Metabolomics as a tool to predict the risk of decompensation or liver related death in patients with compensated cirrhosis.

BACKGROUND AIMS Patients with compensated cirrhosis with clinically significant portal hypertension (CSPH: HVPG >10 mmHg) have a high risk of decompensation. HVPG is, however, an invasive procedure not available in all centers. The present study aims to assess whether metabolomics can improve the capacity of clinical models in predicting clinical outcome in these compensated patients. APPROACH RESULTS This is a nested study from the PREDESCI cohort (a RCT of non-selective beta blockers (NSBB) versus placebo in 201 patients with compensated cirrhosis and CSPH) including 167 patients for whom a blood sample was collected. A targeted metabolomic serum analysis, using UHPLC-MS, was performed. Metabolites underwent univariate time-to event cox regression analysis. Top ranked metabolites were selected using LogRank P-value to generate a stepwise cox model. Comparison between models was done using DeLong's test. Eighty-two patients with CSPH were randomized to NSBB and 85 to placebo. Thirty-three patients developed the main endpoint (decompensation/liver-related death). The model including HVPG, Child-Pugh and treatment received (HVPG/Clinical model) had a C-index of 0.748 [CI95% 0.664-0.827]. Addition of two metabolites, Ceramide (d18:1/22:0) and Methionine (HVPG/Clinical/Metabolite model) significantly improved model's performance (C-index of 0.808 [CI95% 0.735-0.882]; P=0.032). The combination of these two metabolites together with Child-Pugh and type of treatment received (Clinical/Metabolite model) had a C-Index of 0.785 [CI95% 0.710-0.860] not significantly different from the HVPG based models including or not metabolites. CONCLUSIONS In patients with compensated cirrhosis and CSPH, metabolomics improves the capacity of clinical models and achieves similar predictive capacity than models including HVPG