scholarly journals HBV-DNA Load-Related Peritumoral Inflammation and ALBI Scores Predict HBV Associated Hepatocellular Carcinoma Prognosis after Curative Resection

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Rui Liao ◽  
Cheng-You Du ◽  
Jian-Ping Gong ◽  
Fang Luo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Function ◽  
Curative Resection ◽  
Predictive Accuracy ◽  
Hepatitis Virus ◽  
External Validation ◽  
Hbv Dna ◽  
Discriminative Ability ◽  
Staging Systems ◽  
Bclc Staging

Background. Both persistent inflammatory activity and liver function damage contribute to a poor prognosis of hepatocellular carcinoma (HCC). This study aimed to develop nomograms that incorporate hepatitis virus B (HBV)-related peritumoral inflammation score (PIS) and liver function based on ALBI score to predict postoperative outcomes of HCC.Methods.The prognostic roles of HBV-related preoperative PIS and ALBI scores in HCC recurrence were examined, and then two nomograms were constructed. The predictive accuracy and discriminative ability of the nomograms were compared with AJCC and BCLC staging systems of HCC.Results.PIS (HBV-PIS) and ALBI scores (HBV-ALBI) with different HBV-DNA loads had association with overall survival (OS) and/or recurrence-free survival (RFS) of HCC. The independent predictors of OS and RFS were incorporated into the corresponding nomograms. In the training cohort, the C-indexes of OS and RFS nomograms were 0.751 and 0.736, respectively. ROC analyses showed that both OS and RFS nomograms had larger AUC (0.775 and 0.739, respectively) than AJCC and BCLC staging systems. These results were verified by the internal and external validation cohorts.Conclusion. The proposed nomograms, including HBV-DNA load-related PIS and ALBI scores, were accurate in predicting survival for HCC after curative resection.

scholarly journals A Novel Nomogram to Predict Prolonged Survival After Hepatectomy in Repeat Recurrent Hepatocellular Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Qiongxuan Fang ◽  
Ruifeng Yang ◽  
Dongbo Chen ◽  
Ran Fei ◽  
Pu Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
External Validation ◽  
Repeat Hepatectomy ◽  
Discriminative Ability ◽  
Training Cohort ◽  
Recurrent Hepatocellular Carcinoma ◽  
Kaplan Meier ◽  
Staging Systems ◽  
Better Than

Background: Repeat hepatectomy is an important treatment for patients with repeat recurrent hepatocellular carcinoma (HCC).Methods: This study was a multicenter retrospective analysis of 1,135 patients who underwent primary curative liver resection for HCC. One hundred recurrent patients with second hepatectomy were included to develop a nomogram to predict the risk of post-recurrence survival (PRS). Thirty-eight patients in another institution were used to externally validate the nomogram. Univariate and multivariate Cox regression analyses were used to identify independent risk factors of PRS. Discrimination, calibration, and the Kaplan–Meier curves were used to evaluate the model performance.Results: The nomogram was based on variables associated with PRS after HCC recurrence, including the tumor, node, and metastasis (TNM) stage; albumin and aspartate aminotransferase levels at recurrence; tumor size, site, differentiation of recurrences; and time to recurrence (TTR). The discriminative ability of the nomogram, as indicated by the C statistics (0.758 and 0.811 for training cohort and external validation cohorts, respectively), was shown, which was better than that of the TNM staging system (0.609 and 0.609, respectively). The calibration curves showed ideal agreement between the prediction and the real observations. The area under the curves (AUCs) of the training cohort and external validation cohorts were 0.843 and 0.890, respectively. The Kaplan–Meier curve of the established nomogram also performed better than those of both the TNM and the BCLC staging systems.Conclusions: We constructed a nomogram to predict PRS in patients with repeat hepatectomy (RH) after repeat recurrence of HCC.

scholarly journals Development of an ALBI and ascites based model to predict survival for BCLC Stage B hepatocellular carcinoma

