Published Ahead of Print on December 15, 2014 as 10.1200/JCO.2014.57.9151
The latest version is at http://jco.ascopubs.org/cgi/doi/10.1200/JCO.2014.57.9151

JOURNAL OF CLINICAL ONCOLOGYO R I G I N A L

R E P O R T

Assessment of Liver Function in Patients With
Hepatocellular Carcinoma: A New Evidence-BasedApproach—The ALBI Grade
Philip J. Johnson, Sarah Berhane, Chiaki Kagebayashi, Shinji Satomura, Mabel Teng, Helen L. Reeves,
James O’Beirne, Richard Fox, Anna Skowronska, Daniel Palmer, Winnie Yeo, Frankie Mo, Paul Lai,
Mercedes Iñarrairaegui, Stephen L. Chan, Bruno Sangro, Rebecca Miksad, Toshifumi Tada, Takashi Kumada,and Hidenori Toyoda
See accompanying editorial doi: 10.1200/JCO.2014.59.0521
Author affiliations appear at the end of
this article.
Published online ahead of print at
www.jco.org on December 15, 2014.
Supported in part by National Cancer
Institute Grant No. K23CA139005(R.M.). B.S. acknowledges that Centro
de Investigación Biomédica en Red deEnfermedades Hepáticas y Digestivas
is funded by Instituto de Salud Carlos
III (Spain).
Authors’ disclosures of potential
conflicts of interest are found in thearticle online at www.jco.org. Author
contributions are found at the end of
this article.
Corresponding author: Philip J.
Johnson, MD, Department of Molecular
and Clinical Cancer Medicine, The
Duncan Building, Daulby St, Liverpool
L69 3BX, United Kingdom; e-mail:Philip.Johnson@liverpool.ac.uk.
© 2014 by American Society of ClinicalOncology
0732-183X/14/3299-1/$20.00
DOI: 10.1200/JCO.2014.57.9151

A

B

S

T

R

A

C

T

PurposeMost patients with hepatocellular carcinoma (HCC) have associated chronic liver disease, theseverity of which is currently assessed by the Child-Pugh (C-P) grade. In this international
collaboration, we identify objective measures of liver function/dysfunction that independently
influence survival in patients with HCC and then combine these into a model that could becompared with the conventional C-P grade.
Patients and Methods
We developed a simple model to assess liver function, based on 1,313 patients with HCC of all
stages from Japan, that involved only serum bilirubin and albumin levels. We then tested themodel using similar cohorts from other geographical regions (n ⫽ 5,097) and other clinicalsituations (patients undergoing resection [n ⫽ 525] or sorafenib treatment for advanced HCC [n ⫽1,132]). The specificity of the model for liver (dys)function was tested in patients with chronic liverdisease but without HCC (n ⫽ 501).
Results
The model, the Albumin-Bilirubin (ALBI) grade, performed at least as well as the C-P grade in all
geographic regions. The majority of patients with HCC had C-P grade A disease at presentation,
and within this C-P grade, ALBI revealed two classes with clearly different prognoses. Its utility inpatients with chronic liver disease alone supported the contention that the ALBI grade was indeed
an index of liver (dys)function.
Conclusion
The ALBI grade offers a simple, evidence-based, objective, and discriminatory method ofassessing liver function in HCC that has been extensively tested in an international setting. Thisnew model eliminates the need for subjective variables such as ascites and encephalopathy, arequirement in the conventional C-P grade.
J Clin Oncol 32. © 2014 by American Society of Clinical Oncology

INTRODUCTION

Most patients with hepatocellular carcinoma(HCC) have associated chronic liver disease,1 usually at the stage of cirrhosis in which HCC development is one of the main causes of liver-related
mortality.2 It is widely perceived that survival in
HCC depends on tumor stage, underlying liverfunction, and perhaps, performance status. Liverfunction is currently graded according to the ChildPugh (C-P) system, which was originally developed
to assess prognosis in patients with cirrhosis andportal hypertension undergoing surgery for variceal
bleeding.3,4 The C-P grade (which is based on a scorederived from five parameters including conventional liver function tests, extent of ascites, and degree of hepatic encephalopathy) has since become
widely used, sometimes with modification for different
etiologies, in all areas of chronic liver disease.5,6 Manyof its limitations have been described in detail.7
It is not clear that the C-P grade is appropriate
for assessing liver function/dysfunction in patientswith HCC. A variable percentage of patients with
HCC do not, in fact, have cirrhosis, but rather a© 2014 by American Society of Clinical Oncology

