In:
Journal of Clinical Gastroenterology, Ovid Technologies (Wolters Kluwer Health), Vol. 57, No. 2 ( 2022-01-10), p. 189-197
Abstract:
Liver biopsy and hepatic venous pressure gradient (HVPG), the gold standard for assessing advanced fibrosis (AF) and clinically significant portal hypertension (CSPH), are invasive, costly, and time-consuming. Goal: We investigated if the combination of fibrosis index based on 4 factors (FIB-4) and liver stiffness measure (LSM) can identify AF and more importantly, CSPH. Patients and Methods: Patients with chronic liver disease referred for transjugular liver biopsy were analyzed retrospectively. FIB-4 and LSM were compared with liver histology for diagnosing AF. FIB-4, LSM, and platelet count were compared with HVPG for diagnosing CSPH. Optimal cutoffs for predicting CSPH were determined by grid search. A composite log-odds to predict CSPH was derived from logistic regression using LSM, FIB-4, and gender. Internal bootstrap validation and external validation were performed. Results: A total of 142 patients were included in the derivation; 42.3% had AF, and 11.3% had CSPH using the current gold standards. The area under the receiver operating characteristic curve (AUROC) for LSM, FIB-4, and their combination to predict AF were 0.7550, 0.7049, and 0.7768, respectively. LSM, FIB-4, and platelet count predicted CSPH with AUROC 0.6818, 0.7532, and 0.7240, respectively. LSM plus FIB-4 showed the best performance in predicting CSPH with AUROC 0.8155. Based on LSM, FIB-4, and gender, a novel model—the Portal Hypertension Assessment Tool (PHAT)—was developed to predict CSPH. PHAT score ≥−2.76 predicted CSPH with sensitivity 94%, specificity 67%, positive predictive value 27%, negative predictive value 99%, and accuracy 70%. In internal and external validation, AUROCs for the model were 0.8293 and 0.7899, respectively. Conclusion: A model consisting of FIB-4, LSM, and gender can identify CSPH among patients with chronic liver disease.
Type of Medium:
Online Resource
ISSN:
1539-2031
DOI:
10.1097/MCG.0000000000001664
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2022
detail.hit.zdb_id:
2041558-8
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