Precision Risk Analysis of Cancer Therapy with Interactive Nomograms and Survival Plots

We present the design and evaluation of an integrated problem solving environment for cancer therapy analysis. The environment intertwines a statistical martingale model and a K Nearest Neighbor approach with visual encodings, including novel interactive nomograms, in order to compute and explain a...

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Published inIEEE transactions on visualization and computer graphics Vol. 25; no. 4; pp. 1732 - 1745
Main Authors Marai, G. Elisabeta, Ma, Chihua, Burks, Andrew Thomas, Pellolio, Filippo, Canahuate, Guadalupe, Vock, David M., Mohamed, Abdallah S. R., Fuller, Clifton David
Format Journal Article
LanguageEnglish
Published United States IEEE 01.04.2019
Subjects
activity-centered design
Cancer
Collaboration
Computer Graphics
design studies
Encoding
Female
Head
Humans
Male
Medical treatment
Neck
Neoplasms - mortality
Neoplasms - therapy
Nomograms
parallel coordinate plots
precision medicine
Precision Medicine - methods
Survival Analysis
Visual analytics
Visualization
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Summary:We present the design and evaluation of an integrated problem solving environment for cancer therapy analysis. The environment intertwines a statistical martingale model and a K Nearest Neighbor approach with visual encodings, including novel interactive nomograms, in order to compute and explain a patient's probability of survival as a function of similar patient results. A coordinated views paradigm enables exploration of the multivariate, heterogeneous and few-valued data from a large head and neck cancer repository. A visual scaffolding approach further enables users to build from familiar representations to unfamiliar ones. Evaluation with domain experts show how this visualization approach and set of streamlined workflows enable the systematic and precise analysis of a patient prognosis in the context of cohorts of similar patients. We describe the design lessons learned from this successful, multi-site remote collaboration.
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ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2018.2817557