Retrieving Data
The Cancer Mortality category of cancerprof contains a single functions to pull data from the Mortality page of State Cancer Profile.
The function for retrieving incidence data is
mortality_cancer()
Mortality Cancer
Mortality cancer has 22 cancer types to choose from. In total, incidence cancer has 7 arguments: area, areatype, cancer, race, sex, age, year
Argument Details
The
"latest single year (us by state)"argument for year can only be selected ifareais"state"-
For the following cancer types:
- “breast (female)”,
- “ovary”,
- “uterus (corpus & uterus, nos)”
The
sexargument must by"females" For
"prostate"cancer, sex must be"males"For
"childhood (ages <15, all sites)", age must be"ages <15"For
"childhood (ages <20, all sites)", age must be"ages <20"
Examples
mortality1 <- mortality_cancer(
area = "wa",
areatype = "county",
cancer = "all cancer sites",
race = "black (non-hispanic)",
sex = "both sexes",
age = "ages 65+",
year = "latest 5 year average"
)
head(mortality1, n = 3)
#> County FIPS Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate CI_Rank Lower_CI_Rank
#> 1 Yakima County 53077 No 1676.3 947.3 2727.3 1 1
#> 2 Thurston County 53067 No 1187.5 791.2 1704.8 2 1
#> 3 Pierce County 53053 No 1099.3 971.9 1238.8 3 1
#> Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend
#> 1 5 3 <NA> NA NA NA
#> 2 7 7 <NA> NA NA NA
#> 3 5 59 falling -0.9 -1.7 -0.1
mortality2 <- mortality_cancer(
area = "usa",
areatype = "state",
cancer = "prostate",
race = "all races (includes hispanic)",
sex = "males",
age = "ages 50+",
year = "latest single year (us by state)"
)
head(mortality2, n = 3)
#> State FIPS Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate CI_Rank
#> 1 District of Columbia 11001 No 98.9 77.6 124.1 1
#> 2 Colorado 08000 No 86.1 79.3 93.3 2
#> 3 Vermont 50000 No 84.4 67.8 103.9 3
#> Lower_CI_Rank Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend
#> 1 1 35 76 falling -3.3 -3.9 -2.8
#> 2 1 9 623 stable -0.1 -1.0 0.9
#> 3 1 46 93 stable 4.7 -3.8 13.9
mortality3 <- mortality_cancer(
area = "wa",
areatype = "hsa",
cancer = "ovary",
race = "all races (includes hispanic)",
sex = "females",
age = "ages 50+",
year = "latest 5 year average"
)
head(mortality3, n = 3)
#> Health_Service_Area HSA_Code Met Healthy People Objective of ***? Age_Adjusted_Death_Rate Lower_95%_CI_Rate Upper_95%_CI_Rate
#> 1 Clallam, WA - Jefferson, WA 0785 *** 34.6 26.3 44.8
#> 2 Whatcom, WA 0815 *** 31.4 24.2 40.0
#> 3 Pierce, WA 0794 *** 24.6 21.1 28.6
#> CI_Rank Lower_CI_Rank Upper_CI_Rank Annual_Average_Count Recent_Trend Recent_5_Year_Trend Lower_95%_CI_Trend Upper_95%_CI_Trend
#> 1 1 1 4 12 stable -1.0 -2.4 0.3
#> 2 2 1 6 14 stable -0.7 -2.1 0.7
#> 3 3 2 9 36 falling -1.4 -2.0 -0.9