开发可视化乳腺癌临床试验耐受性数据的网络互动工具。

IF 3.3 Q2 ONCOLOGY
Michael Luu, Gillian Gresham, Lynn Henry, Sungjin Kim, Andre Rogatko, Greg Yothers, Ron D Hays, Mourad Tighiouart, Patricia A Ganz
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引用次数: 0

摘要

目的:作为随机对照试验的一部分而收集的患者耐受性纵向数据在总结时往往会丢失信息,无法捕捉治疗体验。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患者耐受性数据并将其可视化:我们使用 NSABP-B35 III 期临床试验中的不良事件(AE)数据(不良事件通用术语标准)和患者报告结果(PROs)来展示这些工具。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,该程序可生成 Sankey 图表,使用四种工具对 AE 和 PRO 进行可视化:AE Explorer、PRO Explorer、Cohort Explorer 和 Custom Explorer.Results:为了说明用户如何使用该交互式工具,我们使用来自 NSABP-B35 III 期试验的数据和来自 NSABP-B30 试验的数据分别介绍了这四种应用的示例。在AE和PRO探索器中,用户可以选择AE或PRO,对指定时间段内的AE或PRO进行可视化,并对不同治疗进行比较。在队列探索器中,用户可以选择具有特定症状、严重程度和接受过治疗的患者子集,以可视化指定时间间隔内的随时间变化的轨迹。通过自定义资源管理器,用户可以上传并可视化结构化的纵向毒性和耐受性数据:我们为临床医生和研究人员创建了一个交互式网络应用程序和工具,用于探索和可视化临床试验耐受性数据。这一工具适应性强,可扩展用于其他临床试验数据的可视化,并可融入未来病人与医生在治疗决策方面的互动中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a Web-Based Interactive Tool for Visualizing Breast Cancer Clinical Trial Tolerability Data.

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.

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来源期刊
CiteScore
6.20
自引率
4.80%
发文量
190
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