Abstract:Objective: To establish a new prediction model combing the inflammatory markers including neutrophil/lymphocyte ratio (NLR) and red blood cell distribution width (RDW) with several hematological testing indicators to assess the prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). Methods: Clinical data and laboratory testing indicators of 577 patients from three hospitals were collected in this study. The model for end-stage liver disease (MELD) score was used to establish the new model cohort of 554 patients with MELD score between 9 points and 40 points. Univariate and multivariate COX regression analysis were used to identify the independent risk factor associated with the prognosis of patients with HBV-ACLF, so as to establish the prognostic assessment model. And ROC curves were applied to validate the new model in predicting the 90-day prognosis in patients with HBV-ACLF in three hospitals, respectively. SPSS 22.0 software was employed for data analyses. Results: Multivate COX regression analysis showed that RDW, NLR, international normalized ratio (INR), and creatinine (Cr) and total bilirubin (TBIL) were independent factors of 90-day prognosis in patients with HBV-ACLF (P<0.05). The prediction model was established according to the multivariate Cox regression analysis, COXRNTIC=0.073×RDW+0.027×NLR+0.004×TBIL+0.236×INR+0.005×Cr (P=0.000), with a cut-off value of 3.59 (sensitivity: 78.48%, specificity: 84.86%). ROC curve was used to detect the predictive ability and the results showed that RNTIC (0.864, 95%CI=0.837-0.903) was better than MELD score (0.737, 95%CI=0.698-0.773), NLR (0.705, 95%CI=0.665-0.743) and RDW (0.677, 95%CI=0.637-0.716) (P=0.000). In the validation cohort, RNTIC model demonstrated a better predictive value of death than RDW, NLR, and MELD score in three hospitals. Conclusion: The short-term prognostic prediction model of HBV-ACLF which is established on the basis of inflammatory markers of RDW and NLR has a better predictive value when compared with MELD score, and is a reliable clinical predictive model.