Prediction of survival and analysis of prognostic factors for patients with AFP negative hepatocellular carcinoma: a population-based study.

PURPOSE: Hepatocellular carcinoma (HCC) has a poor prognosis, and alpha-fetoprotein (AFP) is widely used to evaluate HCC. However, the proportion of AFP-negative individuals cannot be disregarded. This study aimed to establish a nomogram of risk factors affecting the prognosis of patients with AFP-negative HCC and to evaluate its diagnostic efficiency. PATIENTS AND METHODS: Data from patients with AFP-negative initial diagnosis of HCC (ANHC) between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and validation. We randomly divided overall cohort into the training or validation cohort (7:3). Univariate and multivariate Cox regression analysis were used to identify the risk factors. We constructed nomograms with overall survival (OS) and cancer-specific survival (CSS) as clinical endpoint events and constructed survival analysis by using Kaplan-Meier curve. Also, we conducted internal validation with Receiver Operating Characteristic (ROC) analysis and Decision curve analysis (DCA) to validate the clinical value of the model. RESULTS: This study included 1811 patients (1409 men; 64.7% were Caucasian; the average age was 64 years; 60.7% were married). In the multivariate analysis, the independent risk factors affecting prognosis were age, ethnicity, year of diagnosis, tumor size, tumor grade, surgery, chemotherapy, and radiotherapy. The nomogram-based model related C-indexes were 0.762 (95% confidence interval (CI): 0.752-0.772) and 0.752 (95% CI: 0.740-0.769) for predicting OS, and 0.785 (95% CI: 0.774-0.795) and 0.779 (95% CI: 0.762-0.795) for predicting CSS. The nomogram model showed that the predicted death was consistent with the actual value. The ROC analysis and DCA showed that the nomogram had good clinical value compared with TNM staging. CONCLUSION: The age(HR:1.012, 95% CI: 1.006-1.018, P-value < 0.001), ethnicity(African-American: HR:0.946, 95% CI: 0.783-1.212, P-value: 0.66; Others: HR:0.737, 95% CI: 0.613-0.887, P-value: 0.001), tumor diameter(HR:1.006, 95% CI: 1.004-1.008, P-value < 0.001), year of diagnosis (HR:0.852, 95% CI: 0.729-0.997, P-value: 0.046), tumor grade(Grade 2: HR:1.124, 95% CI: 0.953-1.326, P-value: 0.164; Grade 3: HR:1.984, 95% CI: 1.574-2.501, P-value < 0.001; Grade 4: HR:2.119, 95% CI: 1.115-4.027, P-value: 0.022), surgery(Liver Resection: HR:0.193, 95% CI: 0.160-0.234, P-value < 0.001; Liver Transplant: HR:0.102, 95% CI: 0.072-0.145, P-value < 0.001), chemotherapy(HR:0.561, 95% CI: 0.471-0.668, P-value < 0.001), and radiotherapy(HR:0.641, 95% CI: 0.463-0.887, P-value:0.007) were independent prognostic factors for patients with ANHC. We developed a nomogram model for predicting the OS and CSS of patients with ANHC, with a good predictive performance.

An Improved RAIM Availability Assessment Method Based on the Characteristic Slope.

The availability assessment is an important step for onboard application in Receiver Autonomous Integrity Monitoring (RAIM)s. It is commonly implemented using the protection level (PL)-based method. This paper analyzes the deficiencies of three kinds of PL-based methods: RAIM availability might be optimistically or conservatively assessed using the classic-PL-base method; might be conservatively assessed using the enhanced-PL-based method, and neither be optimistically nor conservatively assessed using the ideal-PL-based method with the cost of large calculation amount on-board. An improved slope-based RAIM availability assessment method is proposed, in which the characteristic slope is designed as the assessment basis, and its threshold that can exactly match the integrity risk requirement is derived. The slope-based method has the same RAIM availability assessment result as the ideal-PL-based method. Moreover, because the slope threshold can be calculated offline and searched online, the on-board calculation burden can be reduced using the slope-based method. Simulation is presented to verify the theoretical analysis of the RAIM availability assessment performances for the three PL-based and the slope-based methods.