2020 ◽  
Author(s):  
Huapeng Lin ◽  
Zheng Jin ◽  
Jing Yang ◽  
Wei Hu ◽  
Ying Zhu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Function ◽  
Predictive Model ◽  
Present Model ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
External Validation ◽  
Tumor Burden ◽  
Prognostic Models ◽  
Cox Regression Analysis

Abstract Background: The outcome of the patients with BCLC stage B hepatocellular carcinoma (HCC) varied. Albumin-Bilirubin (ALBI) grade, as a surrogate of the Child-Pugh (CP) grade, was evaluated to be a simple tool for the assessing of the liver function and prognosis. However, it appears to be arbitrary and crude to eliminate the ascites variable from the ALBI grade. We aimed to develop a predictive model constituted with the ALBI grade, the ascites and tumor burden related parameters in patients with BCLC stage B HCC. Methods: Patients diagnosed as the BCLC stage B HCC were collected from a retrospective database. Construction and validation of the predictive model were performed based on multivariate Cox regression analysis. Predictive accuracy, discrimination and fitness performance of the model were compared with the other eight models. The decision curve analysis (DCA) was used to evaluate the clinical utility.Results: A total of 1773 patients diagnosed as BCLC stage B HCC between 2007 to 2016 were included in the present study. As the methods for the assessing of the liver function, the ALBI grade and ascites showed their independent prognostic value, and then the two parameters were combined into one, the ALBI-AS grade. Subsequently, the ALBI-AS grade (hazard ratio (HR)=1.26, p=0.008) along with two tumor burden related parameters (the AFP level and the 8-and-14 grade, p＜0.001) were used for the development of a prognostic prediction model after multivariate analysis. The area under the receiver operator characteristic curve (AUROC) for overall survival at 1, 2 and 3 years predicted by the present model were 0.73, 0.69 and 0.67 in the training cohort. The concordance index (c-index) and the Aiken information criterion (AIC) were 0.68 and 6216.3, respectively. In the internal and external validation cohorts, the present model still revealed excellent predictive accuracy, discrimination and fitness performance. Then the ALBI-AS based model was evaluated to be superior to other prognostic models with highest AUROC, c-index and lowest AIC values. Moreover, DCA also demonstrated that the present model was clinical beneficial. Additionally, participants could be classified into three distinct risk groups by the model.Conclusion: The ALBI-AS grade, as a pragmatic alternative of the ALBI grade, is a novel predictor of survival for patients with BCLC stage B HCC. The ALBI-AS based model was evaluated to be an accurate prognostic tool for individual prognostication, and performed well in terms of discrimination and fitness against other prognostic models. And it is appropriate to validate our findings on a larger prospective cohort.

A new staging system for radiotherapy-based treatment of hepatocellular carcinoma: A multicenter cohort study.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16155-e16155
Author(s):  
Ting-Shi Su ◽  
Shi-Xiong Liang ◽  
Li-Qing Li ◽  
Qiu-Hua Liu ◽  
Xiao-Fei Zhu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
External Validation ◽  
Staging System ◽  
Time Dependent ◽  
Multicenter Cohort Study ◽  
Discriminatory Ability ◽  
Training Cohort ◽  
Multicenter Cohort ◽  
Staging Systems

