Fig. 4.

LMS⁺ primary tumors show a marked rise in metastatic risk after reaching ≥2 cm. (A) Factors that influence the risk of metastasis for patients from the NKI-295/EMC-344 cohort were determined by a random survival forest analysis. Clinical and pathological variables that include tumor size, patient age, histological grade, estrogen receptor status, and the number of positive lymph nodes were simultaneously entered into the model. This method is virtually free of model assumptions and involves constructing survival trees from bootstrap samples by using randomly selected covariates for tree splitting to deliver an ensemble cumulative hazard estimate for metastasis-free survival. The expected frequency of patients developing metastasis from the 128 patients with LMS⁺ tumors (Left) and the 511 patients with LMS⁻ tumors (Right) is obtained from the ensemble estimate and plotted for each covariate. Shown are the results for tumor size. Results for other covariates are shown in SI Fig. 9. Patients that actually developed metastasis are indicated in red along with a lowess regression line through these points shown in magenta. (B) A concordance index from a random survival forest analysis modeling the influence of the LMS, tumor size, and other breast cancer prognostic gene expression signatures on the risk for lung metastasis was calculated (indicated by “All”) by using the NKI-295 cohort. This was then repeated with each of the indicated gene signatures or tumor size omitted from the full model (indicated above the blue bracket “Variable Removed”). The results from 50 runs are shown as a box-and-whisker plot. Nonoverlapping notches are considered significant. Both lung metastasis (Left) and overall survival (Right) were separately analyzed.