Literature DB >> 30392148

Concordance of cancer registry and self-reported race, ethnicity, and cancer type: a report from the American Cancer Society's studies of cancer survivors.

Tracy M Layne1, Leah M Ferrucci2, Beth A Jones2, Tenbroeck Smith3, Lou Gonsalves4, Brenda Cartmel2.   

Abstract

PURPOSE: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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.

Entities:  

Keywords:  Cancer registries; Cancer survivors; Disparities; Ethnicity; Race; Self-report

Mesh:

Year:  2018        PMID: 30392148     DOI: 10.1007/s10552-018-1091-3

Source DB:  PubMed          Journal:  Cancer Causes Control        ISSN: 0957-5243            Impact factor:   2.506


  3 in total

1.  Comparing medical history data derived from electronic health records and survey answers in the All of Us Research Program.

Authors:  Lina Sulieman; Robert M Cronin; Robert J Carroll; Karthik Natarajan; Kayla Marginean; Brandy Mapes; Dan Roden; Paul Harris; Andrea Ramirez
Journal:  J Am Med Inform Assoc       Date:  2022-06-14       Impact factor: 7.942

2.  Family as a Bridge to Improve Meaning in Latinx Individuals Coping with Cancer.

Authors:  Normarie Torres-Blasco; Rosario Costas-Muñiz; Carolina Zamore; Laura Porter; Maria Claros; Guillermo Bernal; Megan J Shen; William Breitbart; Lianel Rosario; Cristina Peña-Vargas; Eida M Castro-Figueroa
Journal:  Palliat Med Rep       Date:  2022-09-05

Review 3.  Indigenous health equity in health register ascertainment and data quality: a narrative review.

Authors:  Karen Wright; Rachel M Tapera; N Susan Stott; Alexandra Sorhage; Anna Mackey; Sîan A Williams
Journal:  Int J Equity Health       Date:  2022-03-12
  3 in total

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