WISH: Cancer Incidence Modules

These modules provide statistics on Wisconsin resident cancer incidence (new cancers) based on data collected by the Wisconsin Cancer Reporting System (WCRS) as mandated by Wis. Stat. § 255.04, Cancer Reporting. WCRS receives reports of newly diagnosed cancers from Wisconsin hospitals, clinics, physician offices, and out-of-state central cancer registries.

Data include case counts, as well as crude and age-adjusted rates for incident cancer cases coded as in situ (non-malignant), invasive (malignant; primary site only), and non-malignant (including borderline and benign) central nervous system tumors according to the International Classification of Diseases for Oncology, Third Edition (ICD-O-3), with the following exceptions:

• In situ cancers of the cervix are not reported.​​
• Basal and squamous cell carcinomas of the skin are not reported, except when these occur on the skin of the genital organs.
• In situ cancers of the urinary bladder are re-coded as invasive behavior because the information that distinguishes between in situ and invasive bladder cancers is not always available or reliable. Stage for these cases remains coded as in situ.
• Cases with unknown age or with sex other than male or female are excluded.

Visit WISH Data Sources for the Cancer Incidence modules citation.

• Cancer Site: SEER Recodes Site Recode ICD-O-3/WHO 2008 are used to classify cancer site selections available in these modules.
• Crude Incidence Rate: the total number of new cancer cases diagnosed in a specific year in the population category of interest, divided by the at-risk population for that category and multiplied by 100,000. WISH Cancer Incidence Modules use the SEER U.S. County Population Data, County-Level Population Files-19 Age Groups (Wisconsin) to define at-risk population denominators.
• Age-adjusted Incidence Rate: the cancer incidence rate adjusted to account for different age distributions between populations. Rates are age-adjusted using the 2000 U.S. standard population using the direct method of calculating rates in the WISH Cancer Incidence Modules.
• Standard Population: a standard population for a geographic area, such as the U.S. or the world, is based on the proportions of the population falling into specific age groups. WISH Cancer Incidence modules use the SEER Standard Populations-19 Age Groups available online.
• Confidence Intervals: reflect the range of variation in estimating cancer incidence rates. WISH uses confidence intervals that are expected to include the true underlying rate 95% of the time. Age-adjusted rates are modified with the Tiwari et al., 2006 adjustment.
• Invasive: describes a malignant cancer or tumor that has spread beyond the layer of tissue in which it developed and is growing into surrounding, healthy tissues. Generally, the invasive stages are either "localized," "regional," or "distant."
• Stage at Diagnosis/Summary Stage: stage measures how far a cancer has spread from its origin. The WISH Cancer Incidence Modules use the Summary Stage system that aligns with the CDC's National Program of Central Cancer Registries and the National Cancer Institute's Surveillance, Epidemiology, and End Results Program to characterize cancers as in situ, localized, regional, or distant.
  • In situ cancer is a small, early cancer that is confined to the cells in which the cancer began and that has not invaded or penetrated the surrounding tissue.
  • Localized cancer is confined to the primary site.
  • Regional cancer has spread beyond the primary site (regional extension) or to regional lymph nodes.
  • Distant cancer has spread to other organs (distant extension) or remote lymph nodes.
  • Some cancers are unstaged, or the stage is unknown or unspecified.

These modules include new cancer cases diagnosed in 2020 and 2021, the first and second years of the COVID-19 pandemic. The COVID-19 pandemic disrupted health services, leading to delays and reductions in cancer screening and diagnosis. This may have contributed to lower incidence for most cancer sites in 2020. The number of new cases diagnosed in 2021 are still a little lower for some cancer types but have returned to pre-pandemic counts for other cancer types.

Data users should acknowledge COVID-19 impacts on cancer incidence data when querying 2020 and 2021 years of diagnosis.

Race and Hispanic ethnicity information available in these modules are primarily based on information collected at diagnosis, typically from medical records. This means they often reflect health care records or patient self-report when available, but consistency and completeness can vary. To improve accuracy and standardization:

• The Indian Health Service (IHS) linkage process helps identify American Indian/Alaska Native individuals more accurately. This is done by linking cancer registry records with the IHS patient registration database to catch cases where American Indian/Alaska Native identity might not have been recorded in the medical record.
• The NAACCR Hispanic Identification Algorithm (NHIA) is used to enhance identification of Hispanic ethnicity. NHIA uses factors like surname, birthplace, and race/ethnicity information to more reliably assign Hispanic origin, especially when it's missing or ambiguous.

Data users should be cautious when interpreting race and ethnicity data due to potential misclassification and underreporting, particularly for American Indian/Alaska Native and Hispanic populations.

Data users should be aware that geographic boundaries can affect case ascertainment and data completeness. For example, underreporting from Minnesota facilities can lead to incomplete data for Wisconsin residents diagnosed or treated across the border, particularly in Division of Public Health Western Region counties. This can result in lower than expected case counts in those areas.