A CT Radiomics-Based Risk Score for Preoperative Estimation of Intraoperative Superior Mesenteric-Portal Vein Involvement in Pancreatic Ductal Adenocarcinoma.

BACKGROUND: The current radiologic criteria for assessing intraoperative superior mesenteric-portal vein (SMPV) involvement (i.e., presence of tumor-SMPV contact >180° or venous deformity) in pancreatic ductal adenocarcinoma (PDAC) are highly specific but insufficiently sensitive. Therefore, development of improved markers for a more accurate prediction is essential. This study aimed to develop a risk score model to estimate SMPV involvement in PDAC using radiomics analysis of computed tomography (CT) images. METHODS: Data from two institution-based cohorts of PDAC patients undergoing preoperative CT scans were used to develop (n = 173) and validate (n = 156) a radiomics-based risk score of SMPV involvement using clinical and imaging variables. A radiomics signature was developed based on 2436 radiomic features extracted from the semi-automatic three-dimensional segmentation ofn CT images. The SMPV involvement risk score was built using multivariate logistic regression and compared with the current radiologic criteria. RESULTS: The study surgically identified SMPV involvement in 59 (34.1%) and 57(36.5 %) patients with PDAC in the development and validation cohorts, respectively. A 12-feature-based radiomics signature achieved areas under receiver operating characteristics curves (AUCs) of 0.89 or greater for estimating SMPV involvement. Multivariate regression identified the radiomics signature and SMPV deformity as associated with SMPV involvement. The risk score model had significantly improved AUC (0.928 vs. 0.768; P < 0.001) and sensitivity (84.2% vs. 66.7%; P = 0.025) in the radiologic evaluation. CONCLUSIONS: The novel risk score in this study, combining radiomics signature and venous deformity, demonstrated promising performance for estimating SMPV involvement preoperatively for patients with PDAC.

Nomogram Estimating Vessels Encapsulating Tumor Clusters in Hepatocellular Carcinoma From Preoperative Gadoxetate Disodium-Enhanced MRI.

BACKGROUND: Vessels encapsulating tumor clusters (VETC) pattern is a novel microvascular pattern associated with poor outcomes of hepatocellular carcinoma (HCC). Preoperative estimation of VETC has potential to improve treatment decisions. PURPOSE: To develop and validate a nomogram based on gadoxetate disodium-enhanced MRI for estimating VETC in HCC and to evaluate whether the estimations are associated with recurrence after hepatic resection. STUDY TYPE: Retrospective. POPULATION: A total of 320 patients with HCC and histopathologic VETC pattern assessment from three centers (development cohort:validation cohort = 173:147). FIELD STRENGTH/SEQUENCE: A3.0  T/turbo spin-echo T2-weighted, spin-echo echo-planar diffusion-weighted, and 3D T1-weighted gradient-echo sequences. ASSESSMENT: A set of previously reported VETC- and/or prognosis-correlated qualitative and quantitative imaging features were assessed. Clinical and imaging variables were compared based on histopathologic VETC status to investigate factors indicating VETC pattern. A regression-based nomogram was then constructed using the significant factors for VETC pattern. The nomogram-estimated VETC stratification was assessed for its association with recurrence. STATISTICAL TESTS: Fisher exact test, t-test or Mann-Whitney test, logistic regression analyses, Harrell's concordance index (C-index), nomogram, Kaplan-Meier curves and log-rank tests. P value < 0.05 was considered statistically significant. RESULTS: Pathological VETC pattern presence was identified in 156 patients (development cohort:validation cohort = 83:73). Tumor size, presence of heterogeneous enhancement with septations or with irregular ring-like structures, and necrosis were significant factors for estimating VETC pattern. The nomogram incorporating these indicators showed good discrimination with a C-index of 0.870 (development cohort) and 0.862 (validation cohort). Significant differences in recurrence rates between the nomogram-estimated high-risk VETC group and low-risk VETC group were found (2-year recurrence rates, 50.7% vs. 30.3% and 49.6% vs. 31.8% in the development and validation cohorts, respectively). DATA CONCLUSION: The nomogram integrating gadoxetate disodium-enhanced MRI features was associated with VETC pattern preoperatively and with postoperative recurrence in patients with HCC. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Development and validation of a machine learning-based model for varices screening in compensated cirrhosis (CHESS2001): an international multicenter study.

