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Objectives <p>Prothrombin induced by vitamin K absence-II (PIVKA-II) is useful for detecting early-stage hepatocellular carcinoma (HCC). Here, we aimed to assess the diagnostic performance of two PIVKA-II assays measured using ARCHITECT and μTASWako for HCC, as well as HCC caused by the hepatitis B virus (HBV), in a Chinese population.</p> Design and methods <p>The GALAD HCC detection algorithm depends on the μTASWako PIVKA-II assay, while the ASAP algorithm uses the ARCHITECT PIVKA-II assay. These methods were validated and compared using a retrospective cohort of 431 HCC patients and 606 chronic liver disease (CLD) controls from Huashan Hospital between January 2022 and December 2023.</p> Results <p>Using receiver operating characteristic curve analyses of the validation cohort, the GALAD algorithm had an area under the curve (AUC) value of 0.896 [95% confidence interval (CI) 0.873–0.919], while the AUC value was 0.894 [95% CI 0.870–0.918] for the ASAP algorithm. The ASAP algorithm for HBV-associated HCC detection had the highest AUC value (0.950; 95% CI 0.933–0.967), with a sensitivity of 89.3% and specificity of 81.6%.</p> Conclusions <p>Using the GALAD and ASAP algorithms to detect HCC displayed similar favorable accuracy. The ASAP algorithm was more reliable for the detection of HBV-associated HCC in Chinese patients.</p>

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Comparison of the diagnostic performance of two PIVKA-II assays using the GALAD and ASAP algorithms for detecting hepatocellular carcinoma in Chinese patients

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月2日

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  • Yao Hu,
  • Jiaying Du,
  • Quan Gao,
  • Yi Cen,
  • Qin Liu,
  • Yanwen Chen

摘要

Objectives

Prothrombin induced by vitamin K absence-II (PIVKA-II) is useful for detecting early-stage hepatocellular carcinoma (HCC). Here, we aimed to assess the diagnostic performance of two PIVKA-II assays measured using ARCHITECT and μTASWako for HCC, as well as HCC caused by the hepatitis B virus (HBV), in a Chinese population.

Design and methods

The GALAD HCC detection algorithm depends on the μTASWako PIVKA-II assay, while the ASAP algorithm uses the ARCHITECT PIVKA-II assay. These methods were validated and compared using a retrospective cohort of 431 HCC patients and 606 chronic liver disease (CLD) controls from Huashan Hospital between January 2022 and December 2023.

Results

Using receiver operating characteristic curve analyses of the validation cohort, the GALAD algorithm had an area under the curve (AUC) value of 0.896 [95% confidence interval (CI) 0.873–0.919], while the AUC value was 0.894 [95% CI 0.870–0.918] for the ASAP algorithm. The ASAP algorithm for HBV-associated HCC detection had the highest AUC value (0.950; 95% CI 0.933–0.967), with a sensitivity of 89.3% and specificity of 81.6%.

Conclusions

Using the GALAD and ASAP algorithms to detect HCC displayed similar favorable accuracy. The ASAP algorithm was more reliable for the detection of HBV-associated HCC in Chinese patients.