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Copyright 2014 by American Society of Clinical Oncology

1Johnson et alrange of liver pathology from mild abnormalities to advanced fibrosis,8 and the degree of liver (dys)function is likely related to the tumor
and the state of the nontumorous liver. In addition, some of thevariables considered in the C-P grade are interrelated (eg, ascites andserum albumin levels), and the grading of ascites and encephalopathy
can be highly subjective. For example, there are no clear guidelines for
distinguishing between mild and moderate ascites and/or the impact
of diuretic therapy on the scoring of this variable, and the impact of thetumor on the pathogenesis of the ascites is not clear. Finally, the C-P
grade does not offer a wide degree of discrimination among patients with
HCC, the majority of whom fall into the A grade.9 In all clinical studies of
HCC in which prognosis is considered, the level of liver (dys)function
clearly impacts on overall survival. For this reason, the C-P has been

widely used for stratification in clinical trials and staging systems, despite
thesystemhavingbeendevelopedarbitrarilybasedonclinicalobservation
several decades ago and without formal statistical grounding.10
The C-P grade relies on individual parameters that are scoredbased on arbitrarily defined, predetermined cutoff points. The loss of
information consequent on categorizing patients into distinct groups
has been shown. Dichotomization of continuous data in a multiple
regression procedure may be associated with considerable loss of statistical power and introduction of bias.11,12 The most noticeable impact lies in patients who fall around the cut point (ie, just below or
above the value used to define the two levels of the binary variable)
who may be classified as having different risk. In the case of the C-P
grade, for example, a score based on a serum bilirubin level of 50

Table 1. Characteristics of the Cohorts

Characteristic

Birmingham

Newcastle

Spain

Japan

China

United States

Cirrhotic
Patients(no HCC)

Total No. of patients
Accrual period
Race, %
White
Asian
Other
Age, years
Median
IQR
Mean
SD
Male
%
Total No. with data
Child-Pugh grade
Total No. with data
A
No.
%
B
No.
%
C
No.
%
Presence of macroscopic
vascular invasion%
Total No. with data
Bilirubin, ␮mol/L
MedianIQR
Total No. with data
Albumin, g/LMedianIQR
Total No. with data
Survival
Median, months
Total No. with data724
2007-2012