Additionally, smaller counties may show large fluctuations in incidence rates year to year, due to the small number of cases. This can make it difficult to interpret changes over time reliably.

Data users should interpret differences in cancer incidence rates between regions and counties with caution, especially when analyzing small populations or counties/regions along state borders.

Crude rates are influenced by the underlying age distribution of a population. Even if two geographies have the same age-adjusted rates, one with the relatively older population generally will have higher crude rates because incidence for most cancers increase with age. The age distribution of a population can change over time and can be different in different geographies. Age-adjusting rates ensures that differences in incidence between diagnosis years or geographies, are not due to differences in the age distribution of the populations being compared.

Most cancer rates published in major publications have been age-adjusted. This removes the effect of different age distributions between populations and allows for direct comparison. Age-adjusted rates produced from these modules should only be compared with another age-adjusted rate calculated by the same method, using the same U.S. standard population.

Confidence intervals for the age-adjusted rates were calculated with a method based on the gamma distribution (modified by Tiwari et al., 2006). This method produces valid confidence intervals even when the number of cases is very small. When the number of cases is large, the confidence intervals produced with the gamma method are equivalent to those produced with more traditional methods. Do not use overlapping confidence intervals to determine significant differences between two rates. This practice fails to detect significant differences more frequently than standard hypothesis testing.

When using these modules, be aware of key coding updates implemented that may affect counts and rates over time:

• 2000: cancer registries transitioned from ICD-O-2 to ICD-O-3 coding standards. This change impacted how certain cancers, particularly cervical, bladder, and hematopoietic cancers were classified. Users should interpret changes in incidence counts and rates around 2000 with caution, as changes may reflect coding updates.
• 2004: cancer registries began collecting information on non-malignant brain and other central nervous system tumors in accordance with Public Law 107-260, the Benign Brain Tumor Cancer Registries Amendment Act.
• 2007: new criteria were applied for determining when tumors are counted as new primaries. This affected case counts and rates by site marginally. For more information, visit SEER Training Major Changes.
• 2010: select lymphoma and leukemia ICD-O-3 codes were updated based on changes by the World Health Organization. Some cancers previously categorized as nonmalignant or premalignant are now considered malignant and reportable. Therefore, the counts for total cancers in Wisconsin are higher for years covered by ICD-O-3 due to changes in reporting requirements.

Data users should interpret data over time with these changes in mind, and consider focusing on consistent coding eras for more accurate comparisons.

WISH Cancer Incidence Modules automatically apply suppression when navigating within the queries:

• Cells with results of less than 6 cases are marked with an "X" to protect confidentiality and reduce risk of reidentification.
• Cells with results of a period (.) indicate there are zero cases.
• If all values in a row or column are zero, that row or column is not displayed.

Additionally, complementary suppression rules may be applied within modules by greying out selection options automatically. This prevents data users from returning rates informed by low counts considered unreliable, or subtracting cells to derive suppressed counts. For example, in the Cancer Incidence module, if you are attempting to query an individual county's age-adjusted incidence rate, you will only be able to select 5 or 10 year diagnosis year groups in Step 4.

WCRS cancer incidence data are dynamic, meaning they are continuously updated as new cases are reported, existing records are corrected, and additional information becomes available. WCRS follows national standards for quality and completeness, ensuring that finalized data are reliable and suitable for surveillance and public report.

For public data query systems like WISH, cancer incidence data are frozen and published annually to create a stable, consistent dataset for comparison across years. The annual freeze ensures that data users are working with a standardized version of the data. However, because cancer incidence data are dynamic, data users should keep in mind that counts and rates for the most recent diagnosis years may be underestimates and should be interpreted with caution.

• Start by selecting one of the measures offered within each module. All modules offer total number of cases. The Cancer Incidence module also offers crude and age-adjusted incidence rates.
• Follow the remaining steps to select cancer(s) of interest, geographies, and other demographic criteria such as age at diagnosis, sex, and race/ethnicity.
• Important: if you are interested in sex-specific rates or percentages in the Cancer Incidence and Cancer Incidence by Invasive Stage modules, you will need to select Male and/or Female sex in Step 5 to select the appropriate population denominator. This is a common error made by data users when producing information on Male Prostate and Female Breast cancers.
• Outputs from these modules are presented in tabular format with details about the query selection above the results.
• Suppression is applied to cells with results of less than 6 cases. Cells are marked with an "X" to protect confidentiality and reduce risk of reidentification.
• To obscure the value of the suppressed cell, some results greater than 5 cases and corresponding rate or percent values may also be displayed as an "X."
• A period (.) indicates there are zero cases in that cell.
• If all values in a row or column are zero, that row or column is not displayed.
• To save or copy outputs, highlight the desired text, select EDIT, COPY. Then PASTE the output into your work processing or spreadsheet program.
• You can start a new query within the same module by clicking NEXT QUERY.