Integrated Liver Inflammatory Score Predicts the Therapeutic Outcome of Patients with Hepatocellular Carcinoma after Transarterial Chemoembolization

Yu, Meihong; An, Tian-Zhi; Li, Junxiang; Chang, De‐Hua; Zhang, Zishu; Xiao, Yue

doi:10.1016/j.jvir.2021.03.540

Cited by 4 publications

(4 citation statements)

References 25 publications

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“…Additionally, the present study demonstrated that PLT and NLR were predictors of early refractoriness. Several inflammatory indices, such as PLT and NLR, have been investigated to predict the long-term prognosis of HCC patients 35 , 36 . However, regarding the early TACE refractoriness, their predictive potential has not been demonstrated yet, and the present study preliminary revealed that PLT and NLR were predictive factors of early TACE refractoriness.…”

Section: Discussionmentioning

confidence: 99%

Predicting early refractoriness of transarterial chemoembolization in patients with hepatocellular carcinoma using a random forest algorithm: A pilot study

Zou

et al. 2021

J. Cancer

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Purpose: To develop and validate a random forest (RF) based predictive model of early refractoriness to transarterial chemoembolization (TACE) in patients with unresectable hepatocellular carcinoma (HCC). Methods: A total of 227 patients with unresectable HCC who initially treated with TACE from three independent institutions were retrospectively included. Following a random split, 158 patients (70%) were assigned to a training cohort and the remaining 69 patients (30%) were assigned to a validation cohort. The process of variables selection was based on the importance variable scores generated by RF algorithm. A RF predictive model incorporating the selected variables was developed, and five-fold cross-validation was performed. The discrimination and calibration of the RF model were measured by a receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow test. Results: The potential variables selected by RF algorithm for developing predictive model of early TACE refractoriness included patients' age, number of tumors, tumor distribution, platelet count (PLT), and neutrophil-to-lymphocyte ratio (NLR). The results showed that the RF predictive model had good discrimination ability, with an area under curve (AUC) of 0.863 in the training cohort and 0.767 in the validation cohort, respectively. In Hosmer-Lemeshow test, the RF model had a satisfactory calibration with P values of 0.538 and 0.068 in training cohort and validation cohort, respectively. Conclusion: The RF algorithm-based model has a good predictive performance in the prediction of early TACE refractoriness, which may easily be deployed in clinical routine and help to determine the optimal patient of care.

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Section: Discussionmentioning

confidence: 99%

Predicting early refractoriness of transarterial chemoembolization in patients with hepatocellular carcinoma using a random forest algorithm: A pilot study

Zou

et al. 2021

J. Cancer

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“…This result is because the feeding arteries for the central portion of the liver are usually small, which may end in incomplete embolization of the tumor. [20][21][22] This study has several limitations. First, this was a retrospective study.…”

Section: Discussionmentioning

confidence: 99%

“…This result is because the feeding arteries for the central portion of the liver are usually small, which may end in incomplete embolization of the tumor. 20–22…”

Section: Discussionmentioning

confidence: 99%

Tumor enhancement ratio with unenhanced imaging is an independent prognostic factor for patients with hepatocellular carcinoma after transarterial chemoembolization

Yang

Deng

et al. 2021

J Int Med Res

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Objective To investigative whether the odds tumor enhancement ratio (OTER) on cross-sectional imaging is a prognostic factor for hepatocellular carcinoma after transarterial chemoembolization (TACE). Methods This study involved 126 patients who underwent TACE from May 2015 to March 2019. The signal intensity/Hounsfield units (HU) was measured by placing regions of interest on the tumor and surrounding liver in unenhanced and arterial-phase contrast-enhanced cross-sectional images. The OTER was calculated as follows: OTER = (HUTUMORart − HUTUMORun)/ (HULIVERart − HULIVERun). Univariate analysis was performed to determine the factors associated with overall survival (OS). Variables with a P value of <0.10 were included in the multivariate Cox regression analysis. Results The median OS was 757 days. Tumors with a peripheral location, small size, and low OTER had better OS than those with a central location, large size, and high OTER. OS did not differ according to the extent of tumor involvement or tumor enhancement pattern. The OTER, tumor location, and size were included in the multivariate Cox regression analysis. A low OTER was the predictor of better OS. Conclusion A high OTER is a risk factor for poor OS in patients undergoing TACE. This should be taken into consideration before the procedure.

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“…This feature allows ILIS to perform better than other inflammatory indicators in prognosis assessment. Recent studies have shown that ILIS can predict outcomes in HCC patients after transarterial chemoembolization (TACE) [ 9 ]. However, the efficacy of ILIS as a predictive marker is not yet established in patients with early to mid-stage HCC who are amenable to radical resection.…”

Section: Introductionmentioning

confidence: 99%

Prognostic Significance of Preoperative Integrated Liver Inflammatory Score in Patients with Hepatocellular Carcinoma

Guo

et al. 2022

Med Sci Monit

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Background The Integrated Liver Inflammatory Score (ILIS), which includes 5 serum indicators (albumin, bilirubin, neutrophil count, alpha-fetoprotein [AFP], and alkaline phosphatase [ALP]), is a novel inflammation-based predictive model associated with poor survival in hepatocellular carcinoma (HCC) patients. Our study aimed to assess the prognostic value of ILIS in HCC patients undergoing radical hepatectomy and establish a nomogram and artificial neural network based on their ILIS scores. Material/Methods This multicenter retrospective study included patients from 2 institutions from 2007 to 2017. Independent risk factors associated with Recurrence-free survival (RFS) and overall survival (OS) were identified through univariate and multifactor analysis in the training and validation groups, respectively. Afterward, column line graphs and artificial neural networks (ANN) were constructed and validated using the validation group. Results A total of 432 patients were included in this study (275 in the training group and 157 in the validation group). In both cohorts, ILIS was correlated with pathological features such as tumor size, degree of differentiation, Child-Pugh class classification, and BCLC staging. Moreover, ILIS was identified as an independent risk factor for OS. ILIS-based nomograms and artificial neural networks also showed the prognostic value of ILIS. Conclusions Preoperative ILIS is an independent and effective predictor of prognosis in HCC patients treated with radical hepatectomy, as shown by the fact that higher ILIS are associated with worse patient prognosis. We have also established nomograms and ANNs that predict HCC prognosis with high accuracy.

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Integrated Liver Inflammatory Score Predicts the Therapeutic Outcome of Patients with Hepatocellular Carcinoma after Transarterial Chemoembolization

Cited by 4 publications

References 25 publications

Predicting early refractoriness of transarterial chemoembolization in patients with hepatocellular carcinoma using a random forest algorithm: A pilot study

Predicting early refractoriness of transarterial chemoembolization in patients with hepatocellular carcinoma using a random forest algorithm: A pilot study

Tumor enhancement ratio with unenhanced imaging is an independent prognostic factor for patients with hepatocellular carcinoma after transarterial chemoembolization

Prognostic Significance of Preoperative Integrated Liver Inflammatory Score in Patients with Hepatocellular Carcinoma

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