632
2000-2010

834
1994-2012

2,599
1994-2004

1,112
2003-2012

509
1996-2012
Not available

501
2006-2008
Not available

82.9

96.3

97.6
⬎ 95

⬎ 95

United Kingdom

Clinical
Trials
CohortPatients
Undergoing
Resection

1,132
2008-2011

525
1990-2012

24.4
66.1
8.5

⬎ 95

64.6
53.3-71.8
64
11

69
61-76
68
11

63.2
55.1-70.3
62.4
10.9

67
61-72
66.4
8.9

60
52-69
60.1
12.1

60.8
53.0-71
61.3
12.2

54
45-61
53.3
12.4

60
52-68
59
12.6

67
60-73
65.7
9.3

80.5
724

80.7
632

82.9
834

71.7
2,598

85.6
1,112

81.7
416

63.2
500

84.0
1,132

75.8
525

710

626

800

2,599

1,112

361

Not available

1,101

522

525
74

385
61.5

495
62

1,743
67

730
65

208
57.6

1,055
95.8

492
94.3

153
21

150
24.0

237
30

684
26

319
29

111
30.8

46
4.2

30
5.7

32
5

91
14.5

68
8

172
7

63
6

42
11.6

0
0

0
0

29.7
1,117

7.8
523

Not applicable
22.3
701

27.3
631

25.2
824

14.1
2,592

39.3
1,112

35.6
232

17
10-30
715

18
11-34
626

23.9
15.4-40.5
772

15.4
10.3-22.2
2,599

20
12-33
1,112

20.5
12.0-37.6
385

44
23-110501

15.4
10.3-20.5
1,077

12.0
8.6-15.4
523

39
34-43
716

36
31-40
623

36.3
31-41
675

35
31-39
2,599

37
32-40
1,112

35
30-40
376

31
27-35
501

39
35-42
1,074

39
36-42
522

18.8
716ⴱ

10.8
630

26.0
822

47.2
2,596

7.2
1,108

18.6†
505†

Not reached

9.2
1,084

106.8
519

Abbreviations: HCC, hepatocellular carcinoma; IQR, interquartile range; SD, standard deviation.
ⴱOverall medial survival time in the United Kingdom and Spain cohorts was 17.8 months (n ⫽ 2,168); the median survival excluding those undergoing transplantation
was 14.3 months (n ⫽ 1,876).
†Excluding those undergoing transplantation, the equivalent figure in the US cohort was 14.4 months (n ⫽ 442).

2© 2014 by American Society of Clinical Oncology

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Liver Function in Patients With HCC

Table 2. Multivariable Cox Regression Analysis Using Stepwise Forward Selection of Variables (Japanese training set)
Variable
Whole cohort
Macroscopic vascular invasion
Albumin (g/L)
Tumor size (cm)Log10 bilirubin
Tumor number
Age
Sex (male)
ALBI model parameters (based on theJapanese training set)
Log10 bilirubin
Albumin (g/L)

HR

SE

z

P⬎z

95% CI of HR

2.79
0.91
1.10
2.13
1.11
1.01
1.30

0.46
0.0093
0.021
0.46
0.035
0.0062
0.147

6.19
⫺8.81
5.01
3.51
3.34
2.17
2.34

⬍ .001⬍ .001⬍ .001⬍ .001
.001
.030
.019

2.02 to 3.86
0.90 to 0.93
1.06 to 1.14
1.40 to 3.26
1.04 to 1.18
1.00 to 1.03
1.04 to 1.62

1.94
0.92

0.37
0.0080

3.49⫺9.84⬍ .001⬍ .0011.34 to 2.82
0.90 to 0.93

Coefficient

SE

z

P⬎z

95% CI of Coefficient

0.66⫺0.0850.19
0.0087

3.49⫺9.84⬍ .001⬍ .0010.29 to 1.04
⫺0.10 to ⫺0.068

Abbreviations: ALBI, Albumin-Bilirubin; HR, hazard ratio.

␮mol/L has the same impact as one with a value of 500 ␮mol/L.
Similarly, a serum albumin of 27 g/L has the same impact as a serum
albumin of 10 g/L, and within C-P grade A, a patient with a serum
bilirubin level of less than 5 ␮mol/L may have significantly better
hepatic reserve than a patient with a serum bilirubin of 33 ␮mol/L andyet both will be scored the same within the C-P system.

In this study, we have used data from large international databases to identify objective measures of liver dys(function) that independently influence survival in patients with HCC (albumin andbilirubin) and then combined them into a model that could becompared with the conventional C-P grade. This resultant model,
called the Albumin-Bilirubin (ALBI) score, eliminates the need for

A

B

ALBI
Median survival,
gradenmonths (95% CI)
1
65085.6 (63.6 to )2
1,699
46.5 (43.3 to 49.5)
3
247
15.5 (11.6 to 17.8)
Harrell’s C and Somers’s D: 0.61 and 0.23

1.0

1.0

0.8

Survival(probability)

Survival(probability)

0.8

0.6

0.4

0.2

0

0.6

0.4

0.2

20

40

60

0

Time (months)
1.0

ALBI
Median survival,
gradenmonths (95% CI)
1591
24.7 (22.5 to 28.3)
2915
11.4 (10.1 to 12.6)3199
4.9 (4.1 to 6.7)
Harrell’s C and Somers’s D: 0.62 and 0.24

Survival(probability)

0.8

0.6

0.4

0.2

0

20

40

60

Time (months)

D

1.0Child-PughMedian survival,
gradenmonths (95% CI)
A
1,227 19.7 (18.2 to 21.9)B447
7.7 (7.01 to 8.9)C149
4.2 (3.03 to 5.2)
Harrell’s C and Somers’s D: 0.62 and 0.23

0.8

Survival(probability)

C

Child-PughMedian survival,
gradenmonths (95% CI)
A
1,741 63.6 (55.8 to 70.7)
B684 29.9 (26.9 to 32.6)
C
171 14.8 (11.1 to 17.5)
Harrell’s C and Somers’s D: 0.63 and 0.27

