Discriminatory ability of combination models. The concordance index (c-index, y-axis) was calculated for the combination of factors with independent impact according to Cox regression analysis (model 6.1) and 13 alternative combination models considering 5, 7, or 8 factors (A). The numbers refer to the rows in A. The c-indices are presented according to the number of combined factors (B). The combination model with highest discriminatory ability (7.4), which considered regulatory T cells in addition to the 6 factors with independent impact according to Cox regression analysis was chosen as combination model 1. No further increase of the c-index compared to combination model 1 was observed if one of the 3 remaining factors was additionally considered (models 8.1, 8.2, 8.3). C-indices were calculated for different combination models accounting for the number of unfavorable values of all factors considered in the given model (C). All possible models derived from combinations of the five routine factors were considered. The c-indices are presented according to the number of considered factors (D). The model with highest discriminatory ability (4.1) was selected.
ARTICLE ABSTRACT
Purpose: To identify baseline peripheral blood biomarkers associated with clinical outcome following ipilimumab treatment in advanced melanoma patients.Experimental Design: Frequencies of myeloid-derived suppressor cells (MDSC) and regulatory T cells (Treg), serum lactate dehydrogenase (LDH), routine blood counts, and clinical characteristics were assessed in 209 patients. Endpoints were overall survival (OS) and best overall response. Statistical calculations were done by Kaplan–Meier and Cox regression analysis, including calibration and discrimination by C-statistics.Results: Low baseline LDH, absolute monocyte counts (AMC), Lin−CD14+HLA-DR−/low-MDSC frequencies, and high absolute eosinophil counts (AEC), relative lymphocyte counts (RLC), and CD4+CD25+FoxP3+-Treg frequencies were significantly associated with better survival, and were considered in a combination model. Patients (43.5%) presenting with the best biomarker signature had a 30% response rate and median survival of 16 months. In contrast, patients with the worst biomarkers (27.5%) had only a 3% response rate and median survival of 4 months. The occurrence of adverse events correlated with neither baseline biomarker signatures nor the clinical benefit of ipilimumab. In another model, limited to the routine parameters LDH, AMC, AEC, and RLC, the number of favorable factors (4 vs. 3 vs. 2–0) was also associated with OS (P < 0.001 for all pairwise comparisons) in the main study and additionally in an independent validation cohort.Conclusions: A baseline signature of low LDH, AMC, and MDSCs as well as high AEC, Tregs, and RLC is associated with favorable outcome following ipilimumab. Prospective investigation of the predictive impact of these markers following ipilimumab and other treatments, e.g., PD-1 antibodies, is warranted. Clin Cancer Res; 22(12); 2908–18. ©2016 AACR.
