Reeder-Hayes Katherine E, Troester Melissa A, Meyer Anne-Marie
Oncology (Williston Park). 2017 Oct 15;31(10):756-62.
Advances in a wide array of scientific technologies have brought data of unprecedented volume and complexity into the oncology research space. These novel big data resources are applied across a variety of contexts-from health services research using data from insurance claims, cancer registries, and electronic health records, to deeper and broader genomic characterizations of disease. Several forms of big data show promise for improving our understanding of racial disparities in breast cancer, and for powering more intelligent and far-reaching interventions to close the racial gap in breast cancer survival. In this article we introduce several major types of big data used in breast cancer disparities research, highlight important findings to date, and discuss how big data may transform breast cancer disparities research in ways that lead to meaningful, lifesaving changes in breast cancer screening and treatment. We also discuss key challenges that may hinder progress in using big data for cancer disparities research and quality improvement.
一系列科学技术的进步已将数量空前且复杂的数据带入肿瘤学研究领域。这些新型大数据资源被应用于各种情境——从利用保险理赔、癌症登记和电子健康记录中的数据进行卫生服务研究，到对疾病进行更深入、更广泛的基因组特征分析。几种形式的大数据有望增进我们对乳腺癌种族差异的理解，并推动采取更智能、更具深远影响的干预措施，以缩小乳腺癌生存率方面的种族差距。在本文中，我们介绍了乳腺癌差异研究中使用的几种主要类型的大数据，突出了迄今为止的重要发现，并讨论了大数据如何以能在乳腺癌筛查和治疗方面带来有意义的、挽救生命的改变的方式，转变乳腺癌差异研究。我们还讨论了可能阻碍利用大数据进行癌症差异研究和质量改进取得进展的关键挑战。
