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Updated: Feb 19, 2026

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Baseline relative eosinophil count as a predictive biomarker for ipilimumab treatment in advanced melanoma
Pier Francesco Ferrucci1, Sara Gandini2, Emilia Cocorocchio1
1Medical Oncology of Melanoma Unit, Division of Medical Oncology of Melanoma and Sarcoma, European Institute of Oncology, Milan, Italy.
Abstract:
As diverse therapeutic options are now available for advanced melanoma patients, predictive markers that may assist treatment decision are needed. A model based on baseline serum lactate dehydrogenase (LDH), peripheral blood relative lymphocyte counts (RLC) and eosinophil counts (REC) and pattern of distant metastasis, has been recently proposed for pembrolizumab-treated patients. Here, we applied this model to advanced melanoma patients receiving chemotherapy (n = 116) or anti-CTLA-4 therapy (n = 128). Visceral involvement, LDH and RLC were associated with prognosis regardless of treatment. Instead, when compared to chemotherapy-treated patients with REC < 1.5%, those with REC ≥ 1.5% had improved overall survival when receiving anti-CTLA-4 [Hazard Ratio (HR) = 0.56 (0.4-0.93)] but not chemotherapy [HR = 1.13, (0.74-1.74)], and the treatment-by-REC interaction was significant for both overall (p = 0.04) and progression free survival (p = 0.009). These results indicate baseline REC ≥ 1.5% as a candidate predictive biomarker for benefit from anti-CTLA-4. Further studies are needed to confirm these findings in patients receiving immune-modulating agents.

