Long-term survival of hepatocellular carcinoma after percutaneous radiofrequency ablation guided by ultrasound.

BACKGROUND: The risk factors for recurrence and death after radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC) remain poorly known. This study was aimed to study the 10-year overall survival (OS) of HCC treated by ultrasound (US)-guided RFA and the risk factors for recurrence and death. METHODS: Between June 2005 and June 2016, 1000 patients with HCC treated by US-guided RFA at 4 hospitals in China; among them, 525 patients met the criteria for radical ablation and 410 had high AFP levels before RFA treatment. Clinical and biochemical factors were tested for association with recurrence and survival. Patients were divided into the recurrence (n = 348) and no recurrence groups (n = 62). RESULTS: The 5- and 10-year survival rates were 66 and 35%, respectively. Tumor size (HR = 1.36, 95% CI 1.12-1.65), albumin levels (HR = 0.76, 95% CI 0.65-0.91), prothrombin time (HR = 2.18, 95% CI 1.54-3.10), and α-fetoprotein levels (HR = 1.13, 95% CI 1.00-1.26) were independently associated with mortality after RFA for HCC. Tumor size (HR = 1.27, 95% CI: 1.15-1.40), HBV-DNA (HR = 7.70, 95% CI 3.57-16.63), AFP levels before treatment (HR = 2.172, 95% CI 1.256-3.756, P = 0.006), and AFP response (HR = 4.722, 95% CI 1.053-21.184, P = 0.0427) were independently associated with the risk of recurrence of HCC after RFA. The median survival of the patients with and without recurrence after RFA was 54 (95% CI 45-58) and 62 (95% CI 48-80) months, respectively (log-rank, P = 0.04). CONCLUSIONS: Tumor size, albumin, prothrombin time, and α-fetoprotein levels were independently associated with mortality after US-guided RFA for HCC, while tumor size and HBV-DNA were independently associated with recurrence. Patients with recurrence had a poorer survival compared with those without.

Association between chitinase-3-like protein 1 and metabolic-associated fatty liver disease in patients with type 2 diabetes mellitus.

BACKGROUND AND AIM: Early identification of liver fibrosis is essential for the prognosis of metabolic-associated fatty liver disease (MAFLD), particularly in type 2 diabetes mellitus (T2DM) patients. Here, we explored the association of chitinase-3-like protein 1 (CHI3L1) and liver fibrosis in T2DM-MAFLD patients. METHODS: Liver fibrosis was staged in T2DM-MAFLD patients, and a liver stiffness measurement (LSM) of ≥ 8 kPa was used to differentiate between non-significant (NSLF) and significant liver fibrosis (SLF) subgroups. The two subgroups were compared for serum CHI3L1 and other parameters. Linear correlation, logistic regression, and restricted cubic spline (RCS) analyses were performed to evaluate the association between CHI3L1 and liver fibrosis. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of CHI3L1. RESULTS: Among T2DM-MAFLD, SLF patients had higher CHI3L1 compared to NSLF patients. CHI3L1 was found to be positively correlated with LSM. Multivariate logistic regression analysis suggested that CHI3L1 may be a potential independent risk factor for SLF. Further stratified analysis indicated that the odds ratios of SLF in the high CHI3L1 group were higher than in the low CHI3L1 group in the subgroups. RCS analysis suggested an increasing trend in the incidence of significant fibrosis with the rising level of CHI3L1. The area under the ROC curve for detecting significant fibrosis was 0.749 (95% CI: 0.668-0.829). CONCLUSIONS: Serum CHI3L1 demonstrates an association with significant liver fibrosis. High serum levels of CHI3L1 may indicate the existence of significant liver fibrosis in T2DM-MAFLD patients.

Association between triglyceride glucose-body mass index and the staging of non-alcoholic steatohepatitis and fibrosis in patients with non-alcoholic fatty liver disease.

OBJECTIVE: The objective of this study was to thoroughly investigate the clinical value of triglyceride glucose-body mass index (TyG-BMI) in patients diagnosed with non-alcoholic fatty liver disease (NAFLD). Specifically, we aimed to determine its association with non-alcoholic steatohepatitis (NASH) and the progression of liver fibrosis. METHODS: The study included 393 patients diagnosed with NAFLD after liver biopsy. The patients were divided into two distinct cohorts: a training cohort (N = 320) and a validation cohort (N = 73). The training cohort was further divided into four groups based on TyG-BMI quartiles. The clinical characteristics of the patients in each group were compared in detail, and the association between TyG-BMI and NASH, NAFLD Activity Score (NAS) ≥ 4, at-risk NASH, significant fibrosis, advanced fibrosis, and cirrhosis was analyzed using multiple models. Additionally, we generated receiver operating characteristic (ROC) curves to evaluate the predictive ability of TyG-BMI for NASH and fibrosis staging in patients with NAFLD. RESULTS: Patients with higher TyG-BMI values had a significantly higher prevalence of NASH, NAS ≥ 4, at-risk NASH, significant fibrosis, advanced fibrosis, and cirrhosis (all p < .05). TyG-BMI was an independent predictor of these diseases in both unadjusted and adjusted models (all p < .05). ROC curve analysis further revealed the excellent performance of TyG-BMI in predicting NASH, NAS ≥ 4, at-risk NASH, significant fibrosis, advanced fibrosis, and cirrhosis. The validation cohort yielded analogous results. Furthermore, we constructed three multivariate models of TyG-BMI in conjunction with elastography metrics, which demonstrated elevated diagnostic AUC values of 0.782, 0.792, 0.794, 0.785, 0.834, and 0.845, respectively. CONCLUSION: This study confirms a significant association between insulin resistance and NAFLD, including at-risk NASH and fibrosis staging, as assessed using the TyG-BMI index. TyG-BMI and its associated multivariate models can be valuable noninvasive indicators for NAFLD diagnosis, risk stratification, and disease course monitoring.

