Hypergammaglobulinemia is a strong predictor of disease progression, hepatocellular carcinoma, and death in patients with compensated cirrhosis

Cacciola, Irene; Filomia, Roberto; Alibrandi, Angela; Franzè, Maria Stella; Caccamo, Gaia; Maimone, S.; Saitta, Carlo; Squadrito, Giovanni; Raimondo, Giovanni

doi:10.1111/liv.13649

Cited by 10 publications

(10 citation statements)

References 23 publications

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“…It was reported that globulin is positively associate with mortality in patients with cirrhosis [31]. Serum gamma-globulin ≥18 g/L is a significant predictor of disease progression, tumor development and death for cirrhotic patients [32]. INR is used to assess bleeding risk and prognosis in cirrhosis, and end-stage liver disease score that integrates INR has the ability to prioritize patients for liver transplantation [33].…”

Section: Discussionmentioning

confidence: 99%

A radiomics-based model on non-contrast CT for predicting cirrhosis: make the most of image data

Wang

Tao

et al. 2020

Biomark Res

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Background To establish and validate a radiomics-based model for predicting liver cirrhosis in patients with hepatitis B virus (HBV) by using non-contrast computed tomography (CT). Methods This retrospective study developed a radiomics-based model in a training cohort of 144 HBV-infected patients. Radiomic features were extracted from abdominal non-contrast CT scans. Features selection was performed with the least absolute shrinkage and operator (LASSO) method based on highly reproducible features. Support vector machine (SVM) was adopted to build a radiomics signature. Multivariate logistic regression analysis was used to establish a radiomics-based nomogram that integrated radiomics signature and other independent clinical predictors. Performance of models was evaluated through discrimination ability, calibration and clinical benefits. An internal validation was conducted in 150 consecutive patients. Results The radiomics signature comprised 25 cirrhosis-related features and showed significant differences between cirrhosis and non-cirrhosis cohorts (P < 0.001). A radiomics-based nomogram that integrates radiomics signature, alanine transaminase, aspartate aminotransferase, globulin and international normalized ratio showed great calibration and discrimination ability in the training cohort (area under the curve [AUC]: 0.915) and the validation cohort (AUC: 0.872). Decision curve analysis confirmed the most clinical benefits can be provided by the nomogram compared with other methods. Conclusions Our developed radiomics-based nomogram can successfully diagnose the status of cirrhosis in HBV-infected patients, that may help clinical decision-making.

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Section: Discussionmentioning

confidence: 99%

A radiomics-based model on non-contrast CT for predicting cirrhosis: make the most of image data

Wang

Tao

et al. 2020

Biomark Res

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“…Recently, Cacciola et al studied the role of serum gamma globulins in relation to the clinical outcome in cirrhotic patients [ 19 ]. They proved that hypergammaglobulinemia is a strong predictor of disease progression, hepatocellular carcinoma and death in patients with cirrhosis, and that hypergammaglobulinemia may help identify the CTP class A cirrhotics with a poorer prognosis.…”

Section: Discussionmentioning

confidence: 99%

The significance of C-reactive protein to albumin ratio in patients with decompensated cirrhosis