0.6

0.4

0.2

20

40

Time (months)

60

0

20

40

60

Time (months)

Fig 1. Application of the Albumin-Bilirubin (ALBI) model and comparison with Child-Pugh (C-P) grade. Kaplan-Meier curves depict survival according to (A, C, E, and
G) ALBI and (B, D, F, and H) C-P class in (A and B) Japanese, (C and D) European, (E and F) Chinese, and (G and H) US cohorts. Associated tables display the mediansurvival (in months) for each curve as well as Harrell’s C and Somers’ D scores.
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Johnson et al

1.0

ALBI
Median survival,
gradenmonths (95% CI)
1324
18.5 (14.7 to 22.1)
2643
5.3 (4.5 to 6.1)3141
2.3 (1.7 to 3.8)
Harrell’s C and Somers’s D: 0.62 and 0.24

Survival(probability)

0.8

F

1.0

0.6

0.4

0.2

0

0.6

0.4

0.2

20

40

60

0

Time (months)
1.0

ALBI
Median survival,
gradenmonths (95% CI)1
82
19.1 (15.7 to 29.4)
2
167
11.6 (8.8 to 16.7)
370
4.2 (1.9 to 6.2)
Harrell’s C and Somers’s D: 0.64 and 0.29

Survival(probability)

0.8

0.6

0.4

H

1.0

40

60

Child-PughMedian survival,
gradenmonths (95% CI)
A
175 21.1 (16.4 to 30.6)B96
6.8 (4.1 to 8.7)C
37
2.2 (0.8 to 4.3)
Harrell’s C and Somers’s D: 0.68 and 0.36

0.8

0.2

0

20

Time (months)

Survival(probability)

G

Child-PughMedian survival,
gradenmonths (95% CI)
A
728 11.5 (10.0 to 13.0)B318
3.0 (2.6 to 3.8)C62
1.4 (0.8 to 2.0)
Harrell’s C and Somers’s D: 0.62 and 0.24

0.8

Survival(probability)

E

0.6

0.4

0.2

20

40

60

0

Time (months)

20

40

60

Time (months)
Fig 1. (Continued).

subjective variables such as ascites and encephalopathy, a requirement in the C-P grade.
PATIENTS AND METHODS
We accrued data from major HCC centers and from international HCC
clinical trials (Table 1). The centers were chosen to ensure the inclusion ofpatients of all disease stages and representative of a broad range of etiologies
and geographical regions. The patients from clinical trials all had advanced
disease and were treated with the current standard of care, sorafenib. The HCC
centers comprised two centers from high HCC incidence areas, Japan andHong Kong (predominant etiologies, chronic hepatitis C virus [HCV] andhepatitis B virus infection, respectively); two from medium-incidence areas,
Spain and the United States (predominant etiologies, alcohol and HCV); andthe remainder from a low-incidence area, the United Kingdom (mixed etiologies). The United Kingdom and Spanish data were merged into a single
European cohort. A cohort of patients with cirrhosis alone was recruited fromthe Royal Free London National Health Service (NHS) Foundation Trust in
London, United Kingdom.
Survival was measured from the date of diagnosis (first presentation with
HCC) to date of death or last follow-up. All parameters investigated in theanalysis were measured before any treatment and within 6 weeks of diagnosis.
In the case of the clinical trials, survival was measured from the date of random
assignment. All statistical analysis was undertaken in the United Kingdom. Nochanges were made to the data presented by the individual centers before theanalysis, and the C-P grade for individual patients was, similarly, classified by
the investigators at each site before analysis.
4© 2014 by American Society of Clinical Oncology

