Clinical Scoring System to Predict Hepatocellular Carcinoma in Chronic Hepatitis B Carriers

Purpose Hepatitis B virus (HBV) infection is an important etiology for hepatocellular carcinoma (HCC). We aim to develop a simple clinical score in predicting the risk of HCC among HBV carriers. Patients and Methods We first evaluated 1,005 patients and found that the following five factors independently predicted HCC development: age, albumin, bilirubin, HBV DNA, and cirrhosis. These variables were used to construct a prediction score ranging from 0 to 44.5. The score was validated in another prospective cohort of 424 patients. Results During a median follow-up of 10 years, 105 patients (10.%) in the training cohort and 45 patients (10.6%) in the validation cohort developed HCC. Cutoff values of 5 and 20 best discriminated HCC risk. By applying the cutoff value of 5, the score excluded future HCC development with high accuracy (negative predictive value = 97.8% and 97.3% in the training and validation cohorts, respectively). In the validation cohort, the 5-year HCC-free survival rates were 98.3%, 90.5%, and 78.9% in the low-, medium-, and high-risk groups, respectively. The hazard ratios for HCC in the medium- and high-risk groups were 12.8 and 14.6, respectively. Conclusion A simple prediction score constructed from routine clinical and laboratory parameters is accurate in predicting HCC development in HBV carriers. Future prospective validation is warranted.

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Hepatocellular carcinoma (HCC) and hepatic hydatid disease (HHD)

Current Surgical Guidelines ◽

10.1093/med/9780198794769.003.0044 ◽

2018 ◽

pp. 421-430

Author(s):

Abdullah Jibawi ◽

Mohamed Baguneid ◽

Arnab Bhowmick

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Transplantation ◽

Radiofrequency Ablation ◽

High Risk ◽

Hepatitis B ◽

Hydatid Disease ◽

Risk Groups ◽

Hepatic Hydatid Disease ◽

Surgical Options ◽

Hepatic Hydatid

Hepatocellular carcinoma (HCC) is strongly associated with cirrhosis. High-risk groups include those with hepatitis due to hepatitis B (HBV) or C (HCV) virus. This chapter provides an algorithm for investigating liver nodules in order to diagnose hepatocellular carcinoma. It explores surgical options including resection, liver transplantation, and minimally invasive options, such as radiofrequency ablation. Palliative options are described and an algorithm for the treatment of HCC is presented. The chapter also discusses hepatic hydatid disease, caused by the metacestode stages of Echinococcus granulosus and E. multilocularis.

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A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

BMC Cancer ◽

10.1186/s12885-021-07916-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Dongdong Zhou ◽

Xiaoli Liu ◽

Xinhui Wang ◽

Fengna Yan ◽

Peng Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Surgical Therapy ◽

Calibration Curve ◽

Cox Regression ◽

Validation Cohort ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Alpha Fetoprotein ◽

Clinicopathologic Characteristics

Abstract Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

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Risk Factors for Pneumonia and Death in Adult Patients With Seasonal Influenza and Establishment of Prediction Scores: A Population-Based Study

Open Forum Infectious Diseases ◽

10.1093/ofid/ofab068 ◽

2021 ◽

Vol 8 (3) ◽

Author(s):

Koichi Miyashita ◽

Eiji Nakatani ◽

Hironao Hozumi ◽

Yoko Sato ◽

Yoshiki Miyachi ◽

...

Keyword(s):

