Disparities in the Demographic Composition of The Cancer Imaging Archive.

IF 5.6 Q1 ONCOLOGY Radiology. Imaging cancer Pub Date : 2024-01-01 DOI:10.1148/rycan.230100
Aidan Dulaney, John Virostko
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Abstract

Purpose To characterize the demographic distribution of The Cancer Imaging Archive (TCIA) studies and compare them with those of the U.S. cancer population. Materials and Methods In this retrospective study, data from TCIA studies were examined for the inclusion of demographic information. Of 189 studies in TCIA up until April 2023, a total of 83 human cancer studies were found to contain supporting demographic data. The median patient age and the sex, race, and ethnicity proportions of each study were calculated and compared with those of the U.S. cancer population, provided by the Surveillance, Epidemiology, and End Results Program and the Centers for Disease Control and Prevention U.S. Cancer Statistics Data Visualizations Tool. Results The median age of TCIA patients was found to be 6.84 years lower than that of the U.S. cancer population (P = .047) and contained more female than male patients (53% vs 47%). American Indian and Alaska Native, Black or African American, and Hispanic patients were underrepresented in TCIA studies by 47.7%, 35.8%, and 14.7%, respectively, compared with the U.S. cancer population. Conclusion The results demonstrate that the patient demographics of TCIA data sets do not reflect those of the U.S. cancer population, which may decrease the generalizability of artificial intelligence radiology tools developed using these imaging data sets. Keywords: Ethics, Meta-Analysis, Health Disparities, Cancer Health Disparities, Machine Learning, Artificial Intelligence, Race, Ethnicity, Sex, Age, Bias Published under a CC BY 4.0 license.

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癌症成像档案人口构成的差异。
目的 描述癌症成像档案(TCIA)研究的人口分布特征,并将其与美国癌症患者的人口分布进行比较。材料与方法 在这项回顾性研究中,我们检查了 TCIA 研究的数据,以纳入人口统计学信息。在截至 2023 年 4 月的 189 项 TCIA 研究中,共发现 83 项人类癌症研究包含支持性人口统计学数据。我们计算了每项研究的患者年龄中位数以及性别、种族和民族比例,并将其与监测、流行病学和最终结果计划以及美国疾病控制和预防中心的美国癌症统计数据可视化工具提供的美国癌症人口比例进行了比较。结果发现,TCIA 患者的中位年龄比美国癌症患者低 6.84 岁(P = .047),女性患者多于男性患者(53% 对 47%)。与美国癌症患者相比,美国印第安人和阿拉斯加原住民、黑人或非裔美国人以及西班牙裔患者在 TCIA 研究中的比例偏低,分别为 47.7%、35.8% 和 14.7%。结论 研究结果表明,TCIA 数据集的患者人口统计学特征并不反映美国癌症患者的人口统计学特征,这可能会降低利用这些成像数据集开发的人工智能放射学工具的普适性。关键词伦理、元分析、健康差异、癌症健康差异、机器学习、人工智能、种族、民族、性别、年龄、偏差 采用 CC BY 4.0 许可发布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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5.00
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2.30%
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