Centers
Japan. The Japanese data set (from the Ogaki prefecture) comprised
2,599 patients previously reported by Toyoda et al13 who were recruited fromfive institutions in the western part of Japan; the etiology was predominantly
HCV. In this area of Japan, cirrhotic patients and noncirrhotic patients withsevere fibrosis undergo rigorous screening for HCC every 6 months withultrasound examinations and serum biomarkers, supported, when appropriate, by computed tomography or dynamic magnetic resonance imaging.14
China. This cohort comprised consecutive patients attending the multidisciplinary Joint Hepatoma Clinic at the Prince of Wales Hospital, HongKong.15 As the primary referral clinic for HCC in the New Territories Eastof Hong Kong, the Prince of Wales Hospital serves a population of approximately two million; the etiology was predominantly hepatitis B virus.
There was no formal HCC screening program in place over the period of
this study.
Europe. This cohort comprises patients from Spain and the United
Kingdom. Spanish patients were diagnosed at, or referred to, the Clinica
Universidad de Navarra, Pamplona; the etiology was predominantly HCV oralcohol abuse. United Kingdom patients were those referred to the Queen
Elizabeth Hospital, Birmingham, or Newcastle Hospitals NHS Foundation
Trust16; these patients had various etiologies. Patients undergoing liver transplantation (n ⫽ 125 and n ⫽ 168 in Spain and United Kingdom, respectively)
were excluded from the analysis.
United States. The US cohort was drawn from an institutional databaseof patients with HCC seen at Beth Israel Deaconess Medical Center in Boston,
Massachusetts. The underlying etiology was predominantly HCV or alcoholabuse. Patients undergoing liver transplantation (n ⫽ 63) were excluded fromthe analysis.
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Liver Function in Patients With HCC

Patients Entered Onto Clinical Trials
We had access to a data set including 1,132 patients receiving sorafenib
for unresectable advanced HCC within the control groups of two international
clinical trials.17,18 Of the 1,028 patients with complete data, 96% were classified
as C-P grade A. The inclusion criteria are given in the published reports.17,18
Patients With Cirrhosis Alone
This cohort comprised 501 consecutive patients with cirrhosis but no
HCC admitted to the Royal Free London NHS Foundation Trust for management of complications and/or assessment of liver disease. The intent of thiscohort is to provide evidence that the ALBI model is an actual measure of liverfunction, rather than, in some surrogate manner, a measure of tumor stage.

size, log10 bilirubin, tumor number, age, and sex were statisticallysignificant prognostic variables (Table 2). When we eliminated theimpact of the HCC itself (as measured by tumor size or TMN stage),
we discovered that log10 bilirubin and albumin were consistently statistically significant predictors of survival (Appendix Table A2). Although vascular invasion and tumor number had, as expected, an
impact on survival in most of the strata, we confined our model toalbumin and bilirubin because these, alone, were related to liver function. A Cox regression model based on albumin and log10 bilirubin

A

RESULTSJapanese patients had the highest median survival at 47.2 months,
followed by the United States, Europe, and China at 18.6, 17.8, and 7.2
months (including patients undergoing liver transplantation), respectively (Table 1 and Appendix Fig A1, online only). Univariable Cox
regression analysis on the Japanese cohort showed that sex (male),log10 bilirubin, albumin, tumor size, tumor number, presence of vascular invasion, and TNM stage were statistically significant prognostic
variables (Appendix Table A1, online only). Results of the multivariable Cox regression analysis within each disease stage substrata areshown in Appendix Table A2 (online only).
Multivariable Cox regression (with forward selection) on theJapanese training set showed that vascular invasion, albumin, tumor
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Survival(probability)

0.6

0.4

0.2

0

ALBI
grade
n
1
640
2
1,099
3
2

Median survival,
months (95% CI)
85.6 (63.6 to )54.8 (50.2 to 64.3)
73.1 (na)

20

40

60

Time (months)

B

1.0

ALBI
grade
1
2
3

0.8

Survival(probability)

