Combined prognostic nutritional index and albumin-bilirubin grade to predict the postoperative prognosis of HBV-associated hepatocellular carcinoma patients

Liang, Xie; Xu, Lixia; Wang, Peng; Yan, Tao; Zhang, Jinfu; Zhang, Ming; Xu, Mingqing

doi:10.1038/s41598-021-94035-5

Cited by 7 publications

(4 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It can be affirmed that albumin levels are determinant as a prognostic factor in patients with HCC. Low levels of serum albumin are associated with poor nutritional status and a worse prognosis at the diagnosis of HCC [48,49]. Furthermore, various studies describe the importance of albumin as a negative regulator in the progression of HCC, particularly in local invasion and metastasis of HCC [50].…”

Section: Discussionmentioning

confidence: 99%

Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial Intelligence

Martínez-Blanco,

Suárez,

Gil-Rojas

et al. 2024

Diagnostics

View full text Add to dashboard Cite

Background: Hepatocellular carcinoma (HCC) accounts for 75% of primary liver tumors. Controlling risk factors associated with its development and implementing screenings in risk populations does not seem sufficient to improve the prognosis of these patients at diagnosis. The development of a predictive prognostic model for mortality at the diagnosis of HCC is proposed. Methods: In this retrospective multicenter study, the analysis of data from 191 HCC patients was conducted using machine learning (ML) techniques to analyze the prognostic factors of mortality that are significant at the time of diagnosis. Clinical and analytical data of interest in patients with HCC were gathered. Results: Meeting Milan criteria, Barcelona Clinic Liver Cancer (BCLC) classification and albumin levels were the variables with the greatest impact on the prognosis of HCC patients. The ML algorithm that achieved the best results was random forest (RF). Conclusions: The development of a predictive prognostic model at the diagnosis is a valuable tool for patients with HCC and for application in clinical practice. RF is useful and reliable in the analysis of prognostic factors in the diagnosis of HCC. The search for new prognostic factors is still necessary in patients with HCC.

show abstract

Section: Discussionmentioning

confidence: 99%

Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial Intelligence

Martínez-Blanco,

Suárez,

Gil-Rojas

et al. 2024

Diagnostics

View full text Add to dashboard Cite

show abstract

“…Prospective clinical studies have identified malnutrition as an independent negative prognostic factor in patients with HCC ( 26 ). Preoperative malnutrition may lead to increased postoperative infection and complications, resulting in delayed recovery ( 27 ). The predictive role of inflammation and nutrition markers in the prognosis of patients with HCC is of increasing interest.…”

Section: Discussionmentioning

confidence: 99%

Prognostic value of combined inflammatory and nutritional biomarkers in HCC within the Milan criteria after hepatectomy

Feng

Xing²,

Zhao³

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

AimsThis study aimed to evaluate the predictive value of the combined prognostic nutritional index (PNI) and GGT/ALT for the postoperative prognosis of patients with hepatocellular carcinoma (HCC) within Milan criteria undergoing radical hepatectomy.MethodsThis single-center retrospective study included 283 patients with HCC within the Milan criteria who underwent hepatectomy. The receiver operating characteristic (ROC) curve was used to calculate the optimal PNI and GGT/ALT cut-off values. Pre-treatment PNI, GGT/ALT, and PNI-GGT/ALT grades were calculated. Overall survival (OS) and recurrence-free survival (RFS) were estimated using the Kaplan–Meier method, and multivariate analysis was used to identify prognostic factors.ResultsMultivariate Cox regression analysis identified that the PNI, GGT/ALT, tumor number were significant prognostic markers for OS, and that the GGT/ALT, tumor number were significant prognostic markers for OS. The survival curves showed that low PNI, high GGT/ALT ratio, and high PNI-GGT/ALT grade were associated with poorer OS and DFS. With an area under the curve (AUC) of 0.690, PNI-GGT/ALT outperformed each individual score.ConclusionPNI-GGT/ALT, a new prognostic scoring model, qualifies as a novel prognostic predictor for patients with HCC within the Milan criteria after curative resection.

show abstract

“…HBV-HCC prognosis is linked to several factors, including tumor burden, AFP, disease stage, ALBI, and NLR (18,19), and there are also nomograms about HBV-HCC (20)(21)(22). However, no nomogram for HCC patients with high HBsAg expression after local treatment has been available to our knowledge.…”

Section: Introductionmentioning

confidence: 99%

Construction and validation of a machine learning-based nomogram to predict the prognosis of HBV associated hepatocellular carcinoma patients with high levels of hepatitis B surface antigen in primary local treatment: a multicenter study

Xiong,

Qiao,

Wang

et al. 2024

Front. Immunol.

View full text Add to dashboard Cite

BackgroundHepatitis B surface antigen (HBsAg) clearance is associated with improved long-term outcomes and reduced risk of complications. The aim of our study was to identify the effects of levels of HBsAg in HCC patients undergoing TACE and sequential ablation. In addition, we created a nomogram to predict the prognosis of HCC patients with high levels of HBsAg (≥1000U/L) after local treatment.MethodThis study retrospectively evaluated 1008 HBV-HCC patients who underwent TACE combined with ablation at Beijing Youan Hospital and Beijing Ditan Hospital from January 2014 to December 2021, including 334 patients with low HBsAg levels and 674 patients with high HBsAg levels. The high HBsAg group was divided into the training cohort (N=385), internal validation cohort (N=168), and external validation cohort (N=121). The clinical and pathological features of patients were collected, and independent risk factors were identified using Lasso-Cox regression analysis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts. Patients were classified into high-risk and low-risk groups based on the risk scores of the nomogram.ResultAfter PSM, mRFS was 28.4 months (22.1-34.7 months) and 21.9 months (18.5-25.4 months) in the low HBsAg level and high HBsAg level groups (P<0.001). The content of the nomogram includes age, BCLC stage, tumor size, globulin, GGT, and bile acids. The C-index (0.682, 0.666, and 0.740) and 1-, 3-, and 5-year AUCs of the training, internal validation, and external validation cohorts proved good discrimination of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classification of patients with high HBsAg levels into low-risk and high-risk groups according to the risk of recurrence. There was a statistically significant difference in RFS between the two groups in the training, internal validation, and external validation cohorts (P<0.001).ConclusionHigh levels of HBsAg were associated with tumor progression. The nomogram developed and validated in the study had good predictive ability for patients with high HBsAg levels.

show abstract

Combined prognostic nutritional index and albumin-bilirubin grade to predict the postoperative prognosis of HBV-associated hepatocellular carcinoma patients

Cited by 7 publications

References 42 publications

Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial Intelligence

Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial Intelligence

Prognostic value of combined inflammatory and nutritional biomarkers in HCC within the Milan criteria after hepatectomy

Construction and validation of a machine learning-based nomogram to predict the prognosis of HBV associated hepatocellular carcinoma patients with high levels of hepatitis B surface antigen in primary local treatment: a multicenter study

Contact Info

Product

Resources

About