Relative Cancer Survival

Surveillance of cancer incidence and survival are essential in monitoring and understanding CDC’s efforts to support the needs of cancer survivors, estimated to be 12.1 million in 2018.1

Definition and Calculation of Relative Cancer Survival

Relative cancer survival measures the proportion of people with cancer who will be alive at a certain time after diagnosis, given that they did not die from something other than their cancer. Relative cancer survival is defined as the ratio of the observed all-cause survival in a group of individuals with cancer to the expected all-cause survival of a similar group of individuals who do not have cancer.1 Because the expected survival of individuals who do not have cancer is difficult to obtain, it is often approximated by the expected all-cause survival of the general population. This is a reasonable approximation because cancer deaths are generally a negligible proportion of all deaths. Thus, the relative cancer survival is calculated as the observed all-cause survival in a group of individuals with cancer divided by the expected all-cause survival of the general population. To learn more on this topic, visit Measures of Cancer Survival.external icon

Cancer incidence data submitted to CDC’s National Program of Cancer Registries (NPCR) in the 2020 data submission period were used to create a data set in SEER*Stat for this analysis.2 The data set included data from 42 NPCR central cancer registries that met the United States Cancer Statistics (USCS) publication criteria for all years 2011 through 2017 and that conducted linkage with the National Death Index and/or active patient follow-up for all years 2011 through 2017. These registries include Alabama, Alaska, Arizona, Arkansas, California, Colorado, Delaware, Florida, Georgia, Idaho, Illinois, Kansas, Kentucky, Louisiana, Maine, Maryland, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Washington, West Virginia, Wisconsin, and Wyoming. These data cover 86% of the U.S. population.

Cases from these registries were included in the analysis if—

  • The case was an invasive cancer diagnosed from 2011 through 2017. Cases diagnosed in 2018 do not have adequate follow-up time to be included in the analysis.
  • The age of the case was known and was 0 through 99 years.
  • The sex of the case was known.
  • The case was not identified solely on the basis of a death certificate or autopsy.

Analytic Methods

Survival time in months for each case was calculated. Date of start of follow-up (month, day, and year) was set to date of diagnosis. Date of last follow-up (month, day, and year) was set to date of death if the case was matched to the state death files, to the National Death Index, or to date of last contact (if case was actively followed). Cases not linking to the state death files or to the National Death Index were presumed to be alive, and the date of last follow-up was set to December 31, 2017. Where day or month for date of diagnosis, date of death, or date of last contact were missing, the full date was imputed using a standard algorithm.3 Cases that survived past the maximum age (99 years) were censored at age 99. Observed all-cause survival by sex and race (White, Black, and all races combined) for individuals with any cancer and for individuals with 23 common cancer sites was then calculated using the actuarial life table method.4 Cases with multiple primary cancers were included in the dataset, although only the first primary cancer during the inclusion period was included in calculating relative survival for all cancer sites combined. Where a patient had multiple primary cancers of different sites, each cancer was included in calculating cancer-specific relative survival. Where a patient was diagnosed with multiple primary cancers of the same site at the same age, only the first primary cancer was included in calculating relative survival for that cancer site, and only one record per person will contribute to any life page (i.e. strata in a data visualization query).5

Expected all-cause survival for the general population by sex and race (White, Black, and all races combined) were obtained using annual U.S. life tables provided by the National Center for Health Statistics and modified by SEER. The life tables were embedded in SEER*Stat. See Expected Survival Life Tablesexternal icon for more information.

Relative cancer survival was then calculated using the Ederer II method6 for all cancer sites combined and for 23 common cancer sites by sex, race (all races combined, White, Black, and all other races), and age group (younger than 45 years, 45 to 54 years, 55 to 64 years, 65 to 74 years, and 75 years or older). The all other races group includes Indian Health Service-linked American Indian, Alaska Native, and Asian and Pacific Islander cases. Due to concerns related to the completeness and quality of Hispanic vital status information within the cancer registry database, survival information is not presented for this population. See Measures of Cancer Survivalexternal icon for more information.

The quality and completeness of individual data items used in this analysis are discussed in a study by Wilson and others.7

References

  1. U.S. Cancer Statistics Working Group. U.S. Cancer Statistics Data Visualizations Tool, based on 2020 submission data (1999–2018): U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute; www.cdc.gov/cancer/dataviz, June 2021.
  2. National Program of Cancer Registries SEER*Stat Database: NPCR Survival Analytic file 2001–2017 (42 NPCR central cancer registries). United States Department of Health and Human Services, Centers for Disease Control and Prevention. Released June 2021, based on the 2020 submission.
  3. Johnson CJ, Weir HK, Yin D, Niu X. The impact of patient follow-up on population-based survival rates. Journal of Registry Management 2010;37(3):86–103.
  4. Lee ET. Life-table analysis. In: Statistical Methods for Survival Data Analysis, 2nd ed. New York, NY: John Wiley & Sons, 1992: 78–100.
  5. Brenner H, Hakulinen T. Patients with previous cancer should not be excluded in international comparative cancer survival studies. International Journal of Cancer 2007;121(10):2274–2278.
  6. Cho H, Howlader N, Mariotto AB, Cronin KA. Estimating relative survival for cancer patients from the SEER Program using expected rates based on Ederer I versus Ederer II method. pdf icon[PDF-3MB]external icon Surveillance Research Program, National Cancer Institute; 2011. Technical Report #2011-01.
  7. Wilson RJ, O’Neil ME, Ntekop E, Zhang K, Ren Y. Coding completeness and quality of relative survival-related variables in the National Program of Cancer Registries Cancer Surveillance System, 1995–2008. Journal of Registry Management 2014;41(2):65–71.