Multivariate logistic regression analysis was used to develop a m

Multivariate logistic regression analysis was used to develop a model for differentiating HCC from CLD. The model was developed using a subset BAY 57-1293 datasheet of 98 HCC patients and 104 CLD patients with advanced fibrosis or cirrhosis (Metavir F3-4) and then validated using an independent set (37 HCC and 44 CLD (F3-4)). Results:  A UPS signature model incorporating six markers (trypsin-like, caspase-like, chymotrypsin-like, and normalized chymotrypsin-like activities of proteasomes;

AFP; and DCP) accurately differentiated HCC from CLD (area under the curve = 0.938 [95% confidence interval, 0.884–0.991]). When analysis was restricted to patients with tumors ≤ 3 cm, the UPS model exhibited higher sensitivity (83.1% vs 51.8%) and specificity (90.2%

vs 83.7%) than the three conventional markers, with good positive predictive values (34.2% vs 15.1%). These results were confirmed in the independent validation set. Conclusion:  The UPS signature in combination with AFP and DCP provides sensitive and specific differentiation of HCC in patients with CLD. The importance of the UPS in HCC suggests that therapeutic approaches targeting the UPS should be explored. “
“Non-alcoholic steatohepatitis (NASH) is the progressive form of non-alcoholic fatty liver disease (NAFLD). Navitoclax mouse A liver biopsy is considered the “gold standard” for diagnosing/staging NASH. Identification of NAFLD/NASH using non-invasive tools is important for intervention. The study aims were to:

develop/validate the predictive performance of a non-invasive model (index of NASH [ION]); assess the performance of a recognized non-invasive model (fatty liver index [FLI]) compared with ION for NAFLD diagnosis; determine which non-invasive model (FLI, ION, or NAFLD fibrosis score [NFS]) performed best in predicting age-adjusted mortality. From the National Health and Nutrition Examination Survey III database, Org 27569 anthropometric, clinical, ultrasound, laboratory, and mortality data were obtained (n = 4458; n = 861 [19.3%] NAFLD by ultrasound) and used to develop the ION model, and then to compare the ION and FLI models for NAFLD diagnosis. For validation and diagnosis of NASH, liver biopsy data were used (n = 152). Age-adjusted Cox proportional hazard modeling estimated the association among the three non-invasive tests (FLI, ION, and NFS) and mortality. FLI’s threshold score > 60 and ION’s threshold score > 22 had similar specificity (FLI = 80% vs ION = 82%) for NAFLD diagnosis; FLI < 30 (80% sensitivity) and ION < 11 (81% sensitivity) excluded NAFLD. An ION score > 50 predicted histological NASH (92% specificity); the FLI model did not predict NASH or mortality. The ION model was best in predicting cardiovascular/diabetes-related mortality; NFS predicted overall or diabetes-related mortality.

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