Forns index predicts recurrence and death in patients with hepatitis B‐related hepatocellular carcinoma after curative resection

Choi, Won‐Mook; Lee, Jeong Hoon; Ahn, Hongkeun; Cho, Hyeki; Cho, Young Youn; Lee, Minjong; Yoo, Jeong‐Ju; Cho, Yuri; Lee, Dong Hoon; Lee, Yun Bin; Cho, Eun Ju; Yu, Su Jong; Yi, Nam Joon; Lee, Kwang Woong; Kim, Yoon Jun; Yoon, Jung Hwan; Suh, Kyung Suk; Kim, Chung Yong; Lee, Hyo Suk

doi:10.1111/liv.12776

Cited by 20 publications

(23 citation statements)

References 35 publications

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“…Zhang et al reviewed the degree of cirrhosis affecting the prognosis of patients and found that the histological severity of cirrhosis is a vital adverse factor that affects the long-term outcomes of HCC patients undergoing liver surgery [38] . Similar results have been found in many reports [39][40][41] . The effect of AFP levels on patient prognosis is controversial.…”

Section: The Establishment Of Different Risk Groups According To the supporting

confidence: 93%

A practical nomogram from the SEER database to predict the prognosis of hepatocellular carcinoma patients with lymph node metastasis

Zhang

Tao

et al. 2020

Preprint

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Background: The presence of lymph node metastases is related to poor survival outcomes in hepatocellular carcinoma patients and because of the reported low probability of lymph node metastasis, research into the prognoses of such patients is difficult to conduct. In this study, we aimed to develop a nomogram model to predict the prognosis of HCC patients with lymph node metastasis and provided a reasonable basis for the choice of follow-up treatment.Methods: HCC patients diagnosed with LN metastasis from 2010 to 2015 were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate Cox regression and lasso regression were used to screen prognostic factors. Cox multiple-factor analysis was employed to investigate the independent prognostic factors for survival. The concordance index (C-index) and calibration curve were used to evaluate the predictive performance of our model. The clinical benefit was assessed via decision curve analysis (DCA). The survival was analyzed using Kaplan-Meier method and the differences among survival curves were compared by the log-rank test.Results: Patients were randomized into the training group (944 patients) and the validation group (402 patients) in a 70:30 ratio. Grade, T stage, surgery to the liver, chemotherapy, radiation recode, AFP, fibrosis score, tumor size group, M stage were selected as independent prognostic factors, and we developed nomograms using these variables. The c-indices of the training and validation groups were 0.70 and 0.73, respectively. The calibration curves for probability of survival showed good agreement. The DCA indicated that the nomogram had positive net benefits. Patients were divided into two risk groups according to our model, survival curves were drawn, and the log-rank test was performed, the p-value of which was <0.001.Conclusions: The nomogram can accurately predict the prognosis of HCC patients with lymph nodes metastasis and provide a reasonable basis for treatment.

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Section: The Establishment Of Different Risk Groups According To the supporting

confidence: 93%

A practical nomogram from the SEER database to predict the prognosis of hepatocellular carcinoma patients with lymph node metastasis

Zhang

Tao

et al. 2020

Preprint

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“…Zhang et al reviewed the degree of cirrhosis affecting the prognosis of patients and found that the histological severity of cirrhosis is a vital adverse factor that affects the long-term outcomes of HCC patients undergoing liver surgery [36] . Similar results have been found in many reports [37][38][39] . The effect of AFP levels on patient prognosis is controversial.…”

Section: Discussionsupporting

confidence: 93%

A practical nomogram predicting the prognosis of hepatocellular carcinoma patients with lymph node metastasis: A population-based analysis

Zhang

Tao

et al. 2020

Preprint

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Background: Lymph node (LN) metastasis is associated with poor survival outcomes in patients with hepatocellular carcinoma (HCC) patients and because of the reported low probability of lymph node metastasis, research into the Anchorprognoses of such patients is difficult to conduct. In this study, we aimed to develop a nomogram model to predict the prognosis of HCC patients with lymph node metastasis. Methods: HCC patients diagnosed with LN metastasis from 2010 to 2015 were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate Cox regression and lasso regression were used to screen prognostic factors. Cox multiple-factor analysis was used to investigate the independent risk factors for survival. We developed a prognostic nomograms using these independent risk factors. The predictive performance of our nomogram model was evaluated according to the concordance index (C-index) and calibration curve. The net clinical benefit was assessed via decision curve analysis (DCA). Patients were divided into different risk groups according to the model. A survival curve was drawn using the Kaplan-Meier method and the difference was compared by the log-rank test. Results: There were 944 patients in the training cohort and 402 patients in the validation cohort. Grade, T stage, surgery to the liver, chemotherapy, radiation recode, AFP, fibrosis score, tumor size group, M stage were selected as independent prognostic factors, and we developed nomograms using these variables. The calibration curves for probability of survival showed good agreement between the prediction by our model and actual observation in both the training and validation groups. DCA indicated that the nomogram had positive net benefits. Conclusions: The nomogram can accurately predict the prognosis of HCC patients with lymph nodes metastasis and provide a reasonable basis for treatment. Keywords: Hepatocellular carcinoma, prognosis, lymph nodes metastasis, prediction model, nomogram

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“…Forns test A study of liver fibrosis indices (APRI, FIB-4 index, and Forns index) showed that Forns index performed before HCV antiviral therapy was a predictor to identify patients with low likelihood of developing HCC after achieving a sustained virologic response [132] . Morevoer, Forns index was found to predict the recurrence and death of patients with hepatitis B-related HCC after curative resection [133] .…”

Section: Fibrosis-4 Indexmentioning

confidence: 95%

New and old biomarkers of hepatocellular carcinoma

Zacharakis¹,

AlEid²,

Aldossari³

2018

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Hepatocellular carcinoma (HCC) is a significant cause of mortality in patients with chronic liver disease around the world. Development of biomarkers for early HCC detection is a primary public health goal to decrease mortality. The ideal biomarkers should be highly sensitive and specific for surveillance of high-risk populations and early detection of HCC and also be able to predict therapeutic outcome and provide a prognosis on survival. Currently, the new biomarkers do not perform better than the conventional ones such as alpha-fetoprotein in such a way that they could be widely adopted in clinical practice. Another problem is the low sensitivity of these biomarkers in the detection of HCC. Further work on the development of novel biomarkers and on a combination of them is necessary. Advances in identifying unique molecular signatures including genomic, proteomic, metabolomic, and glycomic profiles have improved our understanding of many biological processes involved in HCC. This review focuses on the role of old and new biomarkers in surveillance, diagnosis, prognosis, and prediction of response to therapeutic targets for HCC and provides up-to-date data to health-care providers which would be applied in clinical practice.

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Forns index predicts recurrence and death in patients with hepatitis B‐related hepatocellular carcinoma after curative resection

Abstract: Our data suggest that Forns index could be a useful predictor of recurrence and overall survival after curative resection of HBV-related HCC.

Cited by 20 publications

References 35 publications

A practical nomogram from the SEER database to predict the prognosis of hepatocellular carcinoma patients with lymph node metastasis

A practical nomogram from the SEER database to predict the prognosis of hepatocellular carcinoma patients with lymph node metastasis

A practical nomogram predicting the prognosis of hepatocellular carcinoma patients with lymph node metastasis: A population-based analysis

New and old biomarkers of hepatocellular carcinoma

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