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Composed of obesity and lipid parameters, the cardiometabolic index (CMI) has emerged as a novel diagnostic tool. Originally developed for diabetes diagnosis, its application has expanded to identifying patients with cardiovascular diseases, such as atherosclerosis and hypertension. However, the relationship between CMI and non-alcoholic fatty liver disease (NAFLD) and liver fibrosis in the US population remains unclear. This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2017–2020, involving 2996 participants aged 20 years or older. Vibration controlled transient elastography using a FibroScan® system (model 502, V2 Touch) with controlled attenuation parameter measurements identified NAFLD at a threshold of ≥ 274 dB/m, while liver stiffness measurement (LSM) results (median, ≥ 8.2 kPa) indicated fibrosis. A multifactorial logistic regression model explored the relationship between CMI and NAFLD and fibrosis. The effectiveness of CMI in detecting NAFLD and liver fibrosis was assessed through receiver operating characteristic curve analysis. Controlling for potential confounders, CMI showed a significant positive association with NAFLD (adjusted OR = 1.44, 95% CI 1.44–1.45) and liver fibrosis (adjusted OR = 1.84, 95% CI 1.84–1.85). The Areas Under the Curve for predicting NAFLD and fibrosis were 0.762 (95% CI 0.745 ~ 0.779) and 0.664(95% CI 0.633 ~ 0.696), respectively, with optimal cut-off values of 0.462 and 0.527. There is a positive correlation between CMI and NAFLD and fibrosis, which is a suitable and simple predictor of NAFLD and fibrosis. [ABSTRACT FROM AUTHOR]

Purpose: Patients with chronic hepatitis B (CHB) remain at risk for hepatocellular carcinoma during antiviral therapy. We aimed to clarify the values of alpha-fetoprotein (AFP), lectin-reactive fraction of AFP (AFP-L3), and des-γ-carboxyprothrombin (DCP) for early warning of HCC. Methods: A total of 1348 CHB patients received antiviral therapy and follow-up every 26 weeks. Eighty-four patients with HCC were age-, sex-, and cirrhosis-matched with 168 controls. AFP, AFP-L3, and DCP were compared between the groups from 104 weeks before HCC diagnosis (− 104 w) to the time of diagnosis (0 w). Results: Of the 84 HCC patients, 60 (71.4%) had early-stage HCC, AFP increased from − 26 w, and AFP-L3 and DCP increased from − 78 w. However, levels were unchanged in controls. ΔAFP, ΔAFP-L3, and ΔDCP showed similar abilities for predicting HCC (P > 0.05). Receiver operating characteristic curve analysis showed that AFP had better diagnostic performance for HCC than AFP-L3, DCP, or their combination. The cut-off values of AFP, AFP-L3, and DCP were 5.3 ng/mL, 1.05%, and 31.5 mAU/mL, respectively. Notably, lower AFP values were required to diagnose HCC in patients with detectable HBV DNA (4.1 ng/mL) or elevated alanine aminotransferase (5.2 ng/mL). Conclusions: Changes in AFP, AFP-L3, and DCP can help to predict HCC in CHB patients receiving antiviral therapy. A lower AFP value is needed to diagnose HCC, especially in patients with detectable HBV DNA or elevated alanine aminotransferase. [ABSTRACT FROM AUTHOR]

INTRODUCTION: To assess comparative performance of 14 hepatocellular carcinoma (HCC) prediction models in chronic hepatitis B (CHB) patients using on-treatment values at different timepoints. METHODS: Based on a nationwide prospective cohort of 986 treatment-naive CHB patients undergoing entecavir therapy with every 26-week follow-up, 14 HCC risk scores were calculated using on-treatment values at week 26, 52, 78, and 104, respectively. Model performance predicting 3-year HCC was assessed using time-dependent area under the receiver operating characteristic curve (AUC) and calibration index. Model cutoffs were validated through common diagnostic accuracy measures. RESULTS: During median 4.7-year follow-up, 56 (7.5%) developed HCC. Discrimination using on-treatment values within first 2 years was generally acceptable for most models (AUCs ranging from 0.68 to 0.81), except for REACH-B, NGM-HCC, and PAGE-B, although AUCs slightly decreased from week 26 to 104. Of these, REAL-B, CAMD, GAG-HCC, AASL-HCC, LSM-HCC, mPAGE-B, and mREACH-BII showed highest discrimination with AUCs ranging from 0.76 to 0.81, 0.72 to 0.76, 0.70 to 0.76, and 0.71 to 0.74 when reassessment at week 26, 52, 78, and 104, respectively. With reassessment within first 2 years, both REAL-B and CAMD calibrated well (Brier score ranging from 0.037 to 0.052). Of 9 models reporting cutoffs, REAL-B, AASL-HCC, and mPAGE-B using on-treatment values could identify 30%–40% of patients as low risk with minimal HCC incidence in the low-risk group (0.40% [REAL-B]–1.56% [mPAGE-B]). DISCUSSION: In this undergoing antiviral treatment CHB cohort, most HCC prediction models performed well even using on-treatment values during first 2 years, particularly REAL-B, AASL-HCC, CAMD, and mPAGE-B model. [ABSTRACT FROM AUTHOR]

