Platelet-albumin-bilirubin grade: Risk stratification of liver failure, prognosis after resection for hepatocellular carcinoma

Lü, Liang; Zhang, Yong Fa; Cai, Mengli; Kan, Anna; Zhong, Xiaomei; Mei, Jie; Ling, Yuye; Li, Shao Hua; Shi, Ming; Wei, Wei; Guo, Rong

doi:10.1016/j.dld.2019.04.006

Cited by 25 publications

(33 citation statements)

References 29 publications

(36 reference statements)

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“…9 Another study enrolling 2038 HCC patients with C-P grade A showed that PALBI grade was a simple, objective and discriminatory model for risk stratification of postoperative liver failure and prognosis. 10 In line with the above reports, our findings indicated that PALBI grade could be used as a predictor of survival in HCC. However, PALBI was not a significant predictor of survival in the 36 HCC patients with C-P grade B cirrhosis (not shown, P = 0.948 for OS and P = 0.957 for RFS).…”

Section: Discussionsupporting

confidence: 90%

“…Platelet-albumin-bilirubin (PALBI), is also widely used to assess liver function and prognosis in HCC. [7][8][9][10][11] However, the role of platelets in HCC is quite complicated and is even conflicting. On the one hand, preoperative thrombocytopenia (platelet count (PLT) <100×10⁹/L) is a significant predictor of poor survival and high risk of recurrence in HCC.…”

Section: Introductionmentioning

confidence: 99%

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<p>The Significance of Platelet–Albumin–Bilirubin (PALBI) Grade in Hepatocellular Carcinoma Patients Stratified According to Platelet Count</p>

Pang¹,

Liu²,

Wang³

et al. 2020

CMAR

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Background Platelet–albumin–bilirubin (PALBI) has been demonstrated to be superior to conventional Child–Pugh (C-P) grade in evaluating liver function and prognosis of HCC patients. However, both thrombocytosis and thrombocytopenia are unfavorable for HCC survival. The aim of this study was to preliminarily investigate the prognostic value of PALBI in HCC patients with thrombocytopenia and excluding thrombocytopenia. Methods In this retrospective cohort study, we reviewed 465 cases of HCC patients who underwent radical surgery. PALBI grade was calculated based on preoperative serological examinations. The primary outcomes were overall survival (OS) and recurrence-free survival (RFS), which were assessed by Kaplan–Meier method and Cox regression. The prognostic performances of PALBI and other models were estimated by using the concordance index (C-index). Results During a median follow-up time of 28 months, 31.6% (147/465) of patients died and 33.5% (156/465) experienced recurrence. Multivariate analyses revealed that both thrombocytosis and thrombocytopenia were independently associated with poor OS and RFS compared with normal platelet count (PLT) in HCC patients. Stratified analysis further revealed that PALBI was a significant predictor for HCC survival in patients excluding thrombocytopenia but not in patients with thrombocytopenia. In particular, in HCC patients excluding thrombocytopenia, the combination of tumor size with PALBI (C-index = 0.730, 95% CI: 0.674–0.786) may be superior to the classical Barcelona Clinic Liver Cancer (BCLC) and Cancer of Liver Italian Program (CLIP) staging systems in predicting survival. Conclusion In conclusion, PALBI grade, in particular the combination with tumor size, is an effective model for discriminating survival in HCC patients excluding thrombocytopenia but not in thrombocytopenic HCC patients.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

<p>The Significance of Platelet–Albumin–Bilirubin (PALBI) Grade in Hepatocellular Carcinoma Patients Stratified According to Platelet Count</p>

Pang¹,

Liu²,

Wang³

et al. 2020

CMAR

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“…e proposed PALBI could compensate for the shortcomings of ALBI grading. In our study, the ROC analysis revealed that the PALBI grade had better accuracy in predicting PHLF in the training set than the Child-Pugh or the ALBI grade, and the results were consistent with a previous study [34]. In contrast, Ye et al [30] and Xu et al [35] derived opposite conclusions: the ALBI grade showed a larger AUROC curve for predicting PHLF in HCC patients than PALBI and Child-Pugh grade, and the same results were also observed in the validation set from the present study.…”

Section: Discussionsupporting

confidence: 92%

Development and Validation of a Nomogram Based on Noninvasive Liver Reserve and Fibrosis (PALBI and FIB-4) Model to Predict Posthepatectomy Liver Failure Grade B-C in Patients with Hepatocellular Carcinoma

