分析视觉方法描述新诊断多发性骨髓瘤非介入性疾病登记的实践模式

Lihua Yue, Siwen He, Jay Cao, Ying-Ying Lu, Ahmed H. YoussefAgha, Jane Jiu Lu, Liang Liu, S. Srinivasan
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引用次数: 0

摘要

我们的生物识别团队的任务是实现新诊断的多发性骨髓瘤登记的主要目标,以描述常见一线治疗方案和后续治疗策略的实践模式。本文描述了我们用来理解和总结复杂数据结构的分析可视化方法。我们的目标是以一种有凝聚力的整体方式呈现这些方法,这些方法将随着时间的推移而出版的材料结合在一起,每个方法都有聚焦的更窄的目标,源于这个主要目标。这里将简要地重新讨论在其他地方详细描述的方法,以提供整体的观点,并提供有关新应用程序中后续变体的详细信息。这些也被用于临床出版物。还将提供我们的Sankey plot临床出版物对应的编码和图形显示相关细节,我们的方法未发表。
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Analytical Visual Methods to Describe Practice Patterns in a Newly Diagnosed Multiple Myeloma Non-Interventional Disease Registry
Our Biometric team was tasked with implementing a primary objective of a newly diagnosed Multiple Myeloma registry to describe practice patterns of common first-line treatment regimens and subsequent therapeutic strategies. This manuscript describes analytical visual methods we used to understand and summarize a complex data structure. We aim to present these methods in a cohesive holistic manner which threads together materials published over time, each with focused narrower objectives, deriving from this primary objective. Methods described in detail elsewhere are briefly revisited here to provide that holistic perspective and to provide details on subsequent variants in newer applications. These have also been used in clinical publications. The coding and graphical display related details corresponding to our Sankey plot clinical publication, for which our methods are unpublished, will also be provided.
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PROSPECTIVELY ESTIMATING THE AGE OF INITIATION OF E-CIGARETTES AMONG U.S. YOUTH: FINDINGS FROM THE POPULATION ASSESSMENT OF TOBACCO AND HEALTH (PATH) STUDY, 2013-2017. The Kumaraswamy-Rani Distribution and Its Applications Analytical Visual Methods to Describe Practice Patterns in a Newly Diagnosed Multiple Myeloma Non-Interventional Disease Registry Short Prognostic APP for Multiple Myeloma Sample Size Charts for Spearman and Kendall Coefficients
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