Chronic hepatitis B virus (HBV) infection is a major global health issue, and the prognosis of patients with HBV-associated acute-on-chronic hepatic failure (ACLF) is extremely poor. In this study, the efficacy of lamivudine was investigated in patients with ACLF. The effects of HBV DNA load and its related factors on the prognosis were also further explored. A matched retrospective cohort study using data on ACLF patients derived from our hospital database was conducted. One hundred and thirty patients receiving lamivudine were selected into the lamivudine treatment group with another 130 without lamivudine treatment studied as control. They were matched for sex, age and imaging finding with the lamivudine treatment group. All the patients were followed up for 3 months and the survival rates were compared. The influential factors on the mortality were studied by the Cox proportional hazards model. The cumulative survival rates of patients in the lamivudine group were higher than those of the control group (chi(2) = 9.50, P = 0.0021). The mortality of patients in the high virus load group (71/95, 74.7%) was higher than that of those in the low virus load group (15/29, 51.7%) (chi(2) = 5.536, P = 0.019). For patients with a Model for End-Stage Liver Disease (MELD) score of 20-30 by week 4, the mortality of those with HBV DNA that was undetectable or declined for more than 2 log(10) (2/12, 16.7%; 18/40, 45.0%) was lower than that of those with a less than 2 log(10) decline (18/23, 78.3%) (chi(2) = 10.106, P = 0.001). In the Cox proportional hazards model, for patients with a MELD score of 20-30, treatment method (P = 0.002), pretreatment HBV DNA load (P = 0.007) and decline of HBV DNA load during therapy (P = 0.003) were independent predictors; for those with a MELD score of above 30, MELD score (P = 0.008) was the only independent predictor. Lamivudine can significantly decrease the 3-month mortality of patients with a MELD score of 20-30, and a low pretreatment viral load and rapid decline of HBV DNA load are good predictors for the outcome of the treatment.