Development of a prognostic model for early breast cancer integrating neutrophil to lymphocyte ratio and clinical-pathological characteristics

Abstract

Breast cancer-related inflammation is critical in tumorigenesis, cancer progression, and patient prognosis. Several inflammatory markers derived from peripheral blood cells count, such as the neutrophil-lymphocyte ratio (NLR), derived neutrophil-lymphocyte ratio (dNLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) are considered as prognostic markers in several types of malignancy. Here, we investigate and validate a prognostic model in early breast cancer (eBC) patients to predict disease-free survival (DFS) based on readily available baseline clinicopathological prognostic factors and preoperative peripheral blood-derived indexes. We analyzed a training cohort of 710 BC patients and two external validation cohorts of 980 and 157 eBC patients, respectively, with different demographic origins. An elevated preoperative NLR is a better DFS predictor than PLR, MLR, and SII in patients with eBC. The prognostic model generated in this study was able to classify patients into three groups with different risks of relapse based on ECOG-PS, presence of comorbidities, T and N stage, PgR status, and NLR. Prognostic models derived from the combination of clinicopathological features and peripheral blood indices, such as NLR, represent attractive markers mainly because they are easily detectable and applicable in daily clinical practice. More comprehensive prospective studies are needed to unveil their actual effectiveness.