Zhong

Zhang

Huang

et al. 2021

Journal of Oncology

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Hepatectomy is currently one of the most effective treatments for hepatocellular carcinoma (HCC). However, postoperative liver failure (PHLF) is a serious complication and the leading cause of mortality in patients with HCC after hepatectomy. This study attempted to develop a novel nomogram based on noninvasive liver reserve and fibrosis models, platelet-albumin-bilirubin grade (PALBI) and fibrosis-4 index (FIB-4), able to predict PHLF grade B-C. This was a single-centre retrospective study of 574 patients with HCC undergoing hepatectomy between 2014 and 2018. The independent risk factors of PHLF were screened using univariate and multivariate logistic regression analyses. Multivariate logistic regression was performed using the training set, and the nomogram was developed and visualised. The utility of the model was evaluated in a validation set using the receiver operating characteristic (ROC) curve. A total of 574 HCC patients were included (383 in the training set and 191 for the validation set) and included PHLF grade B-C complications of 14.8, 15.4, and 13.6%, respectively. Overall, cirrhosis ( P < 0.026 , OR = 2.296, 95% confidence interval (CI) 1.1.02–4.786), major hepatectomy ( P = 0.031 , OR = 2.211, 95% CI 1.077–4.542), ascites ( P = 0.014 , OR = 3.588, 95% 1.299–9.913), intraoperative blood loss ( P < 0.001 , OR = 4.683, 95% CI 2.281–9.616), PALBI score >−2.53 (, OR = 3.609, 95% CI 1.486–8.764), and FIB-4 score ≥1.45 ( P < 0.001 , OR = 5.267, 95% CI 2.077–13.351) were identified as independent risk factors associated with PHLF grade B-C in the training set. The areas under the ROC curves for the nomogram model in predicting PHLF grade B-C were significant for both the training and validation sets (0.832 vs 0.803). The proposed nomogram predicted PHLF grade B-C among patients with HCC with a better prognostic accuracy than other currently available fibrosis and noninvasive liver reserve models.

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“…In the Zhongshan cohort, hospital stay of patients without PHLF (median [IQR]: 8 [7-10] days) was shorter than that of grade A (10 [8-13] days), grade B (10 [8-13] days) and grade C (16.5 [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] days) PHLF patients (p<0.001 for all).…”

Section: Clinical Characteristicsmentioning

confidence: 99%

Development and Validation of a Nomogram Based on Perioperative Factors to Predict Post-hepatectomy Liver Failure

Xu¹,

Li²,

Ye³

et al. 2021

Journal of Clinical and Translational Hepatology

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Background and Aims: Post-hepatectomy liver failure (PHLF) is a severe complication and main cause of death in patients undergoing hepatectomy. The aim of this study was to build a predictive model of PHLF in patients undergoing hepatectomy. Methods: We retrospectively analyzed patients undergoing hepatectomy at Zhongshan Hospital, Fudan University from July 2015 to June 2018, and randomly divided them into development and internal validation cohorts. External validation was performed in an independent cohort. Least absolute shrinkage and selection operator (commonly referred to as LASSO) logistic regression was applied to identify predictors of PHLF, and multivariate binary logistic regression analysis was performed to establish the predictive model, which was visualized with a nomogram. Results: A total of 492 eligible patients were analyzed. LAS-SO and multivariate analysis identified three preoperative variables, total bilirubin (p=0.001), international normalized ratio (p<0.001) and platelet count (p=0.004), and two intraoperative variables, extent of resection (p=0.002) and blood loss (p=0.004), as independent predictors of PHLF. The area under receiver operating characteristic curve (referred to as AUROC) of the predictive model was 0.838 and outperformed the model for end-stage liver disease score, albumin-bilirubin score and platelet-albumin-bilirubin score (AUROCs: 0.723, 0.695 and 0.663, respectively; p<0.001 for all). The optimal cut-off value of the predictive model was 14.7. External validation showed the model could predict PHLF accurately and distinguish high-risk patients. Conclusions: PHLF can be accurately predicted by this model in patients undergoing hepatectomy, which may significantly contribute to the postoperative care of these patients.

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Platelet-albumin-bilirubin grade: Risk stratification of liver failure, prognosis after resection for hepatocellular carcinoma

Cited by 25 publications

References 29 publications

<p>The Significance of Platelet–Albumin–Bilirubin (PALBI) Grade in Hepatocellular Carcinoma Patients Stratified According to Platelet Count</p>

<p>The Significance of Platelet–Albumin–Bilirubin (PALBI) Grade in Hepatocellular Carcinoma Patients Stratified According to Platelet Count</p>

Development and Validation of a Nomogram Based on Noninvasive Liver Reserve and Fibrosis (PALBI and FIB-4) Model to Predict Posthepatectomy Liver Failure Grade B-C in Patients with Hepatocellular Carcinoma

Development and Validation of a Nomogram Based on Perioperative Factors to Predict Post-hepatectomy Liver Failure

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