ArticleWorld journal of gastrointestinal surgery2024
Predictive value of NLR, Fib4, and APRI in the occurrence of liver failure after hepatectomy in patients with hepatocellular carcinoma.
Article in World journal of gastrointestinal surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Predicting post-hepatectomy liver failure using a nomogram based on portal vein width, inflammatory indices, and the albumin-bilirubin score.World journal of gastrointestinal surgery · 2025Article
- The predictive value of fibrosis profiles for hepatitis E virus-related liver failure among hospitalized patients with acute hepatitis E: a retrospective cohort study.BMC infectious diseases · 2025Article
- Development of a Starvation Response-Based Model and Its Application in Prognostic Assessment of Liver Hepatocellular Carcinoma.Mediators of inflammation · 2025Article
- Exploring predictive markers for liver failure post-hepatectomy in hepatocellular carcinoma patients.World journal of gastrointestinal surgery · 2024Article
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Abstract
backgroundNeutrophil-lymphocyte ratio (NLR), fibrosis index based on four factors (Fib4), aspartate aminotransferase-to-platelet ratio index (APRI) can be used for prognostic evaluation of hepatocellular carcinoma. However, no study has established an individualized prediction model for the prognosis of hepatocellular carcinoma based on these factors.
aimTo screen the factors that affect the prognosis of hepatocellular carcinoma and establish a nomogram model that predicts postoperative liver failure after hepatic resection in patients with hepatocellular carcinoma.
methodsIn total, 220 patients with hepatocellular carcinoma treated in our hospital from January 2022 to January 2023 were selected. They were divided into 154 participants in the modeling cohort, and 66 in the validation cohort. Comparative analysis of the changes in NLR, Fib4, and APRI levels in 154 patients with hepatocellular carcinoma before liver resection and at 3 mo, 6 mo, and 12 mo postoperatively was conducted. Binary logistic regression to analyze the influencing factors on the occurrence of liver failure in hepatocellular carcinoma patients, roadmap prediction modeling, and validation, patient work characteristic curves (ROCs) to evaluate the predictive efficacy of the model, calibration curves to assess the consistency, and decision curve analysis (DCA) to evaluate the model's validity were also conducted.
resultsBinary logistic regression showed that Child-Pugh grading, Surgical site, NLR, Fib4, and APRI were all risk factors for liver failure after hepatic resection in patients with hepatocellular carcinoma. The modeling cohort built a column-line graph model, and the area under the ROC curve was 0.986 [95% confidence interval (CI): 0.963-1.000]. The patients in the validation cohort utilized the column-line graph to predict the probability of survival in the validation cohort and plotted the ROC curve with an area under the curve of the model of 0.692 (95%CI: 0.548-0.837). The deviation of the actual outcome curves from the calibration curves of the column-line plots generated by the modeling and validation cohorts was small, and the DCA confirmed the validity.
conclusionNLR, Fib4, and APRI independently influence posthepatectomy liver failure in patients with hepatocellular carcinoma. The column-line graph prediction model exhibited strong prognostic capability, with substantial concordance between predicted and actual events.
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