Figure 1
Figure 1. Panel of 11 genes and the molecular risk algorithm. (A) The molecular risk algorithm is determined on the basis of the relative contributions of each of the 4 gene functional groups from the tumoral HRS and their reactive microenvironment as follows: MRS = exp (fx)/(1 + exp [fx]), where fx = (−0.913) + (0.401 × apoptosis) + (0.284 × cell cycle) + (−0.301 × monocyte) + (−0.143 × IRF4). Coefficients were derived from a multivariate analysis in which positive values indicate that a greater level of expression is correlated with a worse outcome, and negative coefficients indicate that a greater level of expression of the pathways is associated with a better outcome. (B) MRS as a continuous function was used to set a threshold for stratifying patients by ROC analysis. Patients were stratified according to the levels of the molecular risk score into low-risk (< 0.3) and high-risk (≥ 0.3) groups. (C-D) Survival estimates of FFS in patients from estimation (n = 183) and validation (n = 79) sets after classification into risk groups. Kaplan-Meier analysis and the log-rank test gave significant results in both estimation and validation sets, indicating the potential prognostic capacity of the algorithm developed here.

Panel of 11 genes and the molecular risk algorithm. (A) The molecular risk algorithm is determined on the basis of the relative contributions of each of the 4 gene functional groups from the tumoral HRS and their reactive microenvironment as follows: MRS = exp (fx)/(1 + exp [fx]), where fx = (−0.913) + (0.401 × apoptosis) + (0.284 × cell cycle) + (−0.301 × monocyte) + (−0.143 × IRF4). Coefficients were derived from a multivariate analysis in which positive values indicate that a greater level of expression is correlated with a worse outcome, and negative coefficients indicate that a greater level of expression of the pathways is associated with a better outcome. (B) MRS as a continuous function was used to set a threshold for stratifying patients by ROC analysis. Patients were stratified according to the levels of the molecular risk score into low-risk (< 0.3) and high-risk (≥ 0.3) groups. (C-D) Survival estimates of FFS in patients from estimation (n = 183) and validation (n = 79) sets after classification into risk groups. Kaplan-Meier analysis and the log-rank test gave significant results in both estimation and validation sets, indicating the potential prognostic capacity of the algorithm developed here.

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