Comments (1)
some thoughts towards an example:
- observed rates of prostate cancer incidence are dramatically impacted by uptake of PSA screening. Rapid increase in PCa diagnoses were seen in early 90s with introduction of the test, followed by a steady decrease after a large pool of previously undiagnosed cancers were detected.
- the above is true for all PCa cancers, but I bet if you stratify by stage/grade, you'll see a drop in the detection of high stage/grade cancers (and an increase in low risk cancers) since the early 90's
- those trends are very likely to be different for black vs white men, since black men are approx 1.5 times more likely to be diagnosed and >2 times as likely to die from PCa. Overlaid on that observed disparity is the fact that access to care (and hence, PSA screening) for these two groups has been different over time.
- Interestingly, Florida has a unique population distribution in a spatial sense. Though the above statement is true for racial disparities overall, you may not see the same thing in certain rural counties. For example, Polk county has poor health outcomes by several metrics without a substantial minority population.
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Related Issues (20)
- mixed-up columns in example data
- Tidyeval Principles
- recode_age_groups() should navigate around grouped data frames
- count_fcds() shortcuts for sex, race, origin HOT 1
- Document the recoding report
- Move SEER data into separate package
- Add test to catch that population data matches all years HOT 1
- Use IACR ICD-O-3 list HOT 1
- Document that age_adjust() needs counties if not Florida
- Unable to install package HOT 2
- Update for compatibility with tidyr v1.0.0 HOT 1
- if_else failing because of factor/character conversion
- add county = TRUE to count_fcds()
- Add count_filter_fcds() that does counting and filtering together HOT 1
- Typos SEER FL pop loading script
- Add option to exclude seer_stage == "In Situ" to count_fcds()
- Age_adjustment() to output warning message for dropping cases
- Incompatible types under 'age_group'? HOT 8
- separate_age_groups() fails ungracefully when it age groups aren't separable
- Discrepancy in counting female population when using age_adjust() for "Cervix Uteri" HOT 1
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