Current and Evolving Methods to Visualize Biological Data in Cancer Research

被引:17
作者
Chia, Puey Ling [1 ,2 ]
Gedye, Craig [3 ]
Boutros, Paul C. [4 ,5 ,6 ]
Wheatley-Price, Paul [7 ,8 ]
John, Thomas [1 ,2 ]
机构
[1] Austin Hlth, Dept Med Oncol, Melbourne, Vic, Australia
[2] Austin Hlth, Olivia Newton John Canc Res Inst, Melbourne, Vic, Australia
[3] Univ Newcastle, Sch Biomed Sci & Pharm, Hunter Med Res Inst, New Lambton Hts, NSW, Australia
[4] Ontario Inst Canc Res, Informat & Biocomp Program, Toronto, ON, Canada
[5] Univ Toronto, Dept Med Biophys, Toronto, ON, Canada
[6] Univ Toronto, Dept Pharmacol & Toxicol, Toronto, ON, Canada
[7] Univ Ottawa, Ottawa Hosp, Res Inst, Ottawa, ON, Canada
[8] Univ Ottawa, Dept Med, Ottawa, ON, Canada
来源
JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE | 2016年 / 108卷 / 08期
基金
英国医学研究理事会;
关键词
CLINICAL-TRIALS; FOREST PLOTS; BIAS; METAANALYSIS; GUIDELINES; CISPLATIN; THERAPY; DESIGN;
D O I
10.1093/jnci/djw031
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Although the measurements of clinical outcomes for cancer treatments have become diverse and complex, there remains a need for clear, easily interpreted representations of patients' experiences. With oncology trials increasingly reporting non-time-to-event outcomes, data visualization has evolved to incorporate parameters such as responses to therapy, duration and degree of response, and novel representations of underlying tumor biology. We review both commonly used and newly developed methods to display outcomes in oncology, with a focus on those that have evolved to represent complex datasets.
引用
收藏
页数:11
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