Statistical Methods
All statistical analysis was undertaken using Stata IC 12 (Stata, College
Station, TX). To identify prognostic factors for the future model, exploratory
univariable and multivariable Cox regression analyses were undertaken on theentire Japanese cohort because this was the largest and most complete data set.
To isolate the impact of liver function on survival (as distinct from that of HCC
per se), multivariable Cox regression (with stepwise forward selection) withineach disease stage substrata was used to identify predictive patient characteristics common to all strata. Disease stage was described according to tumor size(⬍ 3, 3 to 5, 5.1 to 10, and ⬎ 10 cm) or the TNM stage classification of the Liver
Cancer Study Group of Japan (stages I to IV).19 The entire Japanese cohort(n ⫽ 2,599) was then randomly split into two groups, the training (n ⫽ 1,313)
and validation sets (n ⫽ 1,286).
Cox regression analysis was performed on the Japanese training set toderive a model. By splitting its linear predictor (xb) at the 25th and 90th
percentiles, three groups, according to survival, were generated. Using thisclassification, patients with HCC were assigned as low, medium, or high risk,
describing the lowest 25% of risk, medium risk between the 25th and 90th
percentile, and the highest 10% of risk, respectively. Evidence of deviationfrom proportional hazards assumption was assessed using Stata’s phtest andthrough visual assessment of log-log survival plots.
The discriminatory performance of the ALBI model and C-P grade wascalculated and compared using Harrell’s C and Somers’ D statistics20-22 andalso assessed visually via Kaplan-Meier (KM) plots for each of the Japanesetraining and validation sets and for the European, Chinese, and US cohorts.
Because patients with HCC predominantly fell into C-P grade A, weused KM plots to investigate the utility of the ALBI grade to detect variationin survival within this C-P grade. The ALBI grade was also applied topatients with advanced disease who received sorafenib and to cirrhotic
patients without HCC.

1.0

0.8

Median survival,
months (95% CI)
24.5 (22.2 to 28.3)
14.7 (13.7 to 16.8)
4.7 (0.2 to )

n
622
657
5

0.6

0.4

0.2

0

20

40

60

Time (months)

C

1.0

ALBI
grade
1
2
3

0.8

Survival(probability)

Patients Undergoing Resection
This cohort consisted of 525 Japanese patients from five institutions in
the western part of Japan who had undergone HCC resection between 1990
and 2012.

Median survival,
months (95% CI)
20.03 (17.4 to 24.9)
8.1 (6.5 to 9.6)
7.9 (3.6 to 12.2)

n
303
398
27

0.6

0.4

0.2

0

20

40

60

Time (months)
Fig 2. Performance of the Albumin-Bilirubin (ALBI) model in patients with
hepatocellular carcinoma with Child-Pugh (C-P) grade A. Kaplan-Meier curves
depict survival according to ALBI grades within C-P grade A patients of the (A)Japanese, (B) European/US, and (C) Chinese cohorts. Associated tables display
the median survival (in months) for each curve.

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Johnson et al

was built on the Japanese training set. The parameters of this model
are shown in Table 2; the equation for the linear predictor was asfollows: linear predictor ⫽ (log10 bilirubin ⫻ 0.66) ⫹ (albumin ⫻⫺0.085), where bilirubin is in ␮mol/L and albumin in g/L.
Calculating the patient-level linear prediction (xb) and applying
the cut points assigned each patient to one of three prognostic groups,
now named the ALBI grade, 1 to 3. The cut points were as follows: xb
ⱕ ⫺2.60 (ALBI grade 1), more than ⫺2.60 to ⱕ ⫺1.39 (ALBI grade2), and xb more than ⫺1.39 (ALBI grade 3).
The ALBI model was applied to the training and validation sets of
the Japanese cohort and compared with C-P grade for the same data
sets (Appendix Fig A2, online only). Visual inspection of the resulting
KM curves showed equally good discrimination between the three
ALBI prognostic groups and the C-P grade. This is reflected by theHarrell’s C and Somers’ D scores, which were similar.
Applying the model to the other cohorts, visual inspection of thecurves again indicated that the discrimination between the three ALBI
groups was as good as that of the C-P grade (Figs 1A to 1H). This isreflected in the Harrell’s C and Somers’ D scores (Figs 1A to 1H). KM
curves showing the ALBI breakdown of C-P grade A patients in theJapanese, European, and US and Chinese cohorts are shown in Figures
2A to 2C and reveal two distinct prognostic groups (mainly fallingunder ALBI grade 1 or 2).

For C-P grade A patients receiving sorafenib for advanced disease, two clear and nonoverlapping groups were again revealed (Fig
3A). In patients with cirrhosis alone, the ALBI grade revealed three
distinct prognostic groups (Fig 3B). In patients undergoing resection,
two clear prognostic groups (ALBI grades 1 and 2) were again observed (Fig 3C), whereas for the same cohort, the C-P grades (A and B)
overlapped (Fig 3D).
A nomogram that permits calculation of ALBI score directlyfrom serum bilirubin and albumin values in the clinical setting wasconstructed (Fig 4). An equivalent heat map is also shown in Appendix
Figure A3 (online only). There was no evidence to indicate that the
ALBI score deviated from the proportional hazards assumption.

