Dataset Information

Noninvasive Prediction of Outcomes in Autoimmune Hepatitis-Related Cirrhosis.

ABSTRACT: The value of noninvasive tools in the diagnosis of autoimmune hepatitis (AIH)-related cirrhosis and the prediction of clinical outcomes is largely unknown. We sought to evaluate (1) the utility of liver stiffness measurement (LSM) in the diagnosis of cirrhosis and (2) the performance of the Sixth Baveno Consensus on Portal Hypertension (Baveno VI), expanded Baveno VI, and the ANTICIPATE models in predicting the absence of varices needing treatment (VNT). A multicenter cohort of 132 patients with AIH-related cirrhosis was retrospectively analyzed. LSM and endoscopies performed at the time of cirrhosis diagnosis were recorded. Most of the patients were female (66%), with a median age of 54 years. Only 33%-49% of patients had a LSM above the cutoff points described for the diagnosis of AIH-related cirrhosis (12.5, 14, and 16 kPa). Patients with portal hypertension (PHT) had significantly higher LSM than those without PHT (15.7 vs. 11.7 kPa; P = 0.001), but 39%-52% of patients with PHT still had LSM below these limits. The time since AIH diagnosis negatively correlated with LSM, with longer time being significantly associated with a lower proportion of patients with LSM above these cutoffs. VNT was present in 12 endoscopies. The use of the Baveno VI, expanded Baveno VI criteria, and the ANTICIPATE model would have saved 46%-63% of endoscopies, but the latter underpredicted the risk of VNT. Conclusions: LSM cutoff points do not have a good discriminative capacity for the diagnosis of AIH-related cirrhosis, especially long-term after treatment initiation. Noninvasive tools are helpful to triage patients for endoscopy.

SUBMITTER: Llovet LP

PROVIDER: S-EPMC9134802 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Noninvasive Prediction of Outcomes in Autoimmune Hepatitis-Related Cirrhosis.

Llovet Laura-Patricia LP Gratacós-Ginès Jordi J Téllez Luis L Gómez-Outomuro Ana A Navascués Carmen A CA Riveiro-Barciela Mar M Vinuesa Raquel R Gómez-Camarero Judith J García-Retortillo Montserrat M Díaz-Fontenla Fernando F Salcedo Magdalena M García-Eliz María M Horta Diana D Guerrero Marta M Rodríguez-Perálvarez Manuel M Fernández-Rodriguez Conrado C Albillos Agustín A G-Abraldes Juan J Parés Albert A Londoño Maria-Carlota MC

Hepatology communications 20220106 6

The value of noninvasive tools in the diagnosis of autoimmune hepatitis (AIH)-related cirrhosis and the prediction of clinical outcomes is largely unknown. We sought to evaluate (1) the utility of liver stiffness measurement (LSM) in the diagnosis of cirrhosis and (2) the performance of the Sixth Baveno Consensus on Portal Hypertension (Baveno VI), expanded Baveno VI, and the ANTICIPATE models in predicting the absence of varices needing treatment (VNT). A multicenter cohort of 132 patients with ...[more]

PMID: 34989164

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Project description:Objectives: Autoimmune hepatitis (AIH) can progress into severe outcomes, i.e., decompensated cirrhosis, from remarkable and persistent inflammation in the liver. Considering the energy-expending nature of inflammation, we tried to define the metabolomics signatures of AIH to uncover the underlying mechanisms of cirrhosis development and its metabolic biomarkers. Methods: Untargeted metabolomics analysis was performed on sera samples from 79 AIH patients at the stages (phenotypes) of non-cirrhosis (n = 27), compensated cirrhosis (n = 22), and decompensated cirrhosis (n = 30). Pattern recognition was used to find unique metabolite fingerprints of cirrhosis with or without decompensation. Results: Out of the 294 annotated metabolites identified, 2 metabolic fingerprints were found associated with the development of cirrhosis (independent of the decompensated state, 42 metabolites) and the evolution of decompensated cirrhosis (out of 47 metabolites), respectively. The cirrhosis-associated fingerprints (eigenmetabolite) showed better capability to differentiate cirrhosis from non-cirrhosis patients than the aminotransferase-to-platelet ratio index. From the metabolic fingerprints, we found two pairs of metabolites (Mesobilirubinogen/6-Hydroxynicotinic acid and LysoPA(8:0/0:0)/7alpha-Hydroxycholesterol) calculated as ratio of intensities, which revealed robust abilities to identify cirrhosis or predict decompensated patients, respectively. These phenotype-related fingerprint metabolites featured fundamental energy supply disturbance along with the development of AIH cirrhosis and progression to decompensation, which was characterized as increased lipolysis, enhanced proteolysis, and increased glycolysis. Conclusions: Remodeling of metabolism to meet the liver inflammation-related energy supply is one of the key signatures of AIH in the development of cirrhosis and decompensation. Therefore, drug regulation metabolism has great potential in the treatment of AIH.

Project description:Evaluating liver fibrosis is crucial for disease severity assessment, treatment decisions, and hepatocarcinogenic risk prediction among patients with chronic hepatitis C. In this retrospective multicenter study, we aimed to construct a novel model formula to predict cirrhosis. A total of 749 patients were randomly allocated to training and validation sets at a ratio of 2:1. Liver stiffness measurement (LSM) was made via transient elastography using FibroScan. Patients with LSM ≥12.5 kPa were regarded as having cirrhosis. The best model formula for predicting cirrhosis was constructed based on factors significantly and independently associated with LSM (≥12.5 kPa) using multivariate regression analysis. Among the 749 patients, 198 (26.4%) had LSM ≥12.5 kPa. In the training set, multivariate analysis identified logarithm natural (ln) type IV collagen 7S, ln hyaluronic acid, and ln Wisteria floribunda agglutinin positive Mac-2-binding protein (WFA+-Mac-2 BP) as the factors that were significantly and independently associated with LSM ≥12.5 kPa. Thus, the formula was constructed as follows: score = -6.154 + 1.166 × ln type IV collagen 7S + 0.526 × ln hyaluronic acid + 1.069 × WFA+-Mac-2 BP. The novel formula yielded the highest area under the curve (0.882; optimal cutoff, -0.381), specificity (81.5%), positive predictive values (62.6%), and predictive accuracy (81.6%) for predicting LSM ≥12.5 kPa among fibrosis markers and indices. These results were almost similar to those in the validated set, indicating the reproducibility and validity of the novel formula. The novel formula scores were significantly, strongly, and positively correlated with LSM values in both the training and validation data sets (correlation coefficient, 0.721 and 0.762; p = 2.67 × 10-81 and 1.88 × 10-48, respectively). In conclusion, the novel formula was highly capable of diagnosing cirrhosis in patients with chronic hepatitis C and exhibited better diagnostic performance compared to conventional fibrosis markers and indices.

Dataset Information

Noninvasive Prediction of Outcomes in Autoimmune Hepatitis-Related Cirrhosis.

Publications

Noninvasive Prediction of Outcomes in Autoimmune Hepatitis-Related Cirrhosis.

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