Racial and Socioeconomic Disparities in Breast Cancer Diagnostic Work Up and Outcomes

乳腺癌诊断工作和结果的种族和社会经济差异

基本信息

  • 批准号:
    10094564
  • 负责人:
  • 金额:
    $ 66.06万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-06-01 至 2026-05-31
  • 项目状态:
    未结题

项目摘要

Project Summary U.S. women of minority race/ethnicity, lower education, lower income, rural residence, and the underinsured experience higher breast cancer disease burden and lower survival rates than women without these characteristics, despite recent improvements in screening access and treatments. The majority of efforts to mitigate these disparities have focused on screening mammography access, but women must navigate multiple additional steps when cancer is suspected, including more imaging, biopsies, and specialist consultations. Each year, >12 million U.S. women enter this diagnostic care continuum. Failure to receive timely, quality evaluation leads to delayed diagnosis, more invasive procedures, advanced cancer stage at diagnosis, and greater mortality. Compared to screening, surprisingly little is known about disparities during this diagnostic period. It is estimated that up to 30% of women with abnormalities detected by mammography fail to obtain appropriate or timely follow-up, and up to 50% of racial/ethnic minorities and socioeconomically disadvantaged women experience such failures. A clearer understanding of disparities along the diagnostic continuum is hindered by the decentralized nature of breast cancer screening and diagnosis in the U.S., with disparities in care likely due to a complex combination of individual, residential, and healthcare delivery factors. We propose to conduct the largest U.S. observational study of disparities in diagnostic breast imaging to date. Specifically, we aim to 1) identify specific subpopulations of women with lower access to and use of key diagnostic imaging technologies; 2) determine differences in diagnostic outcomes that can serve as quality of care indicators based on race/ethnicity and socioeconomic status; and 3) identify differences in timeliness of diagnostic evaluation among disparities populations. We will use multi-level statistical modeling and mediation analyses to account for multifactorial interactions that likely influence inequitable diagnostic care. Our team, the Breast Cancer Surveillance Consortium, consists of national experts in breast cancer epidemiology, biostatistics, health services research, medicine, and radiology. The BCSC represents the largest longitudinal breast cancer imaging data resource linked to long-term outcomes that is representative of the general U.S. population by race/ethnicity. We systematically collect woman-, exam-, residential-, practice-, provider- and tumor-level data across seven regional registries and more than 200 individual practices. With data collected for 13 million breast imaging exams, 5.5 million of which were performed among traditional disparities populations, our team is well-positioned to carry out the proposed analyses. Our study will help shift the breast cancer disparities research paradigm from focusing on screening access to evaluating the entire diagnostic episode. By identifying novel quality of care metrics and “early warning” indicators of disparities, our results will inform both practice-level interventions aimed at closing local disparities gaps and national practice guidelines and policies directed towards more equitable breast cancer diagnostic evaluation.
项目总结

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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CHRISTOPH I LEE其他文献

CHRISTOPH I LEE的其他文献

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{{ truncateString('CHRISTOPH I LEE', 18)}}的其他基金

Population-Based Evaluation of Artificial Intelligence for Mammography Prior to Widespread Clinical Translation
在广泛临床转化之前对乳腺 X 线摄影人工智能进行基于人群的评估
  • 批准号:
    10651842
  • 财政年份:
    2022
  • 资助金额:
    $ 66.06万
  • 项目类别:
Population-Based Evaluation of Artificial Intelligence for Mammography Prior to Widespread Clinical Translation
在广泛临床转化之前对乳腺 X 线摄影人工智能进行基于人群的评估
  • 批准号:
    10445206
  • 财政年份:
    2022
  • 资助金额:
    $ 66.06万
  • 项目类别:
Racial and Socioeconomic Disparities in Breast Cancer Diagnostic Work Up and Outcomes
乳腺癌诊断工作和结果的种族和社会经济差异
  • 批准号:
    10394189
  • 财政年份:
    2021
  • 资助金额:
    $ 66.06万
  • 项目类别:
Racial and Socioeconomic Disparities in Breast Cancer Diagnostic Work Up and Outcomes
乳腺癌诊断工作和结果的种族和社会经济差异
  • 批准号:
    10654528
  • 财政年份:
    2021
  • 资助金额:
    $ 66.06万
  • 项目类别:
Artificial Intelligence for Improved Breast Cancer Screening Accuracy: External Validation, Refinement, and Clinical Translation
人工智能提高乳腺癌筛查准确性:外部验证、细化和临床转化
  • 批准号:
    10544496
  • 财政年份:
    2020
  • 资助金额:
    $ 66.06万
  • 项目类别:
Artificial Intelligence for Improved Breast Cancer Screening Accuracy: External Validation, Refinement, and Clinical Translation
人工智能提高乳腺癌筛查准确性:外部验证、细化和临床转化
  • 批准号:
    10320906
  • 财政年份:
    2020
  • 资助金额:
    $ 66.06万
  • 项目类别:
Artificial Intelligence for Improved Breast Cancer Screening Accuracy: External Validation, Refinement, and Clinical Translation
人工智能提高乳腺癌筛查准确性:外部验证、细化和临床转化
  • 批准号:
    9912472
  • 财政年份:
    2020
  • 资助金额:
    $ 66.06万
  • 项目类别:
Project 2
项目2
  • 批准号:
    10705584
  • 财政年份:
    2011
  • 资助金额:
    $ 66.06万
  • 项目类别:
Project 2
项目2
  • 批准号:
    10411222
  • 财政年份:
    2011
  • 资助金额:
    $ 66.06万
  • 项目类别:

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