e16155 Background: External beam radiation therapy has been used as a palliative to radical treatment of hepatocellular carcinoma (HCC) depending on different tumor status, liver function and patient's general state of health. The existing models of HCC staging cannot perfectly predict the prognosis of radiotherapy. In this study, we aimed to set up a new staging system for radiotherapy-based treatment by incorporating bilirubin-albumin (ALBI) grade and tumor status for the prognostic classifications of HCC. Methods: This multicenter cohort study included 878 HCC patients who received radiotherapy-based treatment. A new staging system was established: stage I, solitary nodule without macrovascular invasion or 2-3 nodules with no more than 3.0 cm each other and PS 0-2 (Ia: ALBI-1 grade; Ib: ALBI-2 or 3 grade); stage II: 2-3 nodules with anyone more than 3.0 cm or ≥4 nodules and PS 0-2 (IIa: ALBI-1 grade; IIb: ALBI-2 grade); stage III: macrovascular invasion or regional lymph node metastasis or distant metastasis and PS 0-2 (IIIa: ALBI-1 grade; IIIb:ALBI-2 grade); stage IV: ALBI-3 grade without stage I patient or/and PS score 3-4. The new modified staging system and the existing staging systems, such as the BCLC, TNM, CNLC staging systems were used for prognostic analysis. All patients were separated into different stages and substages. The long-term overall survival outcomes and time-dependent receiver operating characteristic (ROC) were analyzed. Results: A training cohort of 595 patients underwent stereotactic body radiotherapy (SBRT) from 2011 to 2017 and an external validation cohort of 283 patients underwent intensity-modulated radiotherapy (IMRT) from 2000 to 2013 were included into establishing and validating the new staging system. In the training cohort, the median follow-up time was 55 months (range, 6–100 months), and the new staging system had a good discriminatory ability to separate patients into different stages with 4 notably different curves and substages with 7 notably different curves. BCLC staging could not differentiate stage 0 to A, and stage C to D in these selected patients. TNM staging could not completely distinguish stage IIIb to IV, but also stage Ia to Ib. CNLC staging could not differentiate among stage IIIa, IIIb, and IV. In the external validation, the median follow-up time was 95 months (range, 9–120 months), and the new staging system also had a good discriminatory ability to separate patients into different stages with 4 notably different curves and substages with 7 notably different curves. The new staging system had a better area under curve of time-dependent ROC than BCLC, TNM and CNLC staging in both SBRT and IMRT cohorts. Conclusions: The new modified (Su’s) staging system could provide a good discriminatory ability to separate patients into different stages and substages after radiotherapy treatment. It may be used to supplement the other HCC staging systems.

Identification and validation of a potent multi-mRNA signature for the prediction of early relapse in hepatocellular carcinoma

2019 ◽  
Vol 40 (7) ◽  
pp. 840-852 ◽  
Author(s):  
Jie Cai ◽  
Ying Tong ◽  
Lifeng Huang ◽  
Lei Xia ◽  
Han Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Messenger Rna ◽  
Validation Cohort ◽  
Expression Profiles ◽  
External Validation ◽  
Early Recurrence ◽  
Discovery Cohort ◽  
Early Relapse ◽  
Staging Systems

Abstract Early recurrence of hepatocellular carcinoma (HCC) is implicated in poor patient survival and is the major obstacle to improving prognosis. The current staging systems are insufficient for accurate prediction of early recurrence, suggesting that additional indicators for early recurrence are needed. Here, by analyzing the gene expression profiles of 12 Gene Expression Omnibus data sets (n = 1533), we identified 257 differentially expressed genes between HCC and non-tumor tissues. Least absolute shrinkage and selection operator regression model was used to identify a 24-messenger RNA (mRNA)-based signature in discovery cohort GSE14520. With specific risk score formula, patients were divided into high- and low-risk groups. Recurrence-free survival within 2 years (early-RFS) was significantly different between these two groups in discovery cohort [hazard ratio (HR): 7.954, 95% confidence interval (CI): 4.596–13.767, P < 0.001], internal validation cohort (HR: 8.693, 95% CI: 4.029–18.754, P < 0.001) and external validation cohort (HR: 5.982, 95% CI: 3.414–10.480, P < 0.001). Multivariable and subgroup analyses revealed that the 24-mRNA-based classifier was an independent prognostic factor for predicting early relapse of patients with HCC. We further developed a nomogram integrating the 24-mRNA-based signature and clinicopathological risk factors to predict the early-RFS. The 24-mRNA-signature-integrated nomogram showed good discrimination (concordance index: 0.883, 95% CI: 0.836–0.929) and calibration. Decision curve analysis demonstrated that the 24-mRNA-signature-integrated nomogram was clinically useful. In conclusion, our 24-mRNA signature is a powerful tool for early-relapse prediction and will facilitate individual management of HCC patients.

scholarly journals Clinical Utility of a Nomogram for Predicting 30-Days Poor Outcome in Hospitalized Patients With COVID-19: Multicenter External Validation and Decision Curve Analysis

