Methods for improving cancer surveillance data in American Indian and Alaska Native populations

David K. Espey, Charles L. Wiggins, Melissa A. Jim, Barry A. Miller, Christopher J. Johnson, Thomas Becker

Research output: Contribution to journalArticle

68 Citations (Scopus)

Abstract

BACKGROUND. The misclassification of race decreases the accuracy of cancer incidence data for American Indians and Alaska Natives (AI/ANs) in some central cancer registries. This article describes the data sources and methods that were used to address this misclassification and to produce the cancer statistics used by most of the articles in this supplement. METHODS. Records from United States cancer registries were linked with Indian Health Service (IHS) records to identify AI/AN cases that were misclassified as non-AI/AN. Data were available from 47 registries that linked their data with IHS, met quality criteria, and agreed to participate. Analyses focused on cases among AI/AN residents in IHS Contract Health Service Delivery Area (CHSDA) counties in 33 states. Cancer incidence and stage data were compiled for non-Hispanic whites (NHWs) and AI/ANs across 6 IHS regions of the United States for 1999 through 2004. RESULTS. Misclassification of AI/AN race as nonnative in central cancer registries ranged from 85 individuals in Alaska (3.4%) to 5297 individuals in the Southern Plains (44.5%). Cancer incidence rates among AI/ANs for all cancers combined were lower than for NHWs, but incidence rates varied by geographic region for AI/ANs. Restricting the rate calculations to CHSDA counties generally resulted in higher rates than those obtained for all counties combined. CONCLUSIONS. The classification of race for AI/AN cases in cancer registries can be improved by linking records to the IHS and stratifying by CHSDA counties. Cancer in the AI/AN population is clarified further by describing incidence rates by geographic region. Improved cancer surveillance data for AI/AN communities should aid in the planning, implementation, and evaluation of more effective cancer control and should reduce health disparities in this population.

Original languageEnglish (US)
Pages (from-to)1120-1130
Number of pages11
JournalCancer
Volume113
Issue number5 SUPPL.
DOIs
StatePublished - Sep 1 2008

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North American Indians
United States Indian Health Service
Population
Neoplasms
Contract Services
Catchment Area (Health)
Registries
Incidence
Alaska Natives
Information Storage and Retrieval

Keywords

  • Alaska Native
  • American Indian
  • Cancer
  • Health disparity
  • Incidence
  • Misclassification
  • National Program of Cancer Registries
  • Surveillance, Epidemiology, and End Results
  • United States

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Espey, D. K., Wiggins, C. L., Jim, M. A., Miller, B. A., Johnson, C. J., & Becker, T. (2008). Methods for improving cancer surveillance data in American Indian and Alaska Native populations. Cancer, 113(5 SUPPL.), 1120-1130. https://doi.org/10.1002/cncr.23724

Methods for improving cancer surveillance data in American Indian and Alaska Native populations. / Espey, David K.; Wiggins, Charles L.; Jim, Melissa A.; Miller, Barry A.; Johnson, Christopher J.; Becker, Thomas.

In: Cancer, Vol. 113, No. 5 SUPPL., 01.09.2008, p. 1120-1130.

