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. 2020 Aug 28;9(1):1786888. doi: 10.1080/2162402X.2020.1786888

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© 2020 The Author(s). Published with license by Taylor & Francis Group, LLC.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 1. — Discriminant analysis of melanoma patients (n = 36) treated with PD-1 checkpoint inhibitors at baseline. (a) Discriminant analysis related to PFS: green squares, PFS >6 months, blue squares, PFS <6 months. The horizontal axis represents the predictive, the vertical axis represents the orthogonal component. Ellipse Hotelling’s T2 95% confidence interval limit. (b) Loadings plot with the 14 most relevant variables correlated with PFS. Error bars represent jack-knifed 95% confidence intervals. Positive correlation to long PFS means negative correlation to short PFS, and vice versa. (c) Combined plot showing the scaled loadings (p(corr)[1]) and the variable importance in the projections (VIP) according to PFS; dashed lines mark VIP values = 1.0, and |p(corr[1])| = 0.4, which were used as cutoff points for biomarker selection. Panels d–f show the discriminant analysis (d), loadings (e) and p(corr)[1]/VIP plot (f) when OS (long vs. short) was used as a discriminant binary variable.