Rate/Trend Comparison by Cancer Table
| Above US Rate | Similar to US Rate | Below US Rate | |
|---|---|---|---|
| Rising Trend |
Priority 1: rising  and above Hanson County Todd County |
Priority 2: rising and similar  |
Priority 3: rising and below  |
| Stable Trend |
Priority 4: stable  and above Butte County Dewey County Lyman County McCook County Mellette County |
Priority 6: stable and similar Aurora County Bennett County Bon Homme County Charles Mix County Clark County Clay County Corson County Douglas County Fall River County Faulk County Gregory County Haakon County Hamlin County Hand County Hughes County Jackson County Lake County Marshall County Miner County Moody County Perkins County Potter County Sully County Turner County |
Priority 7: stable and below Campbell County Lincoln County McPherson County |
| Falling Trend |
Priority 5: falling and above Minnehaha County |
Priority 8: falling and similar Beadle County Brookings County Brown County Brule County Codington County Custer County Davison County Day County Deuel County Edmunds County Grant County Hutchinson County Kingsbury County Lawrence County Meade County Pennington County Roberts County Sanborn County Stanley County Tripp County Union County Walworth County |
Priority 9: falling and below Spink County Yankton County |
| Notes: Created by statecancerprofiles.cancer.gov on 07/15/2025 7:04 pm. South Dakota County Name Change: please note that Shannon County, SD (FIPS code=46113) was renamed effective May 1, 2015, and the new name is Oglala Lakota County (FIPS Code=46102). This website now uses Oglala Lakota. Trend2 Rising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.Rate Comparison Above when 95% confident the rate is above and Rate Ratio3 > 1.10Similar when unable to conclude above or below with confidence.Below when 95% confident the rate is below and Rate Ratio3 < 0.901 Priority indices were created by ordering from rates that are rising and above the comparison rate to rates that are falling and below the comparison rate. 2 Recent trend in death rates is usually an Average Annual Percent Change (AAPC) based on the APCs calculated by Joinpoint Version 5.3.0. Due to data availability issues, the time period and/or calculation method used in the calculation of the trends may differ for selected geographic areas. 3 Rate ratio is the county rate divided by the US rate. Previous versions of this table used one-year rates for states and five-year rates for counties. As of June 2018, only five-year rates are used. Source: Death data provided by the National Vital Statistics System public use data file. Death rates calculated by the National Cancer Institute using SEER*Stat. Death rates are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). The Healthy People 2020 goals are based on rates adjusted using different methods but the differences should be minimal. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with mortality data. Note: When the population size for a denominator is small, the rates may be unstable. A rate is unstable when a small change in the numerator (e.g., only one or two additional cases) has a dramatic effect on the calculated rate. Suppression is used to avoid misinterpretation when rates are unstable. State Cancer Registries may provide more current or more local data. Data presented on the State Cancer Profiles Web Site may differ from statistics reported by the State Cancer Registries (for more information). Data for the following has been suppressed to ensure confidentiality and stability of rate and trend estimates: Harding County, Ziebach County Trend for the following could not be reliably determined due to small number of deaths per year: Buffalo County, Hyde County, Jerauld County, Jones County, Oglala Lakota County Interpret Rankings provides insight into interpreting cancer statistics. When the population size for a denominator is small, the rates may be unstable. A rate is unstable when a small change in the numerator (e.g., only one or two additional cases) has a dramatic effect on the calculated rate. Data for United States does not include Puerto Rico. |
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