Race & Breast Cancer Estrogen Receptor Status: Impact of Class and Missing Data

描述(由申请人提供)：尽管美国种族/民族群体在乳腺癌雌激素受体(ER)状态的分布上存在明显的科学共识，但以前对这一主题的研究受到以下限制：(1)ER状态未知的病例比例很大(通常为15-40%)。(2)社会经济数据匮乏。限制对社会经济地位的混淆的控制能力，以及(3)近乎排外地关注黑人/白人的差异。然而，证据表明：(A)有色人种和/或不太富裕的妇女中更容易缺少雌激素受体状态，并且(B)雌激素受体状态的风险因素本身可能是有社会模式的，例如，接受激素替代治疗的情况在过去40年中在白人和更富裕的妇女中更为常见，这表明根据这种数据估计雌激素状况的种族/族裔差异可能是有偏见的，可能会增加患上雌激素受体阳性肿瘤的可能性。由于ER状态是与乳腺癌治疗和生存相关的关键肿瘤生物标志物，因此准确衡量ER状态中种族/民族差异的估计是真实的还是有偏见的程度是重要的。因此，为了评估ER状态对乳腺癌ER状态和乳腺癌发病率的种族/民族差异的估计是否由于ER状态数据的缺失和对社会经济地位缺乏控制而产生偏见，我们将使用多变量和敏感性分析技术来分析一个基于多种族/民族的人口数据集，该数据集包含1998至2002年间发生在美国两个基于人口的癌症登记机构：洛杉矶癌症监测计划和北加州癌症中心的所有浸润性原发乳腺癌病例(n=42,240，其中包括26,491名非西班牙裔白人；4,102名黑人；4,961名西班牙裔，以及4,970名亚洲和太平洋岛民病例)。记录包括关于种族/民族、确诊年龄和肿瘤特征的数据，并与2000年人口普查地区的社会经济数据相联系。分析将：(1)评估种族/民族、社会经济地位、确诊年龄、肿瘤大小和肿瘤分期的ER状态(阳性、阴性或缺失)的分布，以估计ER状态在未知者中分布的概率；以及(2)使用多变量和敏感性分析，评估丢失ER数据和缺乏对社会经济地位的控制是否对按ER状态估计乳腺癌ER状态和乳腺癌发病率的种族/民族差异有偏见。结果将提供第一个证据，证明对ER状况的种族/族裔差异的估计是否由于缺少关于ER状况的数据和没有纳入社会经济数据而存在偏见，并将在一个大型的多种族/族裔队列中这样做。这些发现将提供解决健康差距所需的知识，这是国家癌症研究所、国家卫生研究院和2010年健康人的关键目标，同时还将解决PAR-04-159的目标，通过使用“现有数据”来确定“肿瘤起始和进展的生物标记物对流行病学研究的适用性”。

DESCRIPTION (provided by applicant): Despite an apparent scientific consensus that US racial/ethnic groups have disparate distributions of breast cancer estrogen receptor (ER) status, previous studies of this topic are limited by: (1) the sizable proportion of cases with unknown ER status (typically 15-40%). (2) the paucity of socioeconomic data. limiting ability to control for confounding by socioeconomic position, and (3) the near exclusive focus on black/white differences. Suggesting, however, that estimates of racial/ethnic disparities in ER status based on such data might be biased, evidence indicates: (a) ER status is more frequently missing among women of color and/or less affluent women, and (b) risk factors for ER status may themselves be socially patterned, e.g., exposure to hormone replacement therapy, for the last 40 years more common among white and more affluent women, may increase likelihood of developing an ER-positive tumor. Because ER status is a key tumor biomarker relevant to both breast cancer treatment and survival, it is important to gauge accurately the extent to which estimates of racial/ethnic disparities in ER status are real or biased. Accordingly, to assess whether estimates of racial/ethnic disparities in breast cancer ER status and incidence of breast cancer by ER status are biased by missing data on ER status and lack of control for socioeconomic position, we will employ multivariate and sensitivity analysis techniques to analyze a multi- racial/ethnic population-based data set consisting of all incident cases of invasive primary breast cancer among women (n = 42,240 including 26,491 white non-Hispanic; 4,102 black; 4,961 Hispanic, and 4,970 Asian and Pacific Islander cases) occurring between 1998 and 2002 and included in the records of two US population-based cancer registries: the Los Angeles Cancer Surveillance Program and the Northern California Cancer Center. Records include data on race/ethnicity, age at diagnosis, and tumor characteristics and are linked to 2000 census tract socioeconomic data. Analyses will: (1) assess the distribution of ER status (positive, negative, or missing) by race/ethnicity, socioeconomic position, age at diagnosis, and tumor size and tumor stage, to estimate probabilities for the distribution of ER status among those within unknown status; and (2) using multivariate and sensitivity analysis, assess whether missing ER data and lack of control for socioeconomic position bias estimates of racial/ethnic disparities in breast cancer ER status and breast cancer incidence by ER status. Results will provide the first evidence whether estimates of racial/ethnic disparities in ER status are biased due to missing data on ER status and lack of inclusion of socioeconomic data, and will do so in a large multi-racial/ethnic cohort. Findings will provide knowledge needed to address health disparities, a key objective of the National Cancer Institute, the National Institutes of Health, and Healthy People 2010, while also addressing the objectives of PAR- 04-159, by using "existing data" to determine "applicability of biomarkers of tumor initiation and progression for epidemiologic studies."