2020 ◽  
Vol 7 ◽  
Author(s):  
Bin Zhang ◽  
Qin Liu ◽  
Xiao Zhang ◽  
Shuyi Liu ◽  
Weiqi Chen ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Clinical Utility ◽  
Predictive Accuracy ◽  
Fasting Blood Glucose ◽  
External Validation ◽  
Predictive Performance ◽  
Curve Analysis ◽  
Discriminative Ability ◽  
Decision Curve Analysis ◽  
Poor Outcome

Aim: Early detection of coronavirus disease 2019 (COVID-19) patients who are likely to develop worse outcomes is of great importance, which may help select patients at risk of rapid deterioration who should require high-level monitoring and more aggressive treatment. We aimed to develop and validate a nomogram for predicting 30-days poor outcome of patients with COVID-19.Methods: The prediction model was developed in a primary cohort consisting of 233 patients with laboratory-confirmed COVID-19, and data were collected from January 3 to March 20, 2020. We identified and integrated significant prognostic factors for 30-days poor outcome to construct a nomogram. The model was subjected to internal validation and to external validation with two separate cohorts of 110 and 118 cases, respectively. The performance of the nomogram was assessed with respect to its predictive accuracy, discriminative ability, and clinical usefulness.Results: In the primary cohort, the mean age of patients was 55.4 years and 129 (55.4%) were male. Prognostic factors contained in the clinical nomogram were age, lactic dehydrogenase, aspartate aminotransferase, prothrombin time, serum creatinine, serum sodium, fasting blood glucose, and D-dimer. The model was externally validated in two cohorts achieving an AUC of 0.946 and 0.878, sensitivity of 100 and 79%, and specificity of 76.5 and 83.8%, respectively. Although adding CT score to the clinical nomogram (clinical-CT nomogram) did not yield better predictive performance, decision curve analysis showed that the clinical-CT nomogram provided better clinical utility than the clinical nomogram.Conclusions: We established and validated a nomogram that can provide an individual prediction of 30-days poor outcome for COVID-19 patients. This practical prognostic model may help clinicians in decision making and reduce mortality.

scholarly journals External validation of the detection of indicators and vulnerabilities for emergency room trips (DIVERT) scale: a retrospective cohort study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Fabrice I. Mowbray ◽  
Aaron Jones ◽  
Connie Schumacher ◽  
John Hirdes ◽  
Andrew P. Costa
Keyword(s):  
Cohort Study ◽  
Home Care ◽  
Emergency Room ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Reporting System ◽  
Predictive Accuracy ◽  
External Validation ◽  
Discriminative Ability ◽  
Geographical Regions

Abstract Background The Detection of Indicators and Vulnerabilities of Emergency Room Trips (DIVERT) scale was developed to classify and estimate the risk of emergency department (ED) use among home care clients. The objective of this study was to externally validate the DIVERT scale in a secondary population of home care clients. Methods We conducted a retrospective cohort study, linking data from the Home Care Reporting System and the National Ambulatory Care Reporting System. Data were collected on older long-stay home care clients who received a RAI Home Care (RAI-HC) assessment. Data were collected for home care clients in the Canadian provinces of Ontario and Alberta, as well as in the cities of Winnipeg, Manitoba and Whitehorse, Yukon Territories between April 1, 2011 and September 30, 2014. The DIVERT scale was originally derived from the items of the RAI-HC through the use of recursive partitioning informed by a multinational clinical panel. This scale is currently implemented alongside the RAI-HC in provinces across Canada. The primary outcome of this study was ED visitation within 6 months of a RAI-HC assessment. Results The cohort contained 1,001,133 home care clients. The vast majority of cases received services in Ontario (88%), followed by Alberta (8%), Winnipeg (4%), and Whitehorse (< 1%). Across the four cohorts, the DIVERT scale demonstrated similar discriminative ability to the original validation work for all outcomes during the six-month follow-up: ED visitation (AUC = 0.617–0.647), two or more ED visits (AUC = 0.628–0.634) and hospital admission (AUC = 0.617–0.664). Conclusions The findings of this study support the external validity of the DIVERT scale. More specifically, the predictive accuracy of the DIVERT scale from the original work was similar to the accuracy demonstrated within a new cohort, created from different geographical regions and time periods.

