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Published on: May 8, 2018
National Liver Cancer Screening Trial (TRACER) study protocol.
Amit G Singal1, Neehar D Parikh2, Fasiha Kanwal3
1Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas, USA.
This trial compares ultrasound screening with biomarker GALAD for liver cancer detection in high-risk patients. GALAD may offer a more sensitive and effective approach to early hepatocellular carcinoma (HCC) diagnosis.
Area of Science:
- Hepatology
- Oncology
- Biomarker Discovery
Background:
- Current hepatocellular carcinoma (HCC) screening guidelines recommend ultrasound with or without alpha-fetoprotein (AFP), but face challenges with adherence and sensitivity.
- Blood-based biomarker panels, such as the GALAD score (including sex, age, AFP, AFP-L3, and des-carboxy prothrombin), show promise for improved HCC detection.
- Prospective validation of the GALAD panel in a large clinical utility trial is needed.
Purpose of the Study:
- To compare the effectiveness of ultrasound-based screening versus biomarker-based screening (GALAD) for early HCC detection.
- To evaluate the potential of the GALAD biomarker panel to improve HCC screening adherence and sensitivity.
- To inform clinical practice regarding optimal HCC screening strategies in patients with chronic liver diseases.
Main Methods:
- An adaptive pragmatic randomized phase IV trial (National Liver Cancer Screening Trial) enrolling 5500 patients with chronic hepatitis B or cirrhosis.
- Patients are randomized 1:1 to semi-annual screening with ultrasound ± AFP (arm A) or semi-annual screening with GALAD (arm B).
- Stratification by enrollment site, liver disease severity, etiology, and sex; primary endpoint is reduction in late-stage HCC.
Main Results:
- This section is not yet available as the trial is actively enrolling.
Conclusions:
- The trial's results will guide the optimal strategy for HCC screening and early detection.
- If the GALAD panel demonstrates superiority, it could lead to a shift from ultrasound-based screening to biomarker-based approaches for HCC.
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