GALAD Score for Hepatocellular Carcinoma Detection in Comparison with Liver Ultrasound and Proposal of GALADUS Score.

BACKGROUND: The GALAD score is a serum biomarker-based model that predicts the probability of having hepatocellular carcinoma (HCC) in patients with chronic liver disease. We aimed to assess the performance of the GALAD score in comparison with liver ultrasound for detection of HCC. METHODS: A single-center cohort of 111 HCC patients and 180 controls with cirrhosis or chronic hepatitis B and a multicenter cohort of 233 early HCC and 412 cirrhosis patients from the Early Detection Research Network (EDRN) phase II HCC Study were analyzed. RESULTS: The area under the ROC curve (AUC) of the GALAD score for HCC detection was 0.95 [95% confidence interval (CI), 0.93-97], which was higher than the AUC of ultrasound (0.82, P <0.01). At a cutoff of -0.76, the GALAD score had a sensitivity of 91% and a specificity of 85% for HCC detection. The AUC of the GALAD score for early-stage HCC detection remained high at 0.92 (95% CI, 0.88-0.96; cutoff -1.18, sensitivity 92%, specificity 79%). The AUC of the GALAD score for HCC detection was 0.88 (95% CI, 0.85-0.91) in the EDRN cohort. The combination of GALAD and ultrasound (GALADUS score) further improved the performance of the GALAD score in the single-center cohort, achieving an AUC of 0.98 (95% CI, 0.96-0.99; cutoff -0.18, sensitivity 95%, specificity 91%). CONCLUSIONS: The performance of the GALAD score was superior to ultrasound for HCC detection. The GALADUS score further enhanced the performance of the GALAD score. IMPACT: The GALAD score was validated in the United States.

Model combining pre-transplant tumor biomarkers and tumor size shows more utility in predicting hepatocellular carcinoma recurrence and survival than the BALAD models.

AIM: To assess the performance of BALAD, BALAD-2 and their component biomarkers in predicting outcome of hepatocellular carcinoma (HCC) patients after liver transplant. METHODS: BALAD score and BALAD-2 class are derived from bilirubin, albumin, alpha-fetoprotein (AFP), Lens culinaris agglutinin-reactive AFP (AFP-L3), and des-gamma-carboxyprothrombin (DCP). Pre-transplant AFP, AFP-L3 and DCP were measured in 113 patients transplanted for HCC from 2000 to 2008. Hazard ratios (HR) for recurrence and death were calculated. Univariate and multivariate regression analyses were conducted. C-statistics were used to compare biomarker-based to predictive models. RESULTS: During a median follow-up of 12.2 years, 38 patients recurred and 87 died. The HRs for recurrence in patients with elevated AFP, AFP-L3, and DCP defined by BALAD cut-off values were 2.42 (1.18-5.00), 1.86 (0.98-3.52), and 2.83 (1.42-5.61), respectively. For BALAD, the HRs for recurrence and death per unit increased score were 1.48 (1.15-1.91) and 1.59 (1.28-1.97). For BALAD-2, the HRs for recurrence and death per unit increased class were 1.45 (1.06-1.98) and 1.38 (1.09-1.76). For recurrence prediction, the combination of three biomarkers had the highest c-statistic of 0.66 vs. 0.64, 0.61, 0.53, and 0.53 for BALAD, BALAD-2, Milan, and UCSF, respectively. Similarly, for death prediction, the combination of three biomarkers had the highest c-statistic of 0.66 vs 0.65, 0.61, 0.52, and 0.50 for BALAD, BALAD-2, Milan, and UCSF. A new model combining biomarkers with tumor size at the time of transplant (S-LAD) demonstrated the highest predictive capability with c-statistics of 0.71 and 0.69 for recurrence and death. CONCLUSION: BALAD and BALAD-2 are valid in transplant HCC patients, but less predictive than the three biomarkers in combination or the three biomarkers in combination with maximal tumor diameter (S-LAD).

Combinations of biomarkers and Milan criteria for predicting hepatocellular carcinoma recurrence after liver transplantation.

Growing evidence suggests that pretransplant alpha-fetoprotein (AFP) predicts outcomes of hepatocellular carcinoma (HCC) patients treated with liver transplantation. We aimed to determine whether pretransplant AFP, Lens culinaris agglutinin-reactive alpha-fetoprotein (AFP-L3), and des-gamma-carboxyprothrombin (DCP) predicted HCC recurrence after transplantation. A retrospective cohort study of 313 HCC patients undergoing transplantation between 2000 and 2008 was conducted, and 48 (15.3%) developed recurrence during a median follow-up of 90.8 months. The 127 patients with available serum drawn before transplantation were included; they included 86 without recurrence and 41 with recurrence. Serum was tested for AFP, AFP-L3%, and DCP in a blinded fashion with the µTASWako i30 immunoanalyzer. All biomarkers were significantly associated with HCC recurrence. The hazard ratios (HRs) were 3.5 [95% confidence interval (CI), 1.9-6.7; P < 0.0001] for DCP ≥ 7.5 ng/mL and 2.8 (95% CI, 1.4-5.4; P = 0.002) for AFP ≥ 250 ng/mL. The HR increased to 5.2 (95% CI, 2.3-12.0; P < 0.0001) when AFP ≥ 250 ng/mL and DCP ≥7.5 ng/mL were considered together. When they were combined with the Milan criteria, the HR increased from 2.6 (95% CI, 1.4-4.7; P = 0.003) for outside the Milan criteria to 8.6 (95% CI, 3.0-24.6; P < 0.0001) for outside the Milan criteria and AFP ≥ 250 ng/mL and to 7.2 (95% CI, 2.8-18.1; P < 0.0001) for outside the Milan criteria and DCP ≥7.5 ng/mL. Our findings suggest that biomarkers are useful for predicting the risk of HCC recurrence after transplantation. Using both biomarkers and the Milan criteria may be better than using the Milan criteria alone in optimizing the decision of liver transplantation eligibility.

Quest for quality: department of laboratory medicine and pathology, Mayo Clinic.

This article describes our journey for quality in the Department of Laboratory Medicine and Pathology (DLMP) at Mayo Clinic. It provides the background of the department and the process for the development and implementation of the quality program. In addition, a quality conference and the development of a quality school are outlined. Throughout the course of this process, valuable lessons were learned and are discussed. We are pleased with the success of the quality journey. However, we realize that the quest has just begun. We look forward to the future and the challenges that lie ahead.