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 15.1 million in 2015.1
Definition and Calculation of Relative Cancer Survival
The relative cancer survival rate 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. The relative cancer survival rate 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
Cancer incidence data submitted to National Program of Cancer Registries (NPCR) as of November 30, 2017, were used to create a data set in SEER*Stat for this analysis.2 The data set included data from 39 NPCR central cancer registries that met the United States Cancer Statistics (USCS) publication criteria for all years 2001 through 2014 and that conducted linkage with the National Death Index and/or active patient follow-up for all years 2001 through 2014. These registries include Alabama, Alaska, Arizona, Arkansas, California, Colorado, Delaware, Georgia, Idaho, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maine, Maryland, Minnesota, Mississippi, Missouri, Montana, Nebraska, New Hampshire, New Jersey, New York, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, Tennessee, Texas, Utah, Vermont, Washington, West Virginia, Wisconsin, and Wyoming. These data cover 81% of the U.S. population.
Cases from these registries were included in the analysis if—
- The case was an invasive cancer diagnosed from 2001 through 2014. Cases diagnosed in 2015 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.
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, 2014. 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 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, but if diagnosed at different ages, each cancer was included in the calculation.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 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 other), and age group (younger than 45, 45 to 54, 55 to 64, 65 to 74, 75 or older). The other races group contains Indian Health Service-linked American Indian, Alaska Native, and Asian/Pacific Islander cases. See Measures of Cancer SurvivalExternal 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
- Noone AM, Howlader N, Krapcho M, Miller D, Brest A, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds). SEER Cancer Statistics Review, 1975–2015, National Cancer Institute. Bethesda, MD, http://seer.cancer.gov/csr/1975_2015/,External based on November 2017 SEER data submission, posted to the SEER Web site, April 2018.
- NPCR survival analytical database, Submission 2016 November, 2001–2013, 34 NPCR states.
- 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.
- Lee ET. Life-table analysis. In: Statistical Methods for Survival Data Analysis, 2nd ed. New York, NY: John Wiley & Sons, 1992: 78–100.
- 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.
- 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. Surveillance Research Program, National Cancer Institute; 2011. Technical Report #2011-01. Available from: http://surveillance.cancer.gov/reports/.External
- 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.