Association of Non-Invasive Markers with Significant Fibrosis in Patients with Nonalcoholic Fatty Liver Disease: A Cross-Sectional Study.

Purpose: The identification of significant fibrosis is critical for predicting the prognosis of non-alcoholic fatty liver disease (NAFLD). This study aimed to compare the predictive value of chitinase-3-like protein 1 (CHl3L1) and other non-invasive biomarkers, as well as to establish a novel non-invasive diagnostic model for assessing the risk of significant fibrosis in NAFLD. Patients and Methods: A total of 71 patients with confirmed NAFLD based on liver biopsy were included in this study. Serum CHI3L1 levels and other non-invasive fibrosis assessment measures were determined. The aspartate aminotransferase-to-platelet ratio index (APRI) and Fibrosis-4 Index (FIB-4) were calculated to assess the diagnostic superiority of serum CHI3L1 compared to other non-invasive fibrosis assessment measures. Multivariate logistic regression analysis was conducted to identify relevant variables for constructing a diagnostic model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of each index, including the area under ROC curve (AUC), sensitivity, and specificity. A nomogram was established based on the logistic regression model. Results: Serum CHI3LI levels were found to be higher in NAFLD patients with significant fibrosis compared to those without significant fibrosis. Multivariate logistic regression analysis revealed that aspartate aminotransferase (AST), type IV collagen (IV-C), CHI3L1, and liver stiffness measurement (LSM) were identified as potential independent risk factors associated with significant fibrosis in patients. The AUC of CHI3L1 for diagnosing significant liver fibrosis was 0.716 (0.596,0.836), with the optimal cut-off point of 125.315. The nomogram incorporating CHI3LI, AST, IV-C, and LSM further improved the potential predictive value, with an AUC for diagnosing significant fibrosis of 0.864 (0.766,0.962). This was superior to IV-C, CHI3L1, LSM, and APRI (all p < 0.05). Conclusion: The diagnostic model constructed by CHI3L1 combined with the existing non-invasive markers AST, IV-C, and LSM can help assess the risk of significant liver fibrosis in NAFLD.

A longitudinal observational retrospective study on risk factors and predictive model of PICC associated thrombosis in cancer patients.

To analyze the incidence of PICC associated venous thrombosis. To predict the risk factors of thrombosis. To validate the best predictive model in predicting PICC associated thrombosis. Consecutive oncology cases in 341 who initially naive intended to be inserted central catheter for chemotherapy, were recruited to our dedicated intravenous lab. All patients used the same gauge catheter, Primary endpoint was thrombosis formation, the secondary endpoint was infusion termination without thrombosis. Two patients were excluded. 339 patients were divided into thrombosis group in 59 (17.4%) and non-thrombosis Group in 280 (82.6%), retrospectively. Tumor, Sex, Age, Weight, Height, BMI, BSA, PS, WBC, BPC, PT, D-dimer, APTT, FIB, Smoking history, Location, Catheter length, Ratio and Number as independent variables were analyzed by Fisher's scoring, then Logistic risk regression, ROC analysis and nomogram was introduced. Total incidence was 17.4%. Venous mural thrombosis in 2 (3.4%), "fibrin sleeves" in 55 (93.2%), mixed thrombus in 2 (3.4%), symptomatic thrombosis in 2 (3.4%), asymptomatic thrombosis in 57 (96.6%), respectively. Height (χ² = 4.48, P = 0.03), D-dimer (χ² = 37.81, P < 0.001), Location (χ² = 7.56, P = 0.006), Number (χ² = 43.64, P < 0.001), Ratio (χ² = 4.38, P = 0.04), and PS (χ² = 58.78, P < 0.001), were statistical differences between the two groups analyzed by Fisher's scoring. Logistic risk regression revealed that Height (ß = -0.05, HR = 0.95, 95%CI: 0.911-0.997, P = 0.038), PS (ß = 1.07, HR = 2.91, 95%CI: 1.98-4.27, P < 0.001), D-dimer (ß0.11, HR = 1.12, 95%CI: 1.045-1.200, P < 0.001), Number (ß = 0.87, HR = 2.38, 95% CI: 1.619-3.512, P < 0.001) was independently associated with PICC associated thrombosis. The best prediction model, D-dimer + Number as a novel co-variable was validated in diagnosing PICC associated thrombosis before PICC. Our research revealed that variables PS, Number, D-dimer and Height were risk factors for PICC associated thrombosis, which were slightly associated with PICC related thrombosis, in which, PS was the relatively strongest independent risk factor of PICC related thrombosis.