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Cancer. 2008 Sep 1;113(5 Suppl):1120-30. doi: 10.1002/cncr.23724.

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

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  • 1National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia. david.espey@ihs.gov

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.

PMID:
18720372
[PubMed - indexed for MEDLINE]
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