1. 39 DEVELOPED HCC by EASL criteria
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The GALAD model as a tool for HCC surveillance: a re-analysis of a prospective study
Philip J. Johnson1, Emily de Groot2, Hiroyuki Yamada3, Sarah Berhane1
1. Molecular & Clinical Cancer Medicine, University of Liverpool, & Clatterbridge Cancer Centre, Liverpool, United Kingdom.
2. University of St. Andrews, St. Andrews, United Kingdom.
3. Wako Life Sciences, Inc., Mountain View, CA, United States
INTRODUCTION
PATIENTS & METHODS 2
CONCLUSION
The serum-based tool (“GALAD”), for HCC diagnosis, is based on Gender, Age and 3 serological biomarkers, AFP, AFP-L3 and DCP1. The model was based on rigorous statistical analysis of a prospectively collected cohort.
It performs well irrespective of aetiology and tumour size (AUROC typically ) and has been extensively and internationally validated in more than 6000 patients2.
A prospective evaluation would support the model for use in clinical practice.
Between 2000 and 2004, before GALAD was developed, a prospective study of these three biomarkers was undertaken in North America but they were considered independently, not in a combinatory model such as GALAD3.
The GALAD score is validated in the US setting.
The GALAD score is already significantly raised among those destined to develop HCC at the start of the study, when there is no radiological evidence of HCC and rises steadily thereafter.
The GALAD score may offer an approach to risk stratification in the HCC surveillance setting.
Limitations
This study was not specifically designed to prospectively evaluate the GALAD score
The GALAD score was built on established HCC cases, a separate model may be needed for ‘pre-radiographic diagnosis’.
To visualize changes in biomarker levels over time (in observations taken at irregular time-points), we fitted a curve for each patient using fractional polynomial (FP) regression with GALAD, (or other variable of interest) as the dependent variable and “time to HCC diagnosis/last sample” as the explanatory variable. This allows values at various time points, up to two years prior to HCC diagnosis, to be interpolated and an aggregate curve thereby generated by calculating median value for all patients at that time point. 95% confidence intervals were generated by the bootstrap method.
Table 1: Baseline characteristics of the patients in each group (same groups as those underlined and in italics and yellow from the flow chart)
Variable
No HCC (n=330)
Developed HCCs (n=39)
Established HCCs (n=54)
Overall (n=423)
Gender (% male)
71.87, n=327
79.49, n=39
88.68, n=53
74.70, n=419
Age (years)
52 (47, 55), n=326
53 (49, 56), n=39
55 (51, 62), n=53
52 (48, 57), n=418
AFP (ng/ml)
5.8 (3.4, 12.3), n=328
13.2 (7.9, 37.3), n=39
35.9 (7.4, 217.2), n=54
6.9 (3.7, 19.4), n=421
L3 (%)
6.9 (0.5, 9.2), n=328
10.9 (7.3, 19.7), n=39
8.75 (4.6, 16.2), n=54
7.3 (0.5, 9.7), n=421
DCP (ng/ml)
0.44 (0.23, 1.12), n=329
2.17 (0.43, 6.87), n=36
5.93 (1.69, 18.19), n=51
0.54 (0.27, 2.75), n=416
GALAD
-2.38 (-3.53, -0.84), n=323
-0.44 (-1.37, 0.92), n=36
1.69 (-0.60, 4.06), n=50
-1.75 (-3.19, -0.20), n=409
Median (and interquartile range) presented for continuous variables. Percentages for categorical variables.
RESULTS
Taking the entire group of HCCs from the study (established HCC and developed HCC) the AUROC of the GALAD score was 0.86, significantly higher than the conventional marker of AFP (AUROC=0.79), p<0.01) (Figure 1).
On entry into the study, the GALAD score among those destined to develop HCC was already higher than those not developing HCC, median of vs (Table 1) and AUROC of 0.79 (Figure 2).
It rose steadily thereafter until diagnosis whereas the no HCC group remained low and did not change significantly (Figure 3).
The figures for positive and negative predictive values suggests that using the cut-off of -0.63, surveillance can be risk stratified. Those above having a 2 year risk of HCC of >20%, those below, 5% (Table 2).
AIM
ACKNOWLEDGEMENTS
To re-analyse a North American HCC surveillance dataset, and thereby:
Validate the GALAD model in a North American series.
Examine the extent to which the application of the GALAD model may permit detection of HCC prior to its detection within a conventional radiologically based surveillance program.
The authors wish to acknowledge the work of Sterling et al3 in terms of study design and data collection.
REFERENCES
1.Johnson et al, Cancer Epidemiol Biomarkers Prev Jan;23(1):144-53
2.Berhane et al., Clinical Gastroenterology and Hepatology 2016;14:875–886
3.Sterling RK et al., Clinical Gastroenterology and Hepatology 2009;7:104 –113
PATIENTS & METHODS 1
369 without HCC
Followed prospectively up to 2 years
39 DEVELOPED HCC by EASL criteria
(4.3% p.a.)
Biomarkers every 3-6 months,
Imaging 6-12 months
54 ESTABLISHED HCC
330 NO-HCC
423
Enrolled
HCV, cirrhotic
Log-rank tests:
GALAD vs AFP, p=0.0039
GALAD vs AFP-L3, p=0.0001
GALAD vs DCP, p=0.0089
Flow chart3
DISCLOSURES
Philip Johnson received an educational grant from Wako Life Sciences, Inc.
Figure 1: ROC curves comparing all HCCs vs no-HCC at diagnosis.
Receiver operating characteristic (ROC) curve were plotted to assess GALAD discrimination between the non-HCCs and all HCCs at diagnosis, and between non-HCCs and HCC developers at first and last observation.
Sensitivity, specificity, positive and negative predictive value for HCC development after passing GALAD cut-off of (based on previous publication1) within one and two years were calculated.
Figure 3: Serial changes in GALAD score, those developing HCC vs those not developing HCC
CONTACT INFORMATION
Table 2: Prediction of HCC development/detection within 1 and 2 years after crossing the GALAD boundary
Cut-off
Estimates
For HCC detection within 1 years
For HCC detection within 2 years
-0.63
Sensitivity (95% Ci)
0.59 (0.39, 0.76)
0.69 (0.52, 0.82)
Specificity (95% Ci)
0.71 (0.66, 0.76)
0.73 (0.68, 0.78)
Positive Predictive Value (95% Ci)
0.15 (0.09, 0.23)
0.23 (0.16, 0.32)
Negative Predictive Value (95% Ci)
0.95 (0.92, 0.97)
Correspondence to:
Philip Johnson
Department of Molecular and Clinical Cancer Medicine,
University of Liverpool, Liverpool L69 3GA, UK
Figure 2: ROC curves comparing HCC developers and non-HCCs at baseline (first) and diagnosis (last) for GALAD.