A

B

1.0

Our data show that a simple evidence-based model incorporating only
serum bilirubin and serum albumin concentrations can stratify patients with HCC into three risk categories. Both formal statisticalanalysis and visual inspection suggest that the degree of discrimination
obtained is at least as good as that achieved by the conventional C-P
grade. Across the entire database of 3,887 patients classified as C-P
grade A, two distinct prognostic groups could be identified in all

ALBI
Median survival,
gradenmonths (95% CI)1
475 12.7 (11.7 to 14.9)2542
7.2 (6.4 to 8.2)3
11
3.6 (1.6 to 4.9)
All sorafenib 1,028
9.3 (8.5 to 10.5)
treated

0.6

1.0

0.8

Survival(probability)

0.8

Survival(probability)

DISCUSSION

0.4

0.2

10

0

20

30

40

0.6

0.4

0.2

ALBI
Median survival,
grade n months (95% CI)
1
29
Not reached2
146
Not reached3
144
Not reached

010Time (months)

C

D

0.8

Survival(probability)

Survival(probability)

30

1.0

0.8

0.6

0.4

0

20

Time (months)

1.0

0.2

75% survival,
1-yearmonths (95% CI) survival (%)
No deaths
100
19.5 (9.8 to 24.3)
81.9
1.7 (0.9 to 6.1)
62.9

ALBI
grade
1
2

20

n
290
226

Median survival,
months (95% CI)
135.6 (108 to 186)
81.6 (63.6 to 98.4)

40

60

Time (months)

80

100

0.6

0.4

0.2

Child-Pugh
grade
n
A
488
B
30

0

20

Median survival,
months (95% CI)
106.8 (96 to 132)
98.4 (46.8 to 114)

40

60

80

100

Time (months)

Fig 3. Performance of the Albumin-Bilirubin (ALBI) model in patients undergoing sorafenib treatment, those undergoing resection, and those with cirrhosis (without
hepatocellular carcinoma). Kaplan-Meier curves illustrate survival according to ALBI grades in patients (A) treated with sorafenib as part of a clinical trial, (B) with cirrhosis
alone, and (C) undergoing resection. (D) Corresponding Child-Pugh grades for the resected patients shown in (C). Associated tables display the median survival (inmonths) for each curve.
6© 2014 by American Society of Clinical Oncology

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Liver Function in Patients With HCC

5

10

ALBI
15
0.5

(A3)

0
20

100
90
80
70
60
50
40

−0.5

55
45

−1

25

35

30

10

9
8
7
6
5
4

−1.5

(A2)

−2

Albumin (g/L)

15

Bilirubin (µmol/L)

25

20

30

−2.5
3

35

2

−3
1

−3.5

40

(A1)

−4

−4.5

45

50

55
Fig 4. Nomogram for rapid assessment of the Albumin-Bilirubin (ALBI) score.
Colors refer to ALBI grades A1, A2, and A3.