Oikonomou

Goulis

Kiapidou

et al. 2020

aog

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Background Prognostic indicators in patients with decompensated cirrhosis are vital for the estimation of death risk. The ratio of C-reactive protein to albumin (CAR) has been verified as a prognostic marker in patients with hepatocellular carcinoma and decompensated cirrhosis related to hepatitis B virus. Neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and gamma globulins have been separately studied in cirrhosis. We evaluated the predictive role of CAR and other inflammatory markers in decompensated patients. Methods We prospectively studied 159 patients with stable decompensated cirrhosis, calculating the following indexes: CAR, NLR, LMR, Child-Turcotte-Pugh (CTP), and model for end-stage liver disease (MELD). Results MELD (area under the curve [AUC] 0.814) and CTP score (AUC 0.752) were superior to the other markers above in predicting patients’ mortality (P<0.05). Patients with CAR<2.17 (median value) presented better times of survival: 20 months (12-27) vs. 14 months (10-17) (log rank P=0.015). NLR and LMR barely discriminated patients’ prognosis. In multivariate analysis, only MELD and CTP scores were significant risk factors, whether using the proposed cutoff of 1.3 (hazard ratio [HR] 1.17 [1.106-2.44], P<0.001) or the median 2.17 CAR categorical variable (HR 1.17 [1.104-1.243], P<0.001). When patients who underwent liver transplantation were excluded, apart from the MELD and CTP scores CAR 2.17 was the only significant factor associated with the outcome (HR 3.61 [0.96-13.6], P=0.05) and detected different survival times: 10 (1-48) vs. 11 (2-38) months, log rank P=0.003. Patients with LMR≥1.9 presented significantly better renal function, in terms of true glomerular filtration rate (80±34 vs. 64±33 mL/min, P=0.004) and creatinine levels: 0.84 (0.1-1.8) vs. 0.98 (0.59-3.3) mg/dL (P=0.001). Conclusion Our findings demonstrate the significance of CAR and LMR in the outcome and renal function of decompensated patients.

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“…Diagnosis by imaging in the majority of cases removes the luxury of using traditional immunohistochemistry (IHC), or next-generation sequencing used to identify useful biomarkers like Her2 in breast cancer and MMR in colon cancer. As detailed in the table 1, biomarkers can be serum/blood-based testing [9][10][11][12][13][14][15][16][17] , genetic data (IHC or sequencing,) [16][17][18][19][20][21][22][23] , mutations in circulating tumor cells (CTC) [24] , or treatment specific (sorafenib [25,26] ,TARE [27] or SBRT [28] ). Most of these markers did not reach the clinical practice as of today.…”

Section: Biomarkers In Clinical Practicementioning

confidence: 99%

Challenges in the Current Management of Hepatocellular Carcinoma

Jogi¹,

Varanasi

Bantu

et al. 2021

ijirms

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Management of hepatocellular carcinoma (HCC) is complicated. Barcelona Clinic Liver Cancer (BCLC) staging system is widely used in risk stratifying HCC. It is different from anatomic staging (TNM) used in other cancers and is based on the liver function (Child-Pugh Score) and performance status at diagnosis along with tumor characteristics like size/number of primary, vascular invasion, and distant metastasis. Guidelines proposed by various liver societies help the treating physician select first-line therapy, but there are many limitations to them. Lack of reliable biomarkers that give objective information to monitor the response other than alpha-fetoprotein or radiological response is hurting the management strategies. There are no ideal predictors for recurrence and residual microscopic disease, especially after locoregional therapy (LRT) like surgical resection, ablation, transarterial chemoembolization (TACE), transarterial radioembolization (TARE), and stereotactic radiation therapy (SBRT). Also, there is no convincing evidence to use adjunct therapy along with LRT in localized HCC. There is a need to identify the subset of HCC that would benefit from peri-procedural therapy. Recommendations for treating advanced HCC with macrovascular invasion is not uniform across the guidelines. Some propose LRT (TACE and/or TARE) or recommend systemic therapy only like tyrosine-kinase inhibitors (TKI) or Immune-checkpoint inhibitors (ICI). A considerable portion of patients have poor liver function (Child-Pugh Score C) at diagnosis. In this era of medicine, we should give them options other than supportive care, but unfortunately, it is the preferred option. This population needs special attention in trials. In current practice, there only 2-3 classes of drugs available like TKI, ICI, and vascular endothelial growth factor (VEGF) inhibitors. There is a need to explore more classes of liver-friendly drugs in treating HCC, and the enrolment of patients in clinical trials must be advised in the guidelines.

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Hypergammaglobulinemia is a strong predictor of disease progression, hepatocellular carcinoma, and death in patients with compensated cirrhosis

Abstract: Hypergammaglobulinemia identifies C-P class A cirrhotic patients at higher risk of disease progression, HCC development and death.

Cited by 10 publications

References 23 publications

A radiomics-based model on non-contrast CT for predicting cirrhosis: make the most of image data

A radiomics-based model on non-contrast CT for predicting cirrhosis: make the most of image data

The significance of C-reactive protein to albumin ratio in patients with decompensated cirrhosis

Challenges in the Current Management of Hepatocellular Carcinoma

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