A Day-4 Lille Model Predicts Response to Corticosteroids and Mortality in Severe Alcoholic Hepatitis.

OBJECTIVES

Prednisolone therapy increases the risk of infections in patients with severe alcoholic hepatitis (SAH). We evaluated whether the use of the Lille Model at day 4 (LM4) is useful to predict response to prednisolone compared with the classic day 7 (LM7) in order to limit a futile exposure to corticosteroids.

METHODS

We performed a retrospective analysis of a large multinational cohort of patients with SAH with Maddrey's discriminant function (DF) ≥32. Response to corticosteroids was assessed with LM4 and LM7, according to the validated cutoff value (CUV>0.45). Receiver operating characteristics (ROC) curves were constructed to determine the optimal CUV for LM4 and to compare accuracy between LM4, LM7, MELD (Model for End-Stage Liver Disease), and ABIC (age, bilirubin, international normalized ratio, and creatinine). Logistic regression models were constructed to predict 28- and 90-day mortality. Cox regression analysis was performed to assess long-term survival.

RESULTS

A total of 163 (62.7%) out of 260 patients received corticosteroids. The median DF for the patients treated with corticosteroids was 64.1 (47.9-81.3). Overall 90-day mortality was 35.9%. The median LM4 and LM7 for the patients who received treatment was 0.39 (0.19-0.83) and 0.36 (0.13-0.77). LM4 was a strong independent predictor of 28-day mortality (OR 25.4, (95% confidence interval (CI) 5.1-126.8), P<0.001). By using LM4 with a CUV>0.45, 28- and 90-day survival was significantly higher for responders (90% and 76%) than non-responders (66% and 40%), P<0.001. Importantly, the area under the ROC curve for predicting mortality for LM4 was similar than the classic LM7 (0.77 vs. 0.75, respectively: P=0.558).

CONCLUSIONS

LM4 is as accurate as LM7 in predicting response to corticosteroids, as well as 28- and 90-day mortality. Assessing the efficacy of prednisolone at an earlier time point can avoid a more prolonged futile use of this therapy.