Concordance of cancer registry and self-reported race, ethnicity, and cancer type: a report from the American Cancer Society’s studies of cancer survivors
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To examine the concordance between cancer registry and self-reported data for race, Hispanic ethnicity, and cancer type in the American Cancer Society’s Studies of Cancer Survivors (SCS) I and II.
We calculated sensitivity, specificity, positive predictive value, and Kappa statistics for SCS-I and II. The gold standard for cancer type was registry data and for race and ethnicity was self-reported questionnaire data.
Among 6,306 survivors in SCS-I and 9,170 in SCS-II, overall agreement (Kappa) for cancer type was 0.98 and 0.99, respectively. Concordance was strongest for breast and prostate cancer (Sensitivity ≥ 0.98 in SCS-I and II). For race, Kappa was 0.85 (SCS-I) and 0.93 (SCS-II), with strong concordance for white (Sensitivity = 0.95 in SCS-I and 0.99 in SCS-II) and black survivors (Sensitivity = 0.94 in SCS-I and 0.99 in SCS-II), but weak concordance for American Indian/Alaska Native (Sensitivity = 0.23 in SCS-I and 0.19 in SCS-II) and Asian/Pacific Islander survivors (Sensitivity = 0.43 in SCS-I and 0.87 in SCS-II). Agreement was moderate for Hispanic ethnicity (Kappa = 0.73 and 0.71; Sensitivity = 0.74 and 0.76, in SCS-I and SCS-II, respectively).
We observed strong concordance between cancer registry data and self-report for cancer type in this national sample. For race and ethnicity, however, concordance varied significantly, with the poorest concordances observed for American Indian/Alaska Native and Asian/Pacific Islander survivors. Ensuring accurate recording of race/ethnicity data in registries is crucial for monitoring cancer trends and addressing cancer disparities among cancer survivors.
KeywordsCancer registries Cancer survivors Self-report Disparities Race Ethnicity
We wish to acknowledge the cooperation and efforts of the cancer registries and public health departments from the states of Alabama, Arizona, California (Regions 2–6), Colorado, Connecticut, Delaware, Illinois, Iowa, Idaho, Maine, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, Ohio, Pennsylvania, Rhode Island, South Carolina, Washington, and Wyoming. We also thank the staff of the hundreds of hospitals, including Stamford Hospital, which reported cases to the participating cancer registries. Certain data used in this study were obtained from the Connecticut Tumor Registry located in the Connecticut Department of Public Health. Lastly, we are grateful to the thousands of cancer survivors, their physicians, and their loved ones who contributed to the collection of these data. The authors assume full responsibility for analyses and interpretation of these data.
The American Cancer Society (ACS) Studies of Cancer Survivors (SCS) was supported by the intramural program of research conducted by the ACS Behavioral Research Center.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
- 6.de Moor JS, Mariotto AB, Parry C, Alfano CM, Padgett L, Kent EE, Forsythe L, Scoppa S, Hachey M, Rowland JH (2013) Cancer survivors in the United States: prevalence across the survivorship trajectory and implications for care. Cancer epidemiology, biomarkers & prevention: a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 22 (4):561–570. https://doi.org/10.1158/1055-9965.EPI-12-1356
- 14.Clegg LX, Reichman ME, Hankey BF, Miller BA, Lin YD, Johnson NJ, Schwartz SM, Bernstein L, Chen VW, Goodman MT, Gomez SL, Graff JJ, Lynch CF, Lin CC, Edwards BK (2007) Quality of race, Hispanic ethnicity, and immigrant status in population-based cancer registry data: implications for health disparity studies. Cancer Causes Control 18(2):177–187. https://doi.org/10.1007/s10552-006-0089-4 CrossRefPubMedGoogle Scholar
