Srabanti Sanjana, Tran Michael, Achim Virginie, Fuller David, Canahuate Guadalupe, Miranda Fabio, Marai G Elisabeta
University of Illinois at Chicago.
University of Texas.
IEEE Pac Vis Symp. 2022 Apr;2022:101-110. doi: 10.1109/pacificvis53943.2022.00019. Epub 2022 Jun 8.
The annual incidence of head and neck cancers (HNC) worldwide is more than 550,000 cases, with around 300,000 deaths each year. However, the incidence rates and disease-characteristics of HNC differ between treatment centers and different populations, due to undetermined reasons, which may or not include socioeconomic factors. The multi-faceted and multi-variate nature of the data in the context of the emerging field of health disparities research makes automated analysis impractical. Hence, we present a visual analysis approach to explore the health disparities in the data of HNC patients from two different cohorts at two cancer care centers. Our approach integrates data from multiple sources, including census data and city data, with custom visual encodings and with a nearest neighbor approach. Our design, created in collaboration with oncology experts, makes it possible to analyze the patients' demographic, disease characteristics, treatments and outcomes, and to make significant comparisons of these two cohorts and of individual patients. We evaluate this approach through two case studies performed with domain experts. The results demonstrate that this visual analysis approach successfully accomplishes the goal of comparing two cohorts in terms of different significant factors, and can provide insights into the main source of health disparities between the two centers.
全球范围内，头颈癌（HNC）的年发病率超过55万例，每年约有30万人死亡。然而，由于某些尚未明确的原因（可能包括也可能不包括社会经济因素），不同治疗中心和不同人群之间的头颈癌发病率及疾病特征存在差异。在健康差异研究这一新兴领域中，数据具有多方面、多变量的性质，这使得自动化分析不切实际。因此，我们提出一种可视化分析方法，以探究来自两个癌症护理中心的两个不同队列的头颈癌患者数据中的健康差异。我们的方法将来自多个来源的数据（包括人口普查数据和城市数据）与自定义可视化编码以及最近邻方法相结合。我们与肿瘤学专家合作设计的方法，能够分析患者的人口统计学特征、疾病特征、治疗方法和治疗结果，并对这两个队列以及个体患者进行有意义的比较。我们通过与领域专家进行的两个案例研究来评估这种方法。结果表明，这种可视化分析方法成功实现了根据不同重要因素比较两个队列的目标，并能够深入了解两个中心之间健康差异的主要来源。
