University of Michigan School of Public Health, Ann Arbor, Michigan.
Cancer. 2014 Jun 15;120(12):1847-53. doi: 10.1002/cncr.28589. Epub 2014 Mar 26.
In American Indians (AIs), cancer is a leading cause of mortality, yet their disease burden is not fully understood due to unaddressed racial misclassification in cancer registries. This study describes cancer trends among AIs in Michigan, focusing on breast cancer, in a linked data set of Indian Health Service (IHS), tribal, and state cancer registry data adjusted for misclassification.
AI status was based on reported race and linkage to IHS data and tribal registries. Data with complete linkage on all incident cancer cases in Michigan from 1995 to 2004 was used to calculate age-standardized incidence estimates for invasive all-site and female breast cancers stratified by racial group. For female breast cancers, stage- and age-specific incidence and percent distributions of early- versus late-stage cancers and age of diagnosis were calculated.
More than 50% of all AI cases were identified through IHS and/or tribal linkage. In the linked data, AIs had the lowest rates of all-sites and breast cancer. For breast cancers, AI women had a greater late-stage cancer burden and a younger mean age of diagnosis as compared to whites. Although the age-specific rate for whites was greater than for AI women in nearly all age groups, the difference in hazard ratio increased with increasing age.
Our state-specific information will help formulate effective, tailored cancer prevention strategies to this population in Michigan. The data linkages used in our study are crucial for generating accurate rates and can be effective in addressing misclassification of the AI population and formulating cancer prevention strategies for AI nationwide.
在美国印第安人(AI)中,癌症是导致死亡的主要原因,但由于癌症登记处未解决的种族分类错误,他们的疾病负担并未得到充分了解。本研究在印第安卫生服务(IHS)、部落和州癌症登记处数据的链接数据集内,描述密歇根州 AI 中的癌症趋势,重点是乳腺癌,并针对分类错误进行了调整。
AI 状态基于报告的种族和与 IHS 数据以及部落登记处的联系。使用密歇根州 1995 年至 2004 年所有癌症发病病例的完整链接数据,计算出按种族分层的浸润性所有部位和女性乳腺癌的年龄标准化发病率估计值。对于女性乳腺癌,计算了各期和年龄特异性发病率以及早晚期癌症的百分比分布和诊断年龄。
超过 50%的 AI 病例是通过 IHS 和/或部落联系确定的。在链接数据中,AI 的所有部位和乳腺癌发病率最低。对于乳腺癌,与白人相比,AI 女性的晚期癌症负担更大,诊断年龄更小。尽管在几乎所有年龄组中,白人的年龄特异性发病率都大于 AI 女性,但风险比的差异随着年龄的增加而增加。
我们的州特定信息将有助于为密歇根州的这一人群制定有效的、有针对性的癌症预防策略。我们研究中使用的数据链接对于生成准确的发病率至关重要,可有效解决 AI 人群的分类错误,并为全国范围内的 AI 制定癌症预防策略。