BACKGROUND AND AIMS: The prevalence of high-risk varices (HRV) is low among compensated cirrhotic patients undergoing EGD. Our study aimed to identify a novel machine learning (ML)-based model, named ML EGD, for ruling out HRV and avoiding unnecessary EGDs in patients with compensated cirrhosis. METHODS: An international cohort from 17 institutions from China, Singapore, and India were enrolled (CHESS2001). The variables with the top 3 importance scores (liver stiffness, platelet count, and total bilirubin) were selected by the Shapley additive explanation and input into a light gradient-boosting machine algorithm to develop ML EGD for identification of HRV. Furthermore, we built a web-based calculator for ML EGD, which is free with open access (http://www.pan-chess.cn/calculator/MLEGD_score). Unnecessary EGDs that were not performed and the rates of missed HRV were used to assess the efficacy and safety for varices screening. RESULTS: Of 2794 enrolled patients, 1283 patients formed a real-world cohort from 1 university hospital in China used to develop and internally validate the performance of ML EGD for varices screening. They were randomly assigned into the training (n = 1154) and validation (n = 129) cohorts with a ratio of 9:1. In the training cohort, ML EGD spared 607 (52.6%) unnecessary EGDs with a missed HRV rate of 3.6%. In the validation cohort, ML EGD spared 75 (58.1%) EGDs with a missed HRV rate of 1.4%. To externally test the performance of ML EGD, 966 patients from 14 university hospitals in China (test cohort 1) and 545 from 2 hospitals in Singapore and India (test cohort 2) comprised the 2 test cohorts. In test cohort 1, ML EGD spared 506 (52.4%) EGDs with a missed HRV rate of 2.8%. In test cohort 2, ML EGD spared 224 (41.1%) EGDs with a missed HRV rate of 3.1%. When compared with the Baveno VI criteria, ML EGD spared more screening EGDs in all cohorts (training cohort, 52.6% vs 29.4%; validation cohort, 58.1% vs 44.2%; test cohort 1, 52.4% vs 26.5%; test cohort 2, 41.1% vs 21.1%, respectively; P < .001). CONCLUSIONS: We identified a novel model based on liver stiffness, platelet count, and total bilirubin, named ML EGD, as a free web-based calculator. ML EGD could efficiently help rule out HRV and avoid unnecessary EGDs in patients with compensated cirrhosis. (Clinical trial registration number: NCT04307264.).

Safety and Immunogenicity of SARS-CoV-2 Vaccines in Patients With Chronic Liver Diseases (CHESS-NMCID 2101): A Multicenter Study.

BACKGROUND & AIMS: We aimed to assess the safety and immunogenicity of inactivated whole-virion severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in patients with chronic liver diseases (CLD) in this study. METHODS: This was a prospective, multi-center, open-label study. Participants aged over 18 years with confirmed CLD and healthy volunteers were enrolled. All participants received 2 doses of inactivated whole-virion SARS-CoV-2 vaccines. Adverse reactions were recorded within 14 days after any dose of SARS-CoV-2 vaccine, laboratory testing results were collected after the second dose, and serum samples of enrolled subjects were collected and tested for SARS-CoV-2 neutralizing antibodies at least 14 days after the second dose. RESULTS: A total of 581 participants (437 patients with CLD and 144 healthy volunteers) were enrolled from 15 sites in China. Most adverse reactions were mild and transient, and injection site pain (n = 36; 8.2%) was the most frequently reported adverse event. Three participants had grade 3 aminopherase elevation (defined as alanine aminopherase >5 upper limits of normal) after the second dose of inactivated whole-virion SARS-CoV-2 vaccination, and only 1 of them was judged as severe adverse event potentially related to SARS-CoV-2 vaccination. The positive rates of SARS-CoV-2 neutralizing antibodies were 76.8% in the noncirrhotic CLD group, 78.9% in the compensated cirrhotic group, 76.7% in the decompensated cirrhotic group (P = .894 among CLD subgroups), and 90.3% in healthy controls (P = .008 vs CLD group). CONCLUSION: Inactivated whole-virion SARS-CoV-2 vaccines are safe in patients with CLD. Patients with CLD had lower immunologic response to SARS-CoV-2 vaccines than healthy population. The immunogenicity is similarly low in noncirrhotic CLD, compensated cirrhosis, and decompensated cirrhosis.