Background: Delayed bleeding is an important adverse event after gastric endoscopic submucosal dissection (ESD). We aimed to externally validate the Bleeding after ESD Trend from Japan (BEST-J) score and subsequently develop a risk prediction model for bleeding in Chinese patients with early gastric cancer (EGC) after ESD. Methods: The clinical data of patients who underwent ESD for EGC in Beijing Friendship Hospital from June 2013 to December 2019 were collected retrospectively. The BEST-J score was evaluated according to the clinical data. Through univariate and multivariate logistic regression analyses of the clinical data, the factors affecting delayed bleeding were identified, and a new risk prediction model for bleeding was established. Receiver operating characteristic (ROC) curves were used to evaluate the predictive value of the two prediction models. Results: A total of 444 patients with EGC undergoing ESD were included, of whom 27 patients had delayed bleeding (6.1%). Multivariate logistic regression analysis showed that a history of smoking (P = 0.029), tumor size > 20 mm (P = 0.022), intraoperative use of hemoclips (P = 0.025), resection of multiple tumors (P = 0.027), and prolongation of activated partial thromboplastin time (APTT) (P = 0.020) were independent influencing factors for delayed bleeding. ROC curve analysis showed that the areas under the curves (AUCs) were different between the BEST-J score and the newly built prediction model (0.624 vs. 0.749, P = 0.012). Conclusions: The BEST-J score has moderately good discrimination for Chinese patients with EGC. However, for patients with EGC without severe comorbidities, the new risk prediction model may predict delayed bleeding better than the BEST-J score. [ABSTRACT FROM AUTHOR]

