Neutrophil-to-Lymphocyte Ratio; an Independent Predictor of Mortality or Just a Surrogate Marker of Underlying Complications?

Mac-2-Binding Protein Glycosylation Isomer to Albumin Ratio Predicts Bacterial Infections in Cirrhotic Patients

INTRODUCTION

Mac-2-binding protein glycosylation isomer (M2BPGi) is a novel biomarker for liver fibrosis, but little is known about its role in cirrhosis-associated clinical outcomes. This study aimed to investigate the predictive role of M2BPGi in cirrhosis-associated complications.

METHODS

One hundred and forty-nine cirrhotic patients were retrospectively enrolled. Patients were followed up for 1 year, and cirrhosis-associated clinical events were recorded. Receiver operating characteristic curve (ROC) analysis was used to establish the values of the predictive models for cirrhotic outcomes, and Cox proportional hazards regression models were used to identify predictors of clinical outcomes.

RESULTS

Sixty (40.3%) patients experienced cirrhosis-associated clinical events and had higher M2BPGi levels compared to those without events (8.7 vs. 5.1 cutoff index, p < 0.001). The most common cirrhosis-associated complications were bacterial infections (24.2%). On ROC analysis, M2BPGi to albumin ratio (M2BPGi/albumin) had comparable discriminant abilities for all cirrhosis-associated events (area under the ROC curve [AUC] = 0.74) compared with M2BPGi, Child-Pugh, model for end-stage liver disease, albumin-bilirubin scores, and neutrophil-to-lymphocyte ratio and was superior to M2BPGi alone for all bacterial infectious events (AUC = 0.80). Cox regression analysis revealed that the M2BPGi/albumin, but not M2BPGi alone, independently predicted all cirrhosis-associated events (hazard ratio [HR] = 1.34, p = 0.038) and all bacterial infectious events (HR = 1.51, p = 0.011) within 1 year. However, M2BPGi/albumin did not predict other cirrhotic complications and transplant-free survival.

DISCUSSION/CONCLUSION

M2BPGi/albumin might serve as a potential prognostic indicator for patients with cirrhosis, particularly for predicting bacterial infections.