Univariate and multivariate diagnostic performances of FC data in SS. (A) −log(P) of ROC curves as a function of AUC for each parameter of interest. Red dots represent parameters with AUC ≥ 0.9 and high discriminating power between SS and non-patients with SS (P < .0001), which are considered the best parameters for SS diagnosis. Classical FCM parameters are represented (CD4⁺CD26⁻, CD4⁺CD7⁻, CD4⁺CD26⁻CD158k⁺, and CD4⁺CD26⁻PD-1⁺) as well as new parameters obtained with the multivariate analysis method using the FlowSOM algorithm (C5, C8, C9, D4, and D7). (B) Best SS seed obtained with unsupervised multivariate analysis of the lmd file of merged SS using the FlowSOM algorithm. Cells are clustering according to their phenotype. Node size is proportionate to cell number. Red dots represent nodes of interest for SS diagnosis. (C) Volcano plot of SS (n = 18) vs non-CTCL (n = 35). Red rings represent nodes overrepresented in non-CTCL patients, red dots represent nodes overrepresented in patients with SS (called C5, C8, C9, D4, and D7).