A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma

Chen, Jinbin; Fang, Aiping; Chen, Minshan; Tuoheti, Yiminjiang; Zhou, Zhongguo; Xu, Li; Chen, Jiancong; Pan, Yangxun; Wang, Juncheng; Zhu, Huilian; Zhang, Yaojun

doi:10.1002/cam4.1787

Cited by 26 publications

(24 citation statements)

References 27 publications

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“…In addition, the results from the propensity score matching can enhance the usefulness of CAR. Similarity of the cut‐off values between our study and those reported by Shimizu et al, who have also examined cases of hepatectomy in confirmed HCC, could explain the difference in CAR cut‐off values between our study and previous reports as being due to the variety of treatments that HCC patients have received.…”

Section: Discussionsupporting

confidence: 86%

Verification of inflammation‐based prognostic marker as a prognostic indicator in hepatocellular carcinoma

Yamamoto

Kobayashi

Kuroda

et al. 2019

Annals of Gastroent Surgery

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AimAlthough inflammation‐based markers in cancer have been used for prognostic prediction, the most useful marker for hepatocellular carcinoma (HCC) has not been established. We investigated the usefulness of various inflammation‐based markers in HCC patients after hepatectomy.MethodsA total of 478 patients who underwent initial hepatectomy for HCC from 2009 to 2015 and were diagnosed with pathological HCC were included in this retrospective study. Inflammation‐based markers consisted of the C‐reactive protein to albumin ratio (CAR), Glasgow prognostic score (GPS), neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio, platelet to lymphocyte ratio and prognostic index. Univariate and multivariate analyses for overall survival (OS) and disease‐free survival (DFS) using the Cox proportional hazard model were carried out. Kaplan‐Meier analysis and log‐rank test were used for comparison of OS and DFS. To reduce influences of selection bias and confounders for stratifying CAR, clinicopathological characteristics of patients were balanced by propensity score matching.ResultsMultivariate analysis identified only high CAR (>0.027) as an indicator of poor OS, and high CAR and high GPS (1‐2) as indicators of poor DFS among inflammation‐based markers. After propensity score matching, 124 patients each with low CAR and high CAR were matched. High CAR was correlated with both poor OS and DFS.ConclusionC‐reactive protein to albumin ratio was the most valuable prognostic indicator after hepatectomy for HCC among inflammation‐based markers.

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Section: Discussionsupporting

confidence: 86%

Verification of inflammation‐based prognostic marker as a prognostic indicator in hepatocellular carcinoma

Yamamoto

Kobayashi

Kuroda

et al. 2019

Annals of Gastroent Surgery

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“…The nomogram is a prognostic prediction map based on multiple independent risk factors. It has been researched in a variety of tumors, and several studies have reported that its prediction performance is better than that of traditional liver cancer staging systems ( 10 , 11 ).…”

Section: Discussionmentioning

confidence: 99%

Nomogram Based on Systemic Immune Inflammation Index and Prognostic Nutrition Index Predicts Recurrence of Hepatocellular Carcinoma After Surgery

et al. 2020

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Background Surgery is a potential cure for hepatocellular carcinoma (HCC), but its postoperative recurrence rate is high, its prognosis is poor, and reliable predictive indicators are lacking. This study was conducted to develop a simple, practical, and effective predictive model. Materials and Methods Preoperative clinical and postoperative pathological data on patients with HCC undergoing partial hepatectomies at the Third Affiliated Hospital of Soochow University from January 2010 to December 2015 were retrospectively analyzed, and a nomogram was constructed. The model performance was evaluated using C-indexes, receiver operating characteristic curves, and calibration curves. The results were verified from validation cohort data collected at the same center from January 2016 to January 2017 and compared with the traditional staging systems. Results Three hundred three patients were enrolled in this study: 238 in the training cohort and 65 in the validation cohort. From the univariate and multivariate Cox regression analyses in the training cohort, six independent risk factors, i.e., age, alpha-fetoprotein (AFP), tumor size, satellite nodules, systemic immune inflammation index (SII), and prognostic nutritional index (PNI), were filtered and included in the nomogram. The C-index was 0.701 [95% confidence interval (CI): 0.654–0.748] in the training cohort and 0.705 (95% CI: 0.619–0.791) in the validation cohort. The areas under the curve for the 1- and 3-year recurrence-free survival were 0.706 and 0.716 in the training cohort and 0.686 and 0.743 in the validation cohort, respectively. The calibration curves showed good agreement. Compared with traditional American Joint Committee on Cancer 8th edition (AJCC8th) and Barcelona Clinic Liver Cancer (BCLC) staging systems, our nomogram showed better predictive ability. Conclusion Our nomogram is simple, practical, and reliable. According to our nomogram, predicting the risk of recurrence and stratifying HCC patient management will yield the greatest survival benefit for patients.

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“…The nomogram has been extensively applied to calculate the clinical risk factors and predict clinical prognosis in many tumors, which has shown favorable effects [36,37]. Hence, the risk score was connected with the clinical characteristics (grade, gender, age, IDH status, 1p/19q code), and a nomogram was constructed to prove that the risk score has a great performance in predicting the OS of glioma patients.…”

Section: Discussionmentioning

confidence: 99%

The Prognostic Value of Risk Score Based on Immunogenenomic Landscape Analysis in Glioma

Luo

Huang

Tao

et al. 2020

Preprint

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Background: Glioma is a lethal intracranial tumor, and inflammation plays an important role in the initiation and development of glioma. Hence, there is an urgent need to conduct a bioinformatics analysis of immune-related genes (IRGs) for glioma. The present study aims to explore the association of the risk score with clinical outcomes and predict the prognosis with glioma. Methods: In The Cancer Genome Atlas (TCGA) database, 462 low grade glioma (LGG) samples and 166 glioblastoma (GBM) samples were reviewed, and IRGs correlated with the prognosis were selected by performing a survival analysis and establishing a Cox regression model. The potential molecular mechanism of these IRGs were also explored with assistance of computational biology. The risk score based on seven survival-associated IRGs was determined with the help of the multivariable Cox analysis, the patients were divided into two subgroups according to their risk score. Results: It was found that these differentially expressed IRGs were involved with the cytokine-cytokine receptor through functional enrichment analysis. The risk score based on the seven IRGs (SSTR5、CXCL10、CCL13、SAA1、CCL21、CCL27 and HTR1A) performed well in predicting patient’s the overall survival (OS), and correlated with age, 1p/19q codeletion status, IDH status, and WHO grades, both in the training (TCGA) datasets and the validation ((Chinese Glioma Genome Atlas) CGGA) datasets. The risk score also could reflect infiltration through several types of immune cells. Conclusions: This present study screened some IRGs associated with the patient’s clinical characteristic and prognosis, connect to the immune repertoire, demonstrated the importance of the risk score as a promising biomarker for estimating the clinical prognosis of glioma.

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A novel inflammation‐based nomogram system to predict survival of patients with hepatocellular carcinoma

Cited by 26 publications

References 27 publications

Verification of inflammation‐based prognostic marker as a prognostic indicator in hepatocellular carcinoma

Verification of inflammation‐based prognostic marker as a prognostic indicator in hepatocellular carcinoma

Nomogram Based on Systemic Immune Inflammation Index and Prognostic Nutrition Index Predicts Recurrence of Hepatocellular Carcinoma After Surgery

The Prognostic Value of Risk Score Based on Immunogenenomic Landscape Analysis in Glioma

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