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

描述（由申请人提供）：尽管美国人种/种族群体具有不同的乳腺癌雌激素受体（ER）状态分布这一明显的科学共识，但该主题的既往研究受到以下限制：（1）相当大比例的病例ER状态未知（通常为15-40%）。(2)社会经济数据的缺乏。限制了控制社会经济地位混杂因素的能力，以及（3）几乎只关注黑人/白色差异。然而，基于这些数据对ER状态的种族/民族差异的估计可能有偏见，证据表明：（a）ER状态在有色人种和/或不太富裕的女性中更经常缺失，（B）ER状态的风险因素本身可能是社会模式的，例如，在过去的40年里，激素替代疗法在白色和更富裕的女性中更为常见，这可能会增加发生ER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，因此准确评估ER状态中种族/民族差异的估计值是真实的还是有偏倚的是很重要的。因此，为了评估乳腺癌ER状态的种族/民族差异和ER状态的乳腺癌发病率的估计值是否因ER状态的缺失数据和缺乏对社会经济地位的控制而存在偏倚，我们将采用多变量和敏感性分析技术来分析多种族/民族人群数据集，该数据集由女性中所有侵袭性原发性乳腺癌的发病病例组成（n = 42，240例，包括26，491例非西班牙裔白色白人; 4，102例黑人; 4，961例西班牙裔和4，970例亚洲和太平洋岛民病例）发生于1998年至2002年，并纳入两个美国基于人群的癌症登记处的记录：洛杉矶癌症监测项目和北方加州癌症中心。记录包括种族/民族，诊断年龄和肿瘤特征的数据，并与2000年人口普查区域的社会经济数据相关联。分析将：（1）评估ER状态的分布根据人种/种族、社会经济地位、诊断时的年龄以及肿瘤大小和肿瘤分期（阳性、阴性或缺失），估计ER状态在状态未知的患者中的分布概率;（2）采用多变量和敏感性分析，评估ER数据缺失和缺乏对社会经济地位的控制是否会导致乳腺癌ER状态和ER状态乳腺癌发病率的种族/民族差异的估计偏差。结果将提供第一个证据，证明由于ER状态数据缺失和缺乏社会经济数据，ER状态的种族/民族差异估计是否存在偏倚，并将在大型多种族/民族队列中进行。研究结果将提供解决健康差异所需的知识，这是美国国家癌症研究所、美国国立卫生研究院和健康人群2010年的一个关键目标，同时也解决了PAR- 04-159的目标，通过使用“现有数据”来确定“肿瘤发生和进展的生物标志物在流行病学研究中的适用性”。"

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."