High Risk ◽

Seasonal Influenza ◽

Prediction Models ◽

Validation Cohort ◽

Risk Groups ◽

Population Based ◽

Limited Data ◽

Population Based Study ◽

Relative Risks ◽

Primary Care Settings

Abstract Background Seasonal influenza remains a global health problem; however, there are limited data on the specific relative risks for pneumonia and death among outpatients considered to be at high risk for influenza complications. This population-based study aimed to develop prediction models for determining the risk of influenza-related pneumonia and death. Methods We included patients diagnosed with laboratory-confirmed influenza between 2016 and 2017 (main cohort, n = 25 659), those diagnosed between 2015 and 2016 (validation cohort 1, n = 16 727), and those diagnosed between 2017 and 2018 (validation cohort 2, n = 34 219). Prediction scores were developed based on the incidence and independent predictors of pneumonia and death identified using multivariate analyses, and patients were categorized into low-, medium-, and high-risk groups based on total scores. Results In the main cohort, age, gender, and certain comorbidities (dementia, congestive heart failure, diabetes, and others) were independent predictors of pneumonia and death. The 28-day pneumonia incidence was 0.5%, 4.1%, and 10.8% in the low-, medium-, and high-risk groups, respectively (c-index, 0.75); the 28-day mortality was 0.05%, 0.7%, and 3.3% in the low-, medium-, and high-risk groups, respectively (c-index, 0.85). In validation cohort 1, c-indices for the models for pneumonia and death were 0.75 and 0.87, respectively. In validation cohort 2, c-indices for the models were 0.74 and 0.87, respectively. Conclusions We successfully developed and validated simple-to-use risk prediction models, which would promptly provide useful information for treatment decisions in primary care settings.

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A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

BioData Mining ◽

10.1186/s13040-021-00261-y ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Qian Yan ◽

Wenjiang Zheng ◽

Boqing Wang ◽

Baoqian Ye ◽

Huiyan Luo ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

High Risk ◽

Risk Score ◽

Immune Cells ◽

Prognostic Model ◽

Risk Groups ◽

Low Risk ◽

Prognostic Performance ◽

Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

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472 HEPATITIS B DURING PREGNANCY: IDENTIFICATION OF HIGH RISK GROUPS

Pediatric Research ◽

10.1203/00006450-198104001-00485 ◽

1981 ◽

Vol 15 ◽

pp. 519-519

Author(s):

Madhu Gudavalli ◽

Catherine M P Kierney ◽

Saul Krugman

Keyword(s):

High Risk ◽

Hepatitis B ◽

Risk Groups

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Edukasi Kesehatan sebagai Upaya Preventif Penyakit Hepatitis B dan C pada Warga Binaan Pemasyarakatan

AKSIOLOGIYA Jurnal Pengabdian Kepada Masyarakat ◽

10.30651/aks.v4i1.2164 ◽

2019 ◽

Vol 4 (1) ◽

pp. 43

Author(s):

Patricia Gita Naully ◽

Perdina Nursidika

Keyword(s):

Hepatitis C ◽

High Risk ◽

Hepatitis B ◽

Health Services ◽

Clinical Symptoms ◽

Descriptive Analysis ◽

Risk Groups ◽

Modes Of Transmission ◽

Lecture Method ◽

The Government

ABSTRAK Hepatitis B dan C dianggap paling berbahaya diantara jenis hepatitis yang lain karena keduanya dapat berkembang menjadi penyakit kronik, sering tanpa gejala, dan menyebabkan kematian. Salah satu upaya yang disarankan oleh WHO untuk mencegah peningkatan angka Hepatitis B dan C adalah melakukan kegiatan edukasi kesehatan bagi masyarakat, khususnya kelompok beresiko tinggi seperi Warga Binaan Pemasyarakatan (WBP). Oleh sebab itu, kegiatan penyuluhan ini bertujuan untuk meningkatkan pengetahuan WBP terkait penyebab, gejala, cara penularan, pencegahan, dan layanan kesehatan yang disediakan oleh pemerintah. Kegiatan ini dilakukan di Lembaga Pemasyarakatan (Lapas) Narkotika Kelas IIA Bandung dengan jumlah peserta sebanyak 30 orang WBP. Penyuluhan dilaksanakan dengan metode ceramah. Evaluasi kegiatan dilakukan dengan cara menganalisis hasil kuesioner dan nilai tes para peserta. Teknik analisis yang digunakan adalah analisis deskriptif. Hasil evaluasi membuktikan bahwa mayoritas WBP melakukan tindakan beresiko tinggi karena keterbatasan pengetahuan dan informasi, namun setelah mendapatkan materi penyuluhan terlihat adanya peningkatan nilai tes pada seluruh peserta. Kegiatan ini berhasil meningkatkan pengetahuan WBP di Lapas Narkotika Kelas IIA Bandung terkait penyebab, gejala klinis, cara penularan, pencegahan, serta beberapa layanan kesehatan pemerintah untuk mencegah, mendiagnosa, serta mengobati penyakit Hepatitis B dan C.Kata Kunci: hepatitis B; hepatitis C; penyuluhan; lembaga pemasyarakatanABSTRACTHepatitis B and C are considered as the most dangerous hepatitis types compared to the other, because both can develop into chronic diseases, asymptomatic, and cause death. One of the methods suggested by WHO to prevent an increase of Hepatitis B and C numbers is to conduct health education activities for the community, especially for the high-risk groups such as prisoners (WBP). Therefore, the aim of this extension activity was to upgrade the WBP's knowledge regarding the disease causes, symptoms, transmission methods, prevention, and health services provided by the government. This activity was conducted in Bandung Narcotics Penitentiary class IIA, with 30 WBP participants. The extention was done by the lecture method. Then, the activity evaluation was done by analyzing of questionnaire results and participants' test-scores. Besides, the analysis technique used was descriptive analysis. The evaluation result proved that the majority of WBP taking the high-risk action due to the limited of knowledge and information, but there was a test-score increase for all participants after obtaining counseling materials. This activity was successful to improve the WBP's knowledge in Bandung Narcotics Penitentiary class IIA related to the causes, clinical symptoms, modes of transmission, prevention, and also some government health services to prevent, diagnose, and treat the Hepatitis B and C.Keywords : extension; hepatitis B; hepatitis C; prison.

