Description Usage Format Details Source See Also Examples
CI5 XI summary database.
1 | data("csu_CI5XI_data")
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A data frame with 1113210 observations on the following 10 variables.
registry_code
Registry code (integer)
registry_label
Name of the registry (character)
sex
sex (integer)
cancer_code
cancer code (integer)
cancer_label
cancer label (character)
age
age variable from 1 to 19. 1 is 0-4 years, 2 is 5-9, etc..., 17 is 80-84, 18 is 85+, 19 represents missing age. (integer)
cases
Number of cases (incidence) (integer)
py
Population-year: Reference population of the registry (integer)
CI5_continent
Continent code (integer)
ethnic_group
ethnic code (integer)
All information are available here: http://ci5.iarc.fr/CI5-XI/Default.aspx
http://ci5.iarc.fr/CI5-XI/Default.aspx
csu_asr
csu_cumrisk
csu_eapc
csu_ageSpecific
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | data("csu_CI5XI_data")
#get the registry code asssociate to registry_label
#print(unique(csu_CI5XI_data[,c("registry_code", "registry_label" )]),nrows = 1000)
#get the cancer code asssociate to cancer_label
#print(unique(csu_CI5XI_data[,c("cancer_label", "cancer_code")]),nrows = 1000)
#remove all cancers:
df_data <- subset(csu_CI5XI_data ,cancer_code < 62)
#change group_by option to factor
df_data$sex <- factor(df_data$sex, levels=c(1,2), labels=c("Male", "Female"))
#select Thailand changmai
df_data_1 <- subset(df_data, registry_code==764001)
dt_result_1 <- csu_ageSpecific_top(df_data_1,
var_age="age",
var_cases="cases",
var_py="py",
var_top="cancer_label",
group_by="sex",
plot_title= "Thailand, Chiangmai",
plot_subtitle = "Top 5 cancer",
missing_age = 19)
#select USA
df_data_2 <- subset(df_data,registry_code== 840000 & ethnic_group == 99)
dt_result_2 <- csu_ageSpecific_top(df_data_2,
var_age="age",
var_cases="cases",
var_py="py",
var_top="cancer_label",
group_by="sex",
plot_title= "USA",
plot_subtitle = "Top 5 cancer",
missing_age = 19)
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