Development of a Prognostic Model for Early Breast Cancer Integrating Neutrophil to Lymphocyte Ratio and Clinical-Pathological Characteristics

Faria, Sara Socorro and Giannarelli, Diana and de Lima, Vladmir Claudio Cordeiro and Anwar, Sumadi Luckman and Casadei, Chiara and De Giorgi, Ugo and Madonna, Gabriele and Ascierto, Paolo Antonio and López, Rossana Veronica Mendoza and Chammas, Roger and Capone, Mariaelena (2024) Development of a Prognostic Model for Early Breast Cancer Integrating Neutrophil to Lymphocyte Ratio and Clinical-Pathological Characteristics. Oncologist, 29 (4). e447-e454. ISSN 10837159

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Abstract

Background: 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), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), and systemic immune-inflammation index (SII) are considered as prognostic markers in several types of malignancy. Methods: We investigate and validate a prognostic model in early patients with breast cancer to predict disease-free survival (DFS) based on readily available baseline clinicopathological prognostic factors and preoperative peripheral blood-derived indexes. Results: We analyzed a training cohort of 710 patients and 2 external validation cohorts of 980 and 157 patients with breast cancer, respectively, with different demographic origins. An elevated preoperative NLR is a better DFS predictor than others scores. The prognostic model generated in this study was able to classify patients into 3 groups with different risks of relapse based on ECOG-PS, presence of comorbidities, T and N stage, PgR status, and NLR. Conclusion: 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. © The Author(s) 2023.

Item Type: Article
Additional Information: Cited by: 3; All Open Access, Gold Open Access
Uncontrolled Keywords: Biomarkers; Breast Neoplasms; Female; Humans; Inflammation; Lymphocytes; Neoplasm Recurrence, Local; Neutrophils; Prognosis; Retrospective Studies; epidermal growth factor receptor 2; estrogen receptor; progesterone receptor; biological marker; adult; aged; Article; blood cell count; breast cancer; cancer chemotherapy; cancer prognosis; cancer radiotherapy; cancer survival; clinical practice; cohort analysis; comorbidity; demographics; disease activity; disease free survival; ECOG Performance Status; electronic medical record; female; histology; hormonal therapy; human; lymphocyte count; monocyte; monocyte lymphocyte ratio; neutrophil; neutrophil lymphocyte ratio; pathology; platelet count; platelet lymphocyte ratio; prediction; retrospective study; systemic immune inflammation index; tumor volume; breast tumor; inflammation; lymphocyte; pathology; prognosis; tumor recurrence
Subjects: R Medicine > RD Surgical Divisions
Divisions: Faculty of Medicine, Public Health and Nursing > Surgical Divisions
Depositing User: Ngesti Gandini
Date Deposited: 13 Mar 2025 01:19
Last Modified: 13 Mar 2025 01:19
URI: https://ir.lib.ugm.ac.id/id/eprint/15728

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