Cedars Sinai Medical Center, Department of Computational Biomedicine, Los Angeles, CA.
University of Michigan Rogel, Cancer Center, Ann Arbor, MI.
JCO Clin Cancer Inform. 2024 Jul;8:e2400007. doi: 10.1200/CCI.24.00007.
PURPOSE: Longitudinal patient tolerability data collected as part of randomized controlled trials are often summarized in a way that loses information and does not capture the treatment experience. To address this, we developed an interactive web application to empower clinicians and researchers to explore and visualize patient tolerability data. METHODS: We used adverse event (AE) data (Common Terminology Criteria for Adverse Events) and patient-reported outcomes (PROs) from the NSABP-B35 phase III clinical trial, which compared anastrozole with tamoxifen for breast cancer-free survival, to demonstrate the tools. An interactive web application was developed using R and the Shiny web application framework that generates Sankey diagrams to visualize AEs and PROs using four tools: AE Explorer, PRO Explorer, Cohort Explorer, and Custom Explorer. RESULTS: To illustrate how users can use the interactive tool, examples for each of the four applications are presented using data from the NSABP-B35 phase III trial and the NSABP-B30 trial for the Custom Explorer. In the AE and PRO explorers, users can select AEs or PROs to visualize within specified time periods and compare across treatments. In the cohort explorer, users can select a subset of patients with a specific symptom, severity, and treatment received to visualize the trajectory over time within a specified time interval. With the custom explorer, users can upload and visualize structured longitudinal toxicity and tolerability data. CONCLUSION: We have created an interactive web application and tool for clinicians and researchers to explore and visualize clinical trial tolerability data. This adaptable tool can be extended for other clinical trial data visualization and incorporated into future patient-clinician interactions regarding treatment decisions.
目的:作为随机对照试验的一部分收集的纵向患者耐受性数据通常以一种丢失信息且无法捕捉治疗体验的方式进行总结。为了解决这个问题,我们开发了一个交互式网络应用程序,使临床医生和研究人员能够探索和可视化患者耐受性数据。
方法:我们使用来自 NSABP-B35 三期临床试验的不良事件(CTCAE)数据和患者报告的结果(PROs),该试验比较了阿那曲唑与他莫昔芬对乳腺癌无复发生存率的影响,以展示这些工具。我们使用 R 和 Shiny 网络应用程序框架开发了一个交互式网络应用程序,该框架生成桑基图,使用四个工具可视化 AE 和 PRO:AE 探索器、PRO 探索器、队列探索器和自定义探索器。
结果:为了说明用户如何使用交互式工具,我们使用来自 NSABP-B35 三期试验和 NSABP-B30 试验的数据为每个应用程序提供了示例,用于自定义探索器。在 AE 和 PRO 探索器中,用户可以选择特定时间段内的 AE 或 PRO 进行可视化,并比较不同治疗方法的结果。在队列探索器中,用户可以选择具有特定症状、严重程度和治疗的特定亚组患者,以可视化特定时间间隔内随时间的轨迹。使用自定义探索器,用户可以上传和可视化结构化的纵向毒性和耐受性数据。
结论:我们创建了一个交互式网络应用程序和工具,供临床医生和研究人员探索和可视化临床试验耐受性数据。这个适应性强的工具可以扩展到其他临床试验数据可视化,并纳入未来关于治疗决策的医患互动中。
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