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Pre-Treatment Lactate Dehydrogenase to Albumin Ratio (LAR) Predicts Distant Metastasis and Poor Survival in Nasopharyngeal Carcinoma
Vol 36, Issue 6, 2022
Abstract
Background: Pre-treatment lactate dehydrogenase to albumin ratio (LAR) is a significant biomarker of prognosis in cancer patients. This retrospective cohort study assessed whether pre-treatment LAR is correlated with prognosis in patients with nasopharyngeal carcinoma (NPC). Methods: A total of 790 non-metastatic NPC patients were enrolled in this study. Utilizing the X-tile software, the appropriate cutoff values for pre-treatment LAR were determined. Survival probabilities and differences in survival curves for distant metastasis-free survival (DMFS), overall survival (OS), and progression-free survival (PFS) were generated and assessed by the Kaplan–Meier method and log-rank test. Multivariate analysis (MVA) was used to explore LAR pre-treatment predictive value in DMFS, OS, and PFS. Results: The median follow-up period of this study was 84 months. LAR optimal cutoff value was 5.6. Patients with a high LAR level had inferior 5-year DMFS (57.5% vs 84.1%, p < 0.001), OS (63.5% vs 79.7%, p < 0.001) and PFS (52.9% vs 74.8%, p < 0.001) than those with a low LAR level. MVA showed that the high LAR level was an adverse independent factor for DMFS (hazard ratio (HR) = 2.620;95% confidence interval (CI): 1.738–3.950;p < 0.001), OS (HR = 1.742;95% CI: 1.195–2.540;p = 0.004), and PFS (HR = 1.924;95% CI: 1.325–2.794;p < 0.001), while lactate dehydrogenase and albumin were dependent predictive of DMFS, OS and PFS. A subgroup survival analysis revealed significant correlations between LAR and clinical outcomes in both Epstein-Barr virus (EBV) DNA negative and positive populations and a trend toward statistically significant differences in DMFS in the EBV-DNA negative subgroup. Conclusions: Pre-treatment high LAR level was an independent adverse predictive factor for NPC patients and can serve as a predictive biomarker of prognosis, especially for DMFS.
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Copyright (c) 2022 Shu-lan Chen, Jun Li, Jin-gao Li, Xiao-ting Pan, Hong-wen Wu, Fei Xu
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Medical Genetics, University of Torino Medical School, Italy

Department of Biomedical, Surgical and Dental Sciences, University of Milan, Italy