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The Prevalence of Hepatitis B Surface Antigen and Its Antibody in Blood Donors and High Risk Groups in Iran

Vox Sanguinis ◽

10.1159/000466907 ◽

1979 ◽

Vol 37 (3) ◽

pp. 182-186

Author(s):

H. Farzadegan ◽

C. Harbour ◽

F. Ala

Keyword(s):

High Risk ◽

Hepatitis B ◽

Surface Antigen ◽

Blood Donors ◽

Hepatitis B Surface Antigen ◽

Risk Groups

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A Novel Online Calculator Based on Serum Biomarkers to Detect Hepatocellular Carcinoma among Patients with Hepatitis B

Clinical Chemistry ◽

10.1373/clinchem.2019.308965 ◽

2019 ◽

Vol 65 (12) ◽

pp. 1543-1553 ◽

Cited By ~ 3

Author(s):

Tian Yang ◽

Hao Xing ◽

Guoqiang Wang ◽

Nianyue Wang ◽

Miaoxia Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Hepatitis B ◽

Validation Cohort ◽

Area Under The Curve ◽

Serum Biomarkers ◽

Web Based ◽

Training Cohort ◽

B Virus ◽

Online Calculator ◽

Diagnostic Sensitivity And Specificity

Abstract BACKGROUND Early detection of hepatocellular carcinoma (HCC) among hepatitis B virus (HBV)-infected patients remains a challenge, especially in China. We sought to create an online calculator of serum biomarkers to detect HCC among patients with chronic hepatitis B (CHB). METHODS Participants with HBV-HCC, CHB, HBV-related liver cirrhosis (HBV-LC), benign hepatic tumors, and healthy controls (HCs) were recruited at 11 Chinese hospitals. Potential serum HCC biomarkers, protein induced by vitamin K absence or antagonist-II (PIVKA-II), α-fetoprotein (AFP), lens culinaris agglutinin A-reactive fraction of AFP (AFP-L3) and α-L-fucosidase (AFU) were evaluated in the pilot cohort. The calculator was built in the training cohort via logistic regression model and validated in the validation cohort. RESULTS In the pilot study, PIVKA-II and AFP showed better diagnostic sensitivity and specificity compared with AFP-L3 and AFU and were chosen for further study. A combination of PIVKA-II and AFP demonstrated better diagnostic accuracy in differentiating patients with HBV-HCC from patients with CHB or HBV-LC than AFP or PIVKA-II alone [area under the curve (AUC), 0.922 (95% CI, 0.908–0.935), sensitivity 88.3% and specificity 85.1% for the training cohort; 0.902 (95% CI, 0.875–0.929), 87.8%, and 81.0%, respectively, for the validation cohort]. The nomogram including AFP, PIVKA-II, age, and sex performed well in predicting HBV-HCC with good calibration and discrimination [AUC, 0.941 (95% CI, 0.929–0.952)] and was validated in the validation cohort [AUC, 0.931 (95% CI, 0.909–0.953)]. CONCLUSIONS Our results demonstrated that a web-based calculator including age, sex, AFP, and PIVKA-II accurately predicted the presence of HCC in patients with CHB. ClinicalTrials.gov Identifier NCT03047603

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Validation of a Novel Tissue Array Based Classification of Multiple Myeloma (MM).

