Better performance of PIVKA-II for detecting hepatocellular carcinoma in patients with chronic liver disease with normal total bilirubin.

BACKGROUND: Serum protein induced by vitamin K absence or antagonist-II (PIVKA-II) is a promising biomarker for hepatocellular carcinoma (HCC) surveillance. AIM: To identify the contributing factors related to the abnormal elevation of PIVKA-II level and assess their potential influence on the performance of PIVKA-II in detecting HCC. METHODS: This study retrospectively enrolled in 784 chronic liver disease (CLD) patients and 267 HCC patients in Mengchao Hepatobiliary Hospital of Fujian Medical University from April 2016 to December 2019. Logistic regression and the area under the receiver operating characteristic curve (AUC) were used to evaluate the influencing factors and diagnostic performance of PIVKA-II for HCC, respectively. RESULTS: Elevated PIVKA-II levels were independently positively associated with alcohol-related liver disease, serum alkaline phosphatase (ALP), and total bilirubin (TBIL) for CLD patients and aspartate aminotransferase (AST) and tumor size for HCC patients (all P < 0.05). Serum PIVKA-II were significantly lower in patients with viral etiology, ALP ≤ 1 × upper limit of normal (ULN), TBIL ≤ 1 × ULN, and AST ≤ 1 × ULN than in those with nonviral disease and abnormal ALP, TBIL, or AST (all P < 0.05), but the differences disappeared in patients with early-stage HCC. For patients with TBIL ≤ 1 × ULN, the AUC of PIVKA-II was significantly higher compared to that in patients with TBIL > 1 × ULN (0.817 vs 0.669, P = 0.015), while the difference between ALP ≤ 1 × ULN and ALP > 1 × ULN was not statistically significant (0.783 vs 0.729, P = 0.398). These trends were then more prominently perceived in subgroups of patients with viral etiology and HBV alone. CONCLUSION: Serum PIVKA-II has better performance in detecting HCC at an early stage for CLD patients with normal serum TBIL.

The clinical application of PIVKA-II in hepatocellular carcinoma and chronic liver diseases: A multi-center study in China.

BACKGROUND: Due to the absence of specific symptoms and low survival rate, efficient biomarkers for hepatocellular carcinoma (HCC) diagnosis are urgently required. The purpose of this study was to evaluate the diagnostic performance of protein induced by vitamin K absence or antagonist-II (PIVKA-II) and to determine the optimal cutoff values for HBV infection-related HCC. METHODS: We conducted a cross-sectional, multi-center study in China to ascertain the cutoff value for HCC patients in the context of CHB- and HBV-related cirrhosis. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were used to evaluate the diagnostic performance of PIVKA-II. RESULTS: This study enrolled 784 subjects and demonstrated that PIVKA-II had a sensitivity of 84.08% and a specificity of 90.43% in diagnosis HCC from chronic liver diseases. PIVKA-II at a cutoff of 37.5 mAU/mL yielded an AUC of 0.9737 (sensitivity 91.78% and specificity 96.30%) in discriminating HCC from chronic hepatitis B (CHB) patients. PIVKA-II at a cutoff of 45 mAU/mL yielded an AUC of 0.9419 (sensitivity 77.46% and specificity 95.12%) in discriminating HCC- from HBV-related cirrhosis patients. Furthermore, using a cutoff value of 40 mAU/mL for PIVKA-II as an HCC marker, only 4.81% (15/312) was positive in chronic hepatitis and 12.80% (37/289) in cirrhosis patients, revealing the satisfactory specificity of PIVKA-II in chronic liver disease of different etiologies. CONCLUSION: Our data indicated that PIVKA-II had satisfactory diagnostic efficiencies and could be used as a screening or surveillance biomarker in HCC high-risk population.

Developing a risk prediction model for multidrug-resistant bacterial infection in patients with biliary tract infection.

BACKGROUND/AIMS: The aim of this study was to develop a tool to predict multidrug-resistant bacteria infections among patients with biliary tract infection for targeted therapy. PATIENTS AND METHODS: We conducted a single-center retrospective descriptive study from January 2016 to December 2018. Univariate and multivariable logistic regression analysis were used to identify independent risk factors of multidrug-resistant bacterial infections. A nomogram was constructed according to multivariable regression model. Moreover, the clinical usefulness of the nomogram was estimated by decision curve analysis. RESULTS: 121 inpatients were randomly divided into a training cohort (n = 79) and validation cohort (n = 42). In multivariate analysis, 5 factors were associated with biliary tract infections caused by multidrug-resistant bacterial infections: aspartate aminotransferase (Odds ratio (OR), 13.771; 95% confidence interval (CI), 3.747-64.958; P < 0.001), previous antibiotic use within 90 days (OR, 4.130; 95% CI, 1.192-16.471; P = 0.032), absolute neutrophil count (OR, 3.491; 95% CI, 1.066-12.851; P = 0.046), previous biliary surgery (OR, 3.303; 95% CI, 0.910-13.614; P = 0.079), and hemoglobin (OR, 0.146; 95% CI, 0.030-0.576; P = 0.009). The nomogram model was constructed based on these variables, and showed good calibration and discrimination in the training set [area under the curve (AUC), 0.86] and in the validation set (AUC, 0.799). The decision curve analysis demonstrated the clinical usefulness of our nomogram. Using the nomogram score, high risk and low risk patients with multidrug-resistant bacterial infection could be differentiated. CONCLUSIONS: This simple bedside prediction tool to predict multidrug-resistant bacterial infection can help clinicians identify low versus high risk patients as well as choose appropriate, timely initial empirical antibiotics therapy. This model should be validated before it is widely applied in clinical settings.