Safety and immunogenicity of COVID-19 vaccination in patients with hepatocellular carcinoma (CHESS-NMCID 2101): A multicenter prospective study.

Data on safety and immunogenicity of coronavirus disease 2019 (COVID-19) vaccinations in hepatocellular carcinoma (HCC) patients are limited. In this multicenter prospective study, HCC patients received two doses of inactivated whole-virion COVID-19 vaccines. The safety and neutralizing antibody were monitored. Totally, 74 patients were enrolled from 10 centers in China, and 37 (50.0%), 25 (33.8%), and 12 (16.2%) received the CoronaVac, BBIBP-CorV, and WIBP-CorV, respectively. The vaccines were well tolerated, where pain at the injection site (6.8% [5/74]) and anorexia (2.7% [2/74]) were the most frequent local and systemic adverse events. The median level of neutralizing antibody was 13.5 (interquartile range [IQR]: 6.9-23.2) AU/ml at 45 (IQR: 19-72) days after the second dose of vaccinations, and 60.8% (45/74) of patients had positive neutralizing antibody. Additionally, lower γ-glutamyl transpeptidase level was related to positive neutralizing antibody (odds ratio = 1.022 [1.003-1.049], p = 0.049). In conclusion, this study found that inactivated COVID-19 vaccinations are safe and the immunogenicity is acceptable or hyporesponsive in patients with HCC. Given that the potential benefits may outweigh the risks and the continuing emergences of novel severe acute respiratory syndrome coronavirus 2 variants, we suggest HCC patients to be vaccinated against COVID-19. Future validation studies are warranted.

Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics.

BACKGROUND: Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies. METHODS: Patients with a single HCC of 2-5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation. RESULTS: The CRR model showed higher area under the curve values (0.835-0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796-0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31). CONCLUSIONS: The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.

Safety and immunogenicity of COVID-19 vaccination in patients with non-alcoholic fatty liver disease (CHESS2101): A multicenter study.

BACKGROUND & AIMS: The development of COVID-19 vaccines has progressed with encouraging safety and efficacy data. Concerns have been raised about SARS-CoV-2 vaccine responses in the large population of patients with non-alcoholic fatty liver disease (NAFLD). The study aimed to explore the safety and immunogenicity of COVID-19 vaccination in NAFLD. METHODS: This multicenter study included patients with NAFLD without a history of SARS-CoV-2 infection. All patients were vaccinated with 2 doses of inactivated vaccine against SARS-CoV-2. The primary safety outcome was the incidence of adverse reactions within 7 days after each injection and overall incidence of adverse reactions within 28 days, and the primary immunogenicity outcome was neutralizing antibody response at least 14 days after the whole-course vaccination. RESULTS: A total of 381 patients with pre-existing NAFLD were included from 11 designated centers in China. The median age was 39.0 years (IQR 33.0-48.0 years) and 179 (47.0%) were male. The median BMI was 26.1 kg/m2 (IQR 23.8-28.1 kg/m2). The number of adverse reactions within 7 days after each injection and adverse reactions within 28 days totaled 95 (24.9%) and 112 (29.4%), respectively. The most common adverse reactions were injection site pain in 70 (18.4%), followed by muscle pain in 21 (5.5%), and headache in 20 (5.2%). All adverse reactions were mild and self-limiting, and no grade 3 adverse reactions were recorded. Notably, neutralizing antibodies against SARS-CoV-2 were detected in 364 (95.5%) patients with NAFLD. The median neutralizing antibody titer was 32 (IQR 8-64), and the neutralizing antibody titers were maintained. CONCLUSIONS: The inactivated COVID-19 vaccine appears to be safe with good immunogenicity in patients with NAFLD. LAY SUMMARY: The development of vaccines against coronavirus disease 2019 (COVID-19) has progressed rapidly, with encouraging safety and efficacy data. This study now shows that the inactivated COVID-19 vaccine appears to be safe with good immunogenicity in the large population of patients with non-alcoholic fatty liver disease.