www.jco.org

regions. In Europe and the United States, for example, when C-P
grade A patients were reclassified into ALBI grade 1 or 2, there was a
10-month difference in survival between the two ALBI grades. Our
analysis has focused on the impact of liver function on survival, andnot on liver disease–related events or deaths, because in practice, it isdifficult to specifically attribute the cause of death to the HCC or theunderlying liver disease.
Assessment of liver function is particularly important in clinical
trials because it is perceived that cirrhosis is a competing cause ofdeath. To isolate the impact of a specific HCC treatment on survival,
many HCC treatment studies are limited to patients with C-P grade A.
However, our findings suggest that not all C-P grade A patients are thesame and that this heterogeneity may have an impact on survival
findings. Among C-P grade A patients in clinical trials who received
the standard care, sorafenib, the model distinguishes between a goodrisk group (ALBI grade 1) and a relatively poorer risk group (ALBI
grade 2), with a median survival difference of nearly 6 months. Suchrefinement of liver function assessment might permit retrospective
assessment of sorafenib efficacy and survival in these subgroups
and determine the most appropriate group for this type of treatment in the future.
One of the strengths of this study is the large number of patientsand the generalizability of the results because we have consideredhigh-, medium-, and low-incidence HCC areas and a broad spectrumof etiologies. We specifically excluded patients who underwent livertransplantation because, in these patients, underlying (dys)function iseffectively abrogated by the procedure.
The fact that both serum bilirubin and albumin are part of thebattery of tests widely referred to as liver function tests suggests that
our model is, indeed, measuring liver function, a contention that is
supported by our demonstration that the model showed discrimination in patients with uncomplicated cirrhosis. We have examined thisgroup specifically for the aforementioned reason, not to suggest that it
would have a role outside the area of HCC and chronic liver disease.
Interestingly, in a systematic review of prognostic indicators in cirrhosis, serum albumin and bilirubin were the two most prominent individual prognostic variables in good studies.23
It might seem surprising that survival in particular ALBI stages
varied across geographical regions, but overall median survival is different across geographical regions and the variation is just as striking in
the case of the C-P grades. This may be partly attributable to lead-timebias because it is likely that some countries where extensive publichealth measures have been implemented, such as Japan, will haveapparent survival times greater than those seen in countries such as
Hong Kong, where there is less access to primary care. Using sophisticated approaches, our model could be recalibrated for each region, as
we have previously shown.24
We have previously reported and validated13,24 an objective
serology-based model for survival prediction in HCC. This model,
known as BALAD-2, combines bilirubin and albumin with threeserum biomarkers (␣-fetoprotein [AFP], AFP-L3%, and DCP). This
study adds to the plausibility of the BALAD-2 model because bilirubin
and albumin seem to represent the impact of the underlying liverfunction on survival (as shown here), whereas the three biomarkers
may represent the impact of the tumor itself on survival.
The Model for End-Stage Liver Disease score might be considered an alternative to C-P grade. However, this system is specificallydesigned for patients with end-stage cirrhosis,25-28 and as shown here,© 2014 by American Society of Clinical Oncology

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7

Johnson et al

this is not the case in most patients with HCC. Furthermore, serum
creatinine is one of the parameters in the Model for End-Stage Liver
Disease score and may be less reliable in patients with cancer becauseof cancer-related cachexia (creatinine levels are related to musclemass).29 Although the performance of ALBI is similar to that of C-P,
the fact that it is evidence based, much simpler (using the proposed
nomogram or heat map), and entirely objective will make it easier toimplement. Furthermore, relying on fewer variables, it may be more
readily applicable in large-scale international studies. For example, ina recent US study based on the GIDEON registry (a global, prospective, noninterventional study of patients with unresectable HCC undergoing sorafenib treatment),30 27% of patients were not evaluable
for C-P assessment, largely because of missing international normalized ratio values (a constituent of the C-P grade). A limitation of thisstudy is that we did not have access to the C-P score, only the C-P
grade, as classified by investigators at the individual centers. Hence, we
can draw no conclusions as to the performance of the ALBI system in
relation to specific C-P scores, for example, C-P score 5 to 6.
The ALBI approach will avoid interobserver variation and may
highlight distinct prognostic subgroups within C-P grade A. All theseadvantages are important considerations in the clinical trial setting.
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AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS
OF INTEREST
Disclosures provided by the authors are available with this article atwww.jco.org.

AUTHOR CONTRIBUTIONS
Conception and design: Philip J. Johnson
Provision of study materials or patients: Philip J. Johnson, Sarah
Berhane, Chiaki Kagebayashi, Mabel Teng, Helen L. Reeves, James
O’Beirne, Anna Skowronska, Winnie Yeo, Frankie Mo, Paul Lai,
Mercedes Iñarrairaegui, Stephen L. Chan, Bruno Sangro, Rebecca
Miksad, Toshifumi Tada, Takashi Kumada, Hidenori Toyoda
Collection and assembly of data: Philip J. Johnson, Sarah Berhane,
Chiaki Kagebayashi, Mabel Teng, Helen L. Reeves, James O’Beirne, Anna
Skowronska, Daniel Palmer, Winnie Yeo, Frankie Mo, Paul Lai,
Mercedes Iñarrairaegui, Stephen L. Chan, Bruno Sangro, Rebecca
Miksad, Toshifumi Tada, Takashi Kumada, Hidenori Toyoda
Data analysis and interpretation: Philip J. Johnson, Sarah Berhane,
Shinji Satomura, Richard Fox, Daniel Palmer, Rebecca Miksