Predicting Survival of Patients with Nonmetastatic Breast Cancer Based on Fibrinogen-to-Albumin Ratio and Lymphocyte-to-Monocyte Ratio: A Nomogram-Based Assessment

基于纤维蛋白原/白蛋白比值和淋巴细胞/单核细胞比值预测非转移性乳腺癌患者生存率:基于列线图的评估

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Abstract

BACKGROUND: Parameters of systemic inflammation have received attention as prognostic surrogates in various malignant tumors. Fibrinogen-to-albumin ratio (FAR) and lymphocyte-to-monocyte ratio (LMR) correlate with tumor growth and dissemination. We aimed to bring the combination of FAR and LMR (FAR-LMR) together to establish novel nomograms for survival and recurrence in nonmetastatic breast cancer patients. METHODS: We retrospectively recruited 461 female patients with nonmetastatic breast cancer from January 2011 to December 2013 in our hospital and randomly assigned them into the training cohort (N = 318) and the validation cohort (N = 143). The potential predictive factors for overall survival (OS), locoregional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS) were assessed by Cox proportional hazards models and log-rank test. RESULTS: Elevated FAR was associated with poor OS (p < 0.001) and DMFS (p = 0.02), whereas increased LMR was associated with satisfactory OS (p = 0.01) and LRFS (p = 0.01). High FAR combined with low LMR was associated with less favorable OS (p = 0.001), LRFS (p = 0.005), and DMFS (p = 0.003) Based on multivariate analysis, FAR-LMR, tumor size, lymph node metastasis, age, and pathologic status contributed to prognostic nomograms of OS, DMFS, and LRFS. Nomograms presented exceptional performance for 3-, 5-, and 8-year OS, DMFS, and LRFS prediction compared with clinical TNM stage. The C-index was significantly higher than that of TNM stage, either of FAR or LMR (3-year: 0.709 vs. 0.621 vs. 0.544 vs. 0.641, 5-year: 0.761 vs. 0.597 vs. 0.605 vs. 0.677, 8-year: 0.84 vs. 0.62 vs. 0.539 vs. 0.623). CONCLUSIONS: We developed and validated a convenient predictive model for the survival outcomes of patients with nonmetastatic breast cancer. The nomograms can be utilized as auxiliary tools to provide prognostic information.

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