Prevalence and genotype distribution of group A rotavirus circulating in Shanxi Province, China during 2015-2019.

BACKGROUND: Group A rotavirus (RVA), despite being a leading cause of gastroenteritis in infants and young children, is less studied in Shanxi Province, China. The current study was conducted to determine the prevalence and genetic characterization of RVA in hospitalized children younger than 10 years of age with the diagnosis of acute gastroenteritis in Shanxi Province, China. METHODS: A hospital-based active surveillance of rotavirus gastroenteritis was conducted at Children's Hospital of Shanxi from Jan 1, 2015, through Dec 31, 2019. Rotavirus was detected in stool samples by real-time quantitative reverse transcription PCR (qRT-PCR). G- and P-genotypes were determined by reverse transcription PCR (RT-PCR) and nucleotide sequencing. RESULTS: A total of 961 children younger than 10 years of age was enrolled over the study period, of whom 183 (19.0%) were positive for RVA. The highest RVA-infection frequency (23.7%) was found among children aged 12-23 months, and the seasonal peak was in December. G9P[8] was most prevalent (76.0%), followed by G3P[8] (7.1%), G2P[4] (3.3%), G1P[8] (0.5%) and G9P[4] (0.5%). CONCLUSIONS: These results report for the first time that RVA was one of the main causes of severe infectious gastroenteritis in children, and a high proportion of G9P[8] strains circulating in most areas of Shanxi Province. While the protective efficacy of the rotavirus vaccines has been demonstrated against G9P[8] strains, our results highlight that the dominant strains have not been effectively controlled in China.

Development and validation of a radiomics signature as a non-invasive complementary predictor of gastroesophageal varices and high-risk varices in compensated advanced chronic liver disease: A multicenter study.

BACKGROUND AND AIM: Gastroesophageal varices (GEV) present in compensated advanced chronic liver disease (cACLD) and can develop into high-risk varices (HRV). The gold standard for diagnosing GEV is esophagogastroduodenoscopy (EGD). However, EGD is invasive and less tolerant. This study aimed to develop and validate radiomics signatures based on noncontrast-enhanced computed tomography (CT) images for non-invasive diagnosis of GEV and HRV in patients with cACLD. METHODS: The multicenter trial enrolled 161 patients with cACLD from six university hospitals in China between January 2015 and September 2019, who underwent both EGD and noncontrast-enhanced CT examination within 14 days prior to the endoscopy. Two radiomics signatures, termed rGEV and rHRV, respectively, were built based on CT images in a training cohort of 129 patients and validated in a prospective validation cohort of 32 patients (ClinicalTrials. gov identifier: NCT03749954). RESULTS: In the training cohort, both rGEV and rHRV exhibited high discriminative abilities on determining the existence of GEV and HRV with the area under receiver operating characteristic curve (AUC) of 0.941 (95% confidence interval [CI] 0.904-0.978) and 0.836 (95% CI 0.766-0.905), respectively. In validation cohort, rGEV and rHRV showed high discriminative abilities with AUCs of 0.871 (95% CI 0.739-1.000) and 0.831 (95% CI 0.685-0.978), respectively. CONCLUSIONS: This study demonstrated that rGEV and rHRV could serve as the satisfying auxiliary parameters for detection of GEV and HRV with good diagnostic performance.

Deep Convolutional Neural Network-Aided Detection of Portal Hypertension in Patients With Cirrhosis.

BACKGROUND & AIMS: Noninvasive and accurate methods are needed to identify patients with clinically significant portal hypertension (CSPH). We investigated the ability of deep convolutional neural network (CNN) analysis of computed tomography (CT) or magnetic resonance (MR) to identify patients with CSPH. METHODS: We collected liver and spleen images from patients who underwent contrast-enhanced CT or MR analysis within 14 days of transjugular catheterization for hepatic venous pressure gradient measurement. The CT cohort comprised participants with cirrhosis in the CHESS1701 study, performed at 4 university hospitals in China from August 2016 through September 2017. The MR cohort comprised participants with cirrhosis in the CHESS1802 study, performed at 8 university hospitals in China and 1 in Turkey from December 2018 through April 2019. Patients with CSPH were identified as those with a hepatic venous pressure gradient of 10 mm Hg or higher. In total, we analyzed 10,014 liver images and 899 spleen images collected from 679 participants who underwent CT analysis, and 45,554 liver and spleen images from 271 participants who underwent MR analysis. For each cohort, participants were shuffled and then sampled randomly and equiprobably for 6 times into training, validation, and test data sets (ratio, 3:1:1). Therefore, a total of 6 deep CNN models for each cohort were developed for identification of CSPH. RESULTS: The CT-based CNN analysis identified patients with CSPH with an area under the receiver operating characteristic curve (AUC) value of 0.998 in the training set (95% CI, 0.996-1.000), an AUC of 0.912 in the validation set (95% CI, 0.854-0.971), and an AUC of 0.933 (95% CI, 0.883-0.984) in the test data sets. The MR-based CNN analysis identified patients with CSPH with an AUC of 1.000 in the training set (95% CI, 0.999-1.000), an AUC of 0.924 in the validation set (95% CI, 0.833-1.000), and an AUC of 0.940 in the test data set (95% CI, 0.880-0.999). When the model development procedures were repeated 6 times, AUC values for all CNN analyses were 0.888 or greater, with no significant differences between rounds (P > .05). CONCLUSIONS: We developed a deep CNN to analyze CT or MR images of liver and spleen from patients with cirrhosis that identifies patients with CSPH with an AUC value of 0.9. This provides a noninvasive and rapid method for detection of CSPH (ClincialTrials.gov numbers: NCT03138915 and NCT03766880).

Identification of genes and pathways potentially related to PHF20 by gene expression profile analysis of glioblastoma U87 cell line.

BACKGROUND: Glioblastoma is the most common and aggressive brain tumor associated with a poor prognosis. Plant homeodomain finger protein 20 (PHF20) is highly expressed in primary human gliomas and its expression is associated with tumor grade. However, the molecular mechanism by which PHF20 regulates glioblastoma remains poorly understood. METHODS: Genome wide gene expression analysis was performed to identify differentially expressed genes (DEGs) in U87 cells with PHF20 gene knockdown. Gene ontology (GO) and pathway enrichment analyses were performed to investigate the functions and pathways of DEGs. Pathway-net and signal-net analyses were conducted to identify the key genes and pathways related to PHF20. RESULTS: Expression of 540 genes, including FEN1 and CCL3, were significantly altered upon PHF20 gene silencing. GO analysis results showed that DEGs were significantly enriched in small molecule metabolic and apoptotic processes. Pathway analysis indicated that DEGs were mainly involved in cancer and metabolic pathways. The MAPK, apoptosis and p53 signaling pathways were identified as the hub pathways in the pathway network, while PLCB1, NRAS and PIK3 s were hub genes in the signaling network. CONCLUSIONS: Our findings indicated that PHF20 is a pivotal upstream regulator. It affects the occurrence and development of glioma by regulating a series of tumor-related genes, such as FEN1, CCL3, PLCB1, NRAS and PIK3s, and activation of apoptosis signaling pathways. Therefore, PHF20 might be a novel biomarker for early diagnosis, and a potential target for glioblastoma therapies.