Metabolomics discloses potential biomarkers to predict the acute HVPG response to propranolol in patients with cirrhosis

医学 肝硬化 胃肠病学 内科学 门静脉压 失代偿 普萘洛尔 逻辑回归 单变量分析 逐步回归 门脉高压 多元分析
作者
Enric Reverter,Juan José Lozano,Cristina Alonso,Annalisa Berzigotti,Susana Seijó,Fanny Turón,Anna Baiges,M. Luz Martínez‐Chantar,José M. Mato,Ibon Martínez‐Arranz,Vincenzo La Mura,Virginia Hernández‐Gea,Jaume Bosch,Juan Carlos García–Pagán
出处
期刊:Liver International [Wiley]
卷期号:39 (4): 705-713 被引量:17
标识
DOI:10.1111/liv.14042
摘要

Abstract Background In cirrhosis, a decrease in hepatic venous pressure gradient (HVPG) > 10% after acute iv propranolol (HVPG response) is associated with a lower risk of decompensation and death. Only a part of patients are HVPG responders and there are no accurate non‐invasive markers to identify them. We aimed at discovering metabolomic biomarkers of HVPG responders to propranolol. Methods Sixty‐six patients with cirrhosis and HVPG ≥ 10 mm Hg in whom the acute HVPG response to propranolol was assessed, were prospectively included. A targeted metabolomic serum analysis using ultrahigh‐performance liquid chromatography coupled to mass spectrometry was performed. Different combinations of 2‐3 metabolites identifying HVPG responders (HVPG reduction > 10%) were obtained by stepwise logistic regression. The best of these model (AUROC, Akaike criterion) underwent internal cross‐validation and cut‐offs to classify responders/non‐responders was proposed. Results A total of 41/66 (62%) patients were HVPG responders. Three hundred and eighty‐nine metabolites were detected and 177 were finally eligible. Eighteen metabolites were associated to the HVPG response at univariate analysis; at multivariable analysis, a model including a phosphatidylcholine (PC(P‐16:0/22:6)) and a free fatty acid (20:2(n‐6), eicosadienoic acid) performed well for HVPG response, with an AUROC of 0.801 (0.761 at internal validation). The cut‐off 0.629 was the most efficient for overall classification (49/66 patients correctly classified). Two cut‐off values allowed identifying responders (0.688, PPV 84%) and non‐responders (0.384, NPV 82%) with undetermined values for 17/66 patients. Clinical variables did not add to the model. Conclusions The combination of two metabolites helps at identifying HVPG responders to acute propranolol. It could be a useful non‐invasive test to classify the HVPG response to propranolol.
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