scholarly journals An Evidence-Based Multidisciplinary Approach to the Management of Hepatocellular Carcinoma (HCC): The Alberta HCC Algorithm

2010 ◽  
Vol 24 (11) ◽  
pp. 643-650 ◽  
Author(s):  
Kelly W Burak ◽  
Norman M Kneteman
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Liver Function ◽  
Potential Role ◽  
Staging System ◽  
Evidence Based ◽  
Transarterial Radioembolization ◽  
Bclc Staging ◽  
Tumour Characteristics

Hepatocellular carcinoma (HCC) is one of only a few malignancies with an increasing incidence in North America. Because the vast majority of HCCs occur in the setting of a cirrhotic liver, management of this malignancy is best performed in a multidisciplinary group that recognizes the importance of liver function, as well as patient and tumour characteristics. The Barcelona Clinic Liver Cancer (BCLC) staging system is preferred for HCC because it incorporates the tumour characteristics (ie, tumour-node-metastasis stage), the patient’s performance status and liver function according to the Child-Turcotte-Pugh classification, and then links the BCLC stage to recommended therapeutic interventions. However, the BCLC algorithm does not recognize the potential role of radiofrequency ablation for very early stage HCC, the expanding role of liver transplantation in the management of HCC, the role of transarterial chemoembolization in single large tumours, the potential role of transarterial radioembolization with90Yttrium and the limited evidence for using sorafenib in Child-Turcotte-Pugh class B cirrhotic patients. The current review article presents an evidence-based approach to the multidisciplinary management of HCC along with a new algorithm for the management of HCC that incorporates the BCLC staging system and the authors’ local selection criteria for resection, ablative techniques, liver transplantation, transarterial chemoembolization, transarterial radioembolization and sorafenib in Alberta.

scholarly journals External Validation of the Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) Scale: A Retrospective Cohort Study

2020 ◽  
Author(s):  
Fabrice Immanuel Mowbray ◽  
Aaron Jones ◽  
Connie Schumacher ◽  
John Hirdes ◽  
Andrew Paul Costa
Keyword(s):  
Cohort Study ◽  
Home Care ◽  
Emergency Room ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Reporting System ◽  
Predictive Accuracy ◽  
External Validation ◽  
Discriminative Ability ◽  
Geographical Regions

Abstract Background: The Detection of Indicators and Vulnerabilities of Emergency Room Trips (DIVERT) scale was developed to classify and estimate the risk of emergency department (ED) use in home care clients. The objective of this study was to externally validate the DIVERT scale in a secondary population of home care clients.Methods: We conducted a retrospective cohort study, linking data from the Home Care Reporting System and the National Ambulatory Care Reporting System. Data were collected on older long-stay home care clients who received a RAI Home Care (RAI-HC) assessment. Data were collected for home care clients in the Canadian provinces of Ontario and Alberta, as well as in the cities of Winnipeg, Manitoba and Whitehorse, Yukon Territories, between April 1, 2011 and September 30, 2014. The DIVERT Scale was originally derived from the items of the RAI-HC through the use of recursive partitioning informed by a multinational clinical panel. This scale is currently implemented alongside the RAI-HC in provinces across Canada. The primary outcome of this study was an ED visit within six months of a RAI-HC assessment.Results: The cohort contained 1,001,133 home care clients. The vast majority of cases received services in Ontario (88%), followed by Alberta (8%), Winnipeg (4%), and Whitehorse (<1%). Across the four cohorts, the DIVERT scale demonstrated similar discriminative ability to the original validation work for all outcomes during the six-month follow-up: ED visitation (AUC =0.617-0.647), two or more ED visits (AUC = 0.628-0.634), and hospital admission (AUC = 0.617-0.664).Conclusions: The findings of this study support the external validity of the DIVERT scale. More specifically, the predictive accuracy of the DIVERT scale from the original work was similar to the accuracy demonstrated within a new cohort, created from different geographical regions and time periods.

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