Baseline neutrophil-to-eosinophil-ratio and outcome in metastatic clear-cell renal cell carcinoma treated with nivolumab or ipilimumab/nivolumab.

ABSTRACT

BACKGROUND AND PURPOSE: This study aims to evaluate neutrophil-to-eosinophil ratio (NER) as a prognostic and/or predictive biomarker in metastatic clear cell renal cell carcinoma (m-ccRCC) treated with nivolumab or ipilimumab/nivolumab. PATIENTS/MATERIALS AND METHODS: We performed a retrospective study on m-ccRCC patients treated with nivolumab or ipilimumab/nivolumab (2012-2022). Baseline NER was calculated and correlated with clinical outcomes: response rate (RR), progression free survival (PFS) and overall survival (OS). Corresponding transcriptomic data were analysed. RESULTS: We included 201 m-ccRCC patients, 76 treated with ipilimumab/nivolumab and 125 with nivolumab. Baseline NER was statistically significantly associated with International Metastatic RCC Database Consortium (IMDC) risk groups. Increased NER was associated with shorter PFS and OS in the total patient series and nivolumab-treated patients. In patients treated with ipilimumab/nivolumab, increased NER was only statistically significantly associated with shorter OS. The impact of baseline NER on PFS and OS was independent of IMDC risk stratification. No clear correlation was found between baseline NER and RECIST response or maximal tumour shrinkage. In two additional databases, NER was also associated with PFS and OS in first-line vascular-endothelial-growth-factor-receptor tyrosine-kinase-inhibitors (VEGFR-TKIs), but not to disease-free survival in the post-nephrectomy setting. Lower NER was associated with intratumoural molecular features possibly associated with better outcome on immune checkpoint inhibitors. INTERPRETATION: Lower baseline NER is associated with better PFS and OS, independent of IMDC risk score, in m-ccRCC patients treated with ipilimumab/nivolumab or nivolumab. It correlates with intratumoural molecular features possibly associated with better outcome on immune checkpoint inhibitors. The predictive power of this biomarker is probably limited and insufficient for patient selection.