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Updated: Jun 26, 2025
A Three-Dimensional Spheroid Model to Investigate the Tumor-Stromal Interaction in Hepatocellular Carcinoma
Published on: September 30, 2021
Meta-analysis of the GALAD model for diagnosing primary hepatocellular carcinoma
Jian-Lin Lu1,1, Xiao-Yan Yuan2,1, Jin-Shan Zhang1
1Department of Radiation Oncology and Nuclear Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Background:
Ever since the GALAD (gender-age-Lens culinaris agglutinin-reactive alpha-fetoprotein-alpha-fetoprotein-des-gamma-carboxy prothrombin) logistic regression model was established to diagnose hepatocellular carcinoma (HCC), there has been no high-level evidence that evaluates and summarizes it.
Objective:
This meta-analysis was performed to assess the diagnostic ability of the GALAD model.
Methods:
The following databases were systematically searched for original diagnostic studies on HCC: PubMed, Embase, Medline, the Web of Science, Cochrane Library, China National Knowledge Infrastructure Wanfang (China), Wiper and the Chinese BioMedical Literature Database. After screening the search results according to our criteria, the Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to evaluate the methodologic qualities, and statistical software were used to output the statistics.
Results:
Ultimately, 10 studies were included and analyzed. The results revealed the pooled sensitivity and specificity of the GALAD model to be 0.86 (95% confidence interval [CI]: 0.82, 0.90) and 0.90 (95% CI: 0.87, 0.92), respectively, for all-stage HCC. The area under the curve (AUC) was 0.94. For early-stage HCC, the pooled sensitivity and specificity of the GALAD model were 0.83 (95% CI: 0.78, 0.87) and 0.81 (95% CI: 0.78, 0.83), respectively. The AUC was 0.90.
Conclusion:
This meta-analysis confirmed that the GALAD model has excellent diagnostic performance for early-stage and all-stage HCC and can maintain high sensitivity and specificity in early-stage HCC. Therefore, the GALAD model is qualified for screening early-stage canceration from chronic liver disease.
