基于 My Cancer Genome 临床试验数据模型的乳腺癌和急性髓系白血病临床试验的全景分析。
Landscape Analysis of Breast Cancer and Acute Myeloid Leukemia Trials Using the My Cancer Genome Clinical Trial Data Model.
机构信息
Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN.
Division of Hematology/Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN.
出版信息
JCO Clin Cancer Inform. 2021 Sep;5:975-984. doi: 10.1200/CCI.21.00082.
PURPOSE
The field of oncology is expanding rapidly. New trials are opening as an increasing number of therapeutic agents are being investigated before they can become approved therapies. Aggregate views of these data, particularly data associated with diseases, biomarkers, and drugs, can be helpful in understanding the trends in current research as well as existing gaps in cancer care.
METHODS
In this paper, we performed a landscape analysis for breast cancer and acute myeloid leukemia related trials with structured, curated data from clinical trials using the My Cancer Genome clinical trial knowledgebase.
RESULTS
We have performed detailed analytics on breast cancer (N = 1,128) and acute myeloid leukemia trial sets (N = 483) to highlight the top biomarkers, drug classes, and drugs-thereby supporting a full view of biomarkers, biomarker groups, and drugs that are currently being explored in these respective diseases.
CONCLUSION
Analysis and data visualization of the cancer clinical trial landscape can inform strategic planning for new trial designs and trial activation at a particular site.
目的
肿瘤学领域正在迅速发展。随着越来越多的治疗药物在获得批准之前被进行研究，新的试验正在开展。对这些数据的总体看法，特别是与疾病、生物标志物和药物相关的数据，可以帮助了解当前研究的趋势以及癌症治疗中的现有差距。
方法
在本文中，我们使用 MyCancerGenome 临床试验知识库中来自临床试验的结构化、精心策划的数据，对乳腺癌和急性髓性白血病相关试验进行了景观分析。
结果
我们对乳腺癌（N=1128）和急性髓性白血病试验组（N=483）进行了详细的分析，以突出显示顶级生物标志物、药物类别和药物，从而全面了解这些疾病中正在探索的生物标志物、生物标志物组和药物。
结论
对癌症临床试验格局的分析和数据可视化可以为特定地点的新试验设计和试验启动提供战略规划信息。
Zotero 插件