- 18.Ryerson AB, Eheman CR, Altekruse SF, Ward JW, Jemal A, Sherman RL, Henley SJ, Holtzman D, Lake A, Noone AM, Anderson RN, Ma J, Ly KN, Cronin KA, Penberthy L, Kohler BA (2016) Annual report to the nation on the status of Cancer, 1975–2012, featuring the increasing incidence of liver cancer. Cancer 122(9):1312–1337. https://doi.org/10.1002/cncr.29936 CrossRefPubMedPubMedCentralGoogle Scholar
- 19.Mai PL, Garceau AO, Graubard BI, Dunn M, McNeel TS, Gonsalves L, Gail MH, Greene MH, Willis GB, Wideroff L (2011) Confirmation of family cancer history reported in a population-based survey. J Natl Cancer Inst 103(10):788–797. https://doi.org/10.1093/jnci/djr114 CrossRefPubMedPubMedCentralGoogle Scholar
- 21.Navarro C, Chirlaque MD, Tormo MJ, Perez-Flores D, Rodriguez-Barranco M, Sanchez-Villegas A, Agudo A, Pera G, Amiano P, Dorronsoro M, Larranaga N, Quiros JR, Ardanaz E, Barricarte A, Martinez C, Sanchez MJ, Berenguer A, Gonzalez CA (2006) Validity of self reported diagnoses of cancer in a major Spanish prospective cohort study. J Epidemiol Community Health 60(7):593–599. https://doi.org/10.1136/jech.2005.039131 CrossRefPubMedPubMedCentralGoogle Scholar
- 23.Office of Management and Budget (1997) Revisions to the standard for the classification of federal data on race and ethnicity. Fed Reg 62(210):58782–58790Google Scholar
- 26.Hoopes MJ, Taualii M, Weiser TM, Brucker R, Becker TM (2010) Including self-reported race to improve cancer surveillance data for American Indians and Alaska Natives in Washington state. J Reg Manag 37(2):43–48Google Scholar
- 29.Hsieh MC, Pareti LA, Chen VW (2011) Using NAPIIA to improve the accuracy of Asian race codes in registry data. J Reg Manag 38(4):190–195Google Scholar
- 30.Watson PF, Petrie A (2010) Method agreement analysis: a review of correct methodology. Theriogenology 73(9):1167–1179. https://doi.org/10.1016/j.theriogenology.2010.01.003 CrossRefPubMedGoogle Scholar
- 37.Johnson JC, Soliman AS, Tadgerson D, Copeland GE, Seefeld DA, Pingatore NL, Haverkate R, Banerjee M, Roubidoux MA (2009) Tribal linkage and race data quality for American Indians in a state cancer registry. Am J Prev Med 36(6):549–554. https://doi.org/10.1016/j.amepre.2009.01.035 CrossRefPubMedPubMedCentralGoogle Scholar
- 39.Gomez SL, Glaser SL, Kelsey JL, Lee MM (2004) Bias in completeness of birthplace data for Asian groups in a population-based cancer registry (United States). Cancer Causes Control 15(3):243–253. https://doi.org/10.1023/b:caco.0000024244.91775.64 CrossRefPubMedGoogle Scholar
- 42.Klinger EV, Carlini SV, Gonzalez I, Hubert SS, Linder JA, Rigotti NA, Kontos EZ, Park ER, Marinacci LX, Haas JS (2015) Accuracy of race, ethnicity, and language preference in an electronic health record. J Gen Intern Med 30(6):719–723. https://doi.org/10.1007/s11606-014-3102-8 CrossRefPubMedGoogle Scholar
- 43.IOM (Institute of Medicine) (2009) Race, ethnicity, and language data: standardization for health care quality improvement. IOM (Institute of Medicine), Washington, DCGoogle Scholar
- 44.Group NRaEW (2011) NAACCR guideline for enhancing hispanic/latino identification: revised NAACCR Hispanic/Latino identification algorithm. vol Hispanic/Latino identification: revised NAACCR Hispanic/Latino identification algorithm [NHIA v2.2.1]. SpringfieldGoogle Scholar
- 45.Group NRaEW NAACCR Asian Pacific Islander Identification Algorithm [NAPIIA v1.2.1]. SpringfieldGoogle Scholar
- 46.Colby SL, Ortman JM (2014) Projections of the size and composition of the U.S. population: 2014–2060Google Scholar
- 48.Torre LA, Sauer AM, Chen MS Jr, Kagawa-Singer M, Jemal A, Siegel RL (2016) Cancer statistics for Asian Americans, Native Hawaiians, and Pacific Islanders, 2016: converging incidence in males and females. CA Cancer J Clin 66(3):182–202. https://doi.org/10.3322/caac.21335 CrossRefPubMedPubMedCentralGoogle Scholar