Objectives: We aimed to determine the value of MR-based preoperative nomograms in predicting DNA copy number (CN) subtype in lower grade glioma (LGG) patients. Methods: The overall survival (OS) data were analyzed. MRI data of 170 subjects were retrospectively analyzed. The correlation was explored by univariate and multivariate regression analysis. Results: CN2 subtype was associated with shortest median OS (CN2 subtype vs. others: 46.8 vs. 221.7 months, p < 0.05). The time-dependent receiver operating characteristic for the CN2 subtype was 0.80 (95% CI: 0.74–0.85) for survival at 1 year, 0.80 (95% CI: 0.75–0.85) for survival at 2 years, and 0.77 (95% CI: 0.73–0.83) for survival at 3 years. On multivariate analysis, hemorrhage (OR: 0.118; p < 0.001; 95% CI: 0.037–0.376), poorly defined margin (OR: 4.592; p < 0.001; 95% CI: 1.965–10.730), extranodular growth (OR: 0.247; p = 0.006; 95% CI: 0.091–0.671), and volume ≥ 60 cm3 (OR: 4.734.256; p < 0.001; 95% CI: 2.051–10.924) were associated with CN1 subtype (AUC: 0.781). Proportion CE tumor (OR: 5.905; p = 0.007; 95% CI: 1.622–21.493), extranodular growth (OR: 9.047; p = 0.001; 95% CI: 2.349–34.846), width ≥ median (OR: 0.231; p = 0.049; 95% CI: 0.054–0.998), and depth ≥ median (OR: 0.192; p = 0.023; 95% CI: 0.046–0.799) were associated with CN2 subtype (AUC: 0.854). Necrosis/cystic (OR: 6.128; p = 0.007; 95% CI: 1.635–22.968), hemorrhage (OR: 5.752; p = 0.002; 95% CI: 1.953–16.942), poorly defined margin (OR: 0.164; p < 0.001; 95% CI: 0.063–0.427), and volume ≥ median (OR: 4.422; p < 0.001; 95% CI: 1.925–10.160) were associated with CN3 subtype (AUC: 0.808). All three nomograms showed good discrimination and calibration. Decision curve analysis supported that all nomograms were clinically useful. The average accuracy of the tenfold cross-validation was 0.680 (CN1), 0.794 (CN2), and 0.894 (CN3), respectively. Conclusions: The shortest OS was observed in patients with CN2 subtype. This preliminary radiogenomics analysis revealed that the MR-based preoperative nomograms provide individualized prediction of DNA copy number subtype in LGG patients. Key Points: • This preliminary radiogenomics analysis of LGG revealed that the MR-based preoperative nomograms provide individualized prediction of DNA copy number subtype in LGG patients. • The AUC for the ROC curve was 0.781 for CN1 subtype, 0.854 for CN2 subtype, and 0.808 for CN3 subtype. Decision curve analysis supported that all nomograms were clinically useful. • The sensitivity was 0.779 (CN1), 0.731 (CN2), and 0.851 (CN3), respectively. The specificity was 0.664 (CN1), 0.872 (CN2), and 0.625 (CN3), respectively. And the accuracy was 0.717 (CN1), 0.849 (CN2), and 0.692 (CN3), respectively. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the value of CT radiomics in predicting the epidermal growth factor receptor (EGFR) mutation of patients with non-small cell lung cancer (NSCLC), and combing with the clinical characteristic to construct the prediction model. Methods: Sixty-seven cases of NSCLC confirmed by pathology were enrolled. The pre-treatment chest CT enhanced images were used in Radiomics analysis. Two experienced radiologists delineated the region of interest (ROI) on open source software 3D-Slicer. The feature of ROI was extracted by Pyradiomics software package and a total of 849 features were extracted. By calculating Pearson correlation coefficient between pair-wise features and LASSO method for feature screening. The prediction model was constructed by logical regression, diagnostic efficacy of the model by the area under the receiver operating characteristic (ROC) curve was calculated. Results: Based on clinical model and the radiomics model, the AUC under the ROC was 0.8387 and 0.8815, respectively. The model combining clinical and radiomics features perfect best, the AUC under the ROC was 0.9724, the sensitivity and specificity were 85.3 and 90.9%, respectively. Conclusions: Compared with clinical features or radiomics features alone, the model constructed by combining clinical and pre-treatment chest enhanced CT features may show more utility for improved patient stratification in EGFR mutation and EGFR wild. [ABSTRACT FROM AUTHOR]

Objective. The diagnostic value of antinuclear antibodies (ANAs) including anti-gp210 and anti-sp100 for primary biliary cholangitis/cirrhosis (PBC) has been widely reported. However, their diagnostic performances for antimitochondrial antibody- (AMA-) negative PBC were less well elucidated. Therefore, the aim of the current meta-analysis was to evaluate the diagnostic accuracy of ANAs in patients with AMA-negative PBC. Materials and Methods. Literature on the diagnostic value of biomarkers for AMA-negative PBC was systematically searched in PubMed, MEDLINE, EMBASE, and the Cochrane Library. The qualities of the retrieved studies were assessed by the Quality Assessment of Diagnostic Accuracy Studies-version 2 (QUADAS-2) scale. Pooled sensitivity and specificity of the biomarkers were calculated with random-effects models. The areas under the summary receiver operating characteristic (AUSROC) curves were used to evaluate the overall diagnostic performance of ANAs. Results. A total of 11 studies (400 AMA-negative PBC patients and 6217 controls) were finally included in the meta-analysis. ANAs had an overall sensitivity of 27% (95% CI: 20%, 35%) and specificity of 98% (95% CI: 97%, 99%). The pooled sensitivities for anti-gp210 and anti-sp100 were 23% (95% CI: 13%, 37%) and 25% (95% CI: 13%, 43%), respectively, and their specificities were 99% (95% CI: 97%, 100%) and 97% (95% CI: 93%, 98%), respectively. Conclusions. ANAs exhibited high specificity but low sensitivity and therefore could be used as reliable biomarkers to reduce the necessity of liver histology. [ABSTRACT FROM AUTHOR]