Research output: Contribution to journalArticle

Espey, DK, Wiggins, CL, Jim, MA, Miller, BA, Johnson, CJ & Becker, T 2008, 'Methods for improving cancer surveillance data in American Indian and Alaska Native populations', Cancer, vol. 113, no. 5 SUPPL., pp. 1120-1130. https://doi.org/10.1002/cncr.23724
Espey, David K. ; Wiggins, Charles L. ; Jim, Melissa A. ; Miller, Barry A. ; Johnson, Christopher J. ; Becker, Thomas. / Methods for improving cancer surveillance data in American Indian and Alaska Native populations. In: Cancer. 2008 ; Vol. 113, No. 5 SUPPL. pp. 1120-1130.
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abstract = "BACKGROUND. The misclassification of race decreases the accuracy of cancer incidence data for American Indians and Alaska Natives (AI/ANs) in some central cancer registries. This article describes the data sources and methods that were used to address this misclassification and to produce the cancer statistics used by most of the articles in this supplement. METHODS. Records from United States cancer registries were linked with Indian Health Service (IHS) records to identify AI/AN cases that were misclassified as non-AI/AN. Data were available from 47 registries that linked their data with IHS, met quality criteria, and agreed to participate. Analyses focused on cases among AI/AN residents in IHS Contract Health Service Delivery Area (CHSDA) counties in 33 states. Cancer incidence and stage data were compiled for non-Hispanic whites (NHWs) and AI/ANs across 6 IHS regions of the United States for 1999 through 2004. RESULTS. Misclassification of AI/AN race as nonnative in central cancer registries ranged from 85 individuals in Alaska (3.4{\%}) to 5297 individuals in the Southern Plains (44.5{\%}). Cancer incidence rates among AI/ANs for all cancers combined were lower than for NHWs, but incidence rates varied by geographic region for AI/ANs. Restricting the rate calculations to CHSDA counties generally resulted in higher rates than those obtained for all counties combined. CONCLUSIONS. The classification of race for AI/AN cases in cancer registries can be improved by linking records to the IHS and stratifying by CHSDA counties. Cancer in the AI/AN population is clarified further by describing incidence rates by geographic region. Improved cancer surveillance data for AI/AN communities should aid in the planning, implementation, and evaluation of more effective cancer control and should reduce health disparities in this population.",
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N2 - BACKGROUND. The misclassification of race decreases the accuracy of cancer incidence data for American Indians and Alaska Natives (AI/ANs) in some central cancer registries. This article describes the data sources and methods that were used to address this misclassification and to produce the cancer statistics used by most of the articles in this supplement. METHODS. Records from United States cancer registries were linked with Indian Health Service (IHS) records to identify AI/AN cases that were misclassified as non-AI/AN. Data were available from 47 registries that linked their data with IHS, met quality criteria, and agreed to participate. Analyses focused on cases among AI/AN residents in IHS Contract Health Service Delivery Area (CHSDA) counties in 33 states. Cancer incidence and stage data were compiled for non-Hispanic whites (NHWs) and AI/ANs across 6 IHS regions of the United States for 1999 through 2004. RESULTS. Misclassification of AI/AN race as nonnative in central cancer registries ranged from 85 individuals in Alaska (3.4%) to 5297 individuals in the Southern Plains (44.5%). Cancer incidence rates among AI/ANs for all cancers combined were lower than for NHWs, but incidence rates varied by geographic region for AI/ANs. Restricting the rate calculations to CHSDA counties generally resulted in higher rates than those obtained for all counties combined. CONCLUSIONS. The classification of race for AI/AN cases in cancer registries can be improved by linking records to the IHS and stratifying by CHSDA counties. Cancer in the AI/AN population is clarified further by describing incidence rates by geographic region. Improved cancer surveillance data for AI/AN communities should aid in the planning, implementation, and evaluation of more effective cancer control and should reduce health disparities in this population.

AB - BACKGROUND. The misclassification of race decreases the accuracy of cancer incidence data for American Indians and Alaska Natives (AI/ANs) in some central cancer registries. This article describes the data sources and methods that were used to address this misclassification and to produce the cancer statistics used by most of the articles in this supplement. METHODS. Records from United States cancer registries were linked with Indian Health Service (IHS) records to identify AI/AN cases that were misclassified as non-AI/AN. Data were available from 47 registries that linked their data with IHS, met quality criteria, and agreed to participate. Analyses focused on cases among AI/AN residents in IHS Contract Health Service Delivery Area (CHSDA) counties in 33 states. Cancer incidence and stage data were compiled for non-Hispanic whites (NHWs) and AI/ANs across 6 IHS regions of the United States for 1999 through 2004. RESULTS. Misclassification of AI/AN race as nonnative in central cancer registries ranged from 85 individuals in Alaska (3.4%) to 5297 individuals in the Southern Plains (44.5%). Cancer incidence rates among AI/ANs for all cancers combined were lower than for NHWs, but incidence rates varied by geographic region for AI/ANs. Restricting the rate calculations to CHSDA counties generally resulted in higher rates than those obtained for all counties combined. CONCLUSIONS. The classification of race for AI/AN cases in cancer registries can be improved by linking records to the IHS and stratifying by CHSDA counties. Cancer in the AI/AN population is clarified further by describing incidence rates by geographic region. Improved cancer surveillance data for AI/AN communities should aid in the planning, implementation, and evaluation of more effective cancer control and should reduce health disparities in this population.

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