALL 0 岁 3 44.3
#> 2 9000 Total 60 All Cancers ALL 1-4 岁 12 31.4
#> 3 9000 Total 60 All Cancers ALL 5-9 岁 9 16.4
#> 4 9000 Total 60 All Cancers ALL 10-14 岁 13 32.5
#> 5 9000 Total 60 All Cancers ALL 15-19 岁 8 26.2
#> # ℹ 14 more rows
