ArticlePeerJ2025
A cost-effective predictive tool for AFP-negative focal hepatic lesions of retrospective study: enhancing clinical triage and decision-making.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Hepatocellular carcinoma surveillance: a health economic evaluation.Clinical and molecular hepatology · 2026Review
- From Large-Scale Characterization to Subgroup-Specific Predictive Modeling: A Study on the Diagnostic Value of Liver Stiffness Measurements in Focal Liver Lesions.Diagnostics (Basel, Switzerland) · 2025Article
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Authors and funding
8 authors.
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Abstract
Background: Identifying alpha-fetal protein (AFP)-negative focal hepatic lesions presents a significant challenge, particularly in China. We sought to develop an economically portable tool for the diagnosis of benign and malignant liver lesions with AFP-negative status, and explore its clinical diagnostic efficiency. Methods: A retrospective study was conducted at Peking University Shenzhen Hospital from January 2017 to February 2023, including a total of 348 inpatients with AFP-negative liver space-occupying lesions. The study used a training set of 252 inpatients from January 2017 to September 2021 to establish a diagnostic model for differentiating benign and malignant AFP-negative liver space-occupying lesions. Additionally, a validation cohort of 96 inpatients from October 2021 to February 2023 was used to confirm the diagnostic performance of the model. From January 2017 to February 2023, patients at JingNing People's Hospital, Gansu Province were assigned to the external cohort ( Results: A predictive tool was established by screening age, gender, hepatitis B virus (HBV)/hepatitis C virus (HCV) infected, single lesion, alanine amino transferase (ALT), and lymphocyte-to-monocyte ratio (LMR) using multivariate logistic regression analysis and clinical practice. The area under the curve (AUC) of the model was 0.911 (95% CI [0.873-0.949]) in the training set and 0.882 (95% CI [0.815-0.949]) in the validation cohort. In addition, the model achieved an area under the curve of 0.811 (95% CI [0.687-0.935]) in the external validation cohort. Conclusion: Our results demonstrated that the predictive tool has the characteristics of good diagnostic efficiency, economy and convenience, which is helpful for the clinical triage and decision-making of AFP-negative liver space-occupying lesions.
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