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. 2017 Oct 16;7:13190. doi: 10.1038/s41598-017-13196-4

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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9 vascular features (VF) predict disease free survival (DFS) in ccRCC. (A) Workflow diagram for predicting outcomes with selected vascular features in the ccRCC discovery cohort (N = 64). (B) Hierarchical clustering of the 64 cases by 9 vascular features into two risk groups. Blue – low risk, red – high risk. (C) Principal component analysis demonstrating the first two principal components of the 9 selected VF’s. (D) Kaplan-Meier plot using 9VF’s to separate patients into low- and high-risk groups (HR = 2.4, 95% C.I. = 1.1–5.2). (E) Box plot of VF expression in good and poor DFS risk groups (two-tailed t-test *p < 0.1, **p < 0.05). The 9VF’s are described in Table 1 and Supplementary Table S7.