Blood ◽

10.1182/blood.v112.11.1671.1671 ◽

2008 ◽

Vol 112 (11) ◽

pp. 1671-1671

Author(s):

Nizar J Bahlis ◽

Alex Klimowicz ◽

Paola Neri ◽

Anthony Magliocco ◽

Douglas A. Stewart ◽

...

Keyword(s):

High Risk ◽

Validation Cohort ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Protein Array ◽

Immunoperoxidase Staining ◽

Initial Testing ◽

Independent Validation

Abstract Background: Gene expression profiling molecular classification of MM was proven to be an independent predictor of survival post autologous stem cell transplant (ASCT); however it had limited clinical applicability due to its complex methodology and high costs. We have previously reported the results of a protein-array based classification of MM in an initial testing cohort and concluded that positive immunoperoxidase staining for FGFR3, Cyclin B2 or Integrin beta7 correlates with a shortened survival post ASCT (Bahlis et al. Blood2007:110:449a). We now report on the results of this TMA classification in a larger and independent validation cohort. Methods: Immunoperoxidase staining for Cyclins B1, B2, D1, D2 and D3, FGFR3, PAX5 and Integrin beta 7 were previously validated in our initial testing cohort (n=52). Further analysis of our initial testing cohort identified 3 risk groups: positive expression of FGFR3 or Integrin beta 7 defined as “High risk”, positive Cyclin B2 (in the absence of FGFR3 or Integrin beta 7) as “Intermediate risk” and the lack of expression of any of these biomarkers defined as “Low risk”. In order to confirm the predictive value of our proposed protein-array classification, these immunohistochemical (IHC) stains were performed on the bone marrow biopsies of a larger and independent validation cohort of 79 newly diagnosed MM patients uniformly treated with a dexamethasone based regimen followed by ASCT. The clinical parameters, response criteria and survival outcomes (TTP and OS) of this validation cohort were defined according to the international uniform response criteria. For IHC analysis two pathologists who were blinded with regards to the clinical outcome of these patients scored the cases independently as positive or negative. Discordance in their scoring was seen in 20/79 (25.7%) with a consensus scoring reassigned to all of these cases. The Kaplan-Meier method was used to estimate OS and TTP. Multivariate analysis was performed using the Cox regression method. Figure Figure Results: 79 patients were included in this validation cohort, the median age was 54.4 yrs (27.9–71), 23.7% had ISS stage III, median beta 2-microglobulin was 3.29 mg/L (1.16–37.5). Del13q and t(4;14) were detected by FISH in 35.6% and 13.6% of patients, respectively. Post ASCT, 68% achieved a CR or VGPR with an overall median TTP and OS of 2.29 years (CI 1.84–2.73) and 5.74 years (CI 4.98–6.51) respectively. Expression of FGFR3 was detected in 7.6% of the patients, cyclin B2 in 58.2% and integrin-beta7 in 17.7%. In univariate analysis expression of FGFR3 was associated with a significantly shorter TTP (P=0.011) but not OS (P=0.114). Similarly integrin-beta7 predicted for a shorter TTP (P=0.008) but not OS (P=0.570). Cyclin B2 also predicted for worse TTP (P=0.047) but not OS (P=0.098), whereas the expression of cyclins D1, D2, D3 and PAX5 did not affect survival. Based on our testing cohort definition of risk groups, 18/79 (22.8%) were considered as “High risk” with significantly shorter TTP 0.93 years (CI 0.74–1.12) compared to 2.29 years (CI 1.88–2.69) and 3.35 years (CI 2.51–4.19) for the “Intermediate” (34/79; 43%) and “Low” (27/79; 34.2%) risk groups respectively (P=0.002). The 5-years estimates for OS was 57.1% for the High-risk group compared to 66.3% and 71.6% for the Intermediate and Low risk group respectively (P=0.258). Multivariate analysis was performed using ISS, del13q and the TMA risk group classification as variables. The TMA classification and del 13q were the only independent predictors of TTP with the high-risk group having 3.4 fold greater risk of relapse (P=0.001). Conclusion: We have validated our protein array based classification of Multiple Myeloma and confirmed its survival predictive value post ASCT. MM patients with the High-risk signature should be spared the toxicity of ASCT and considered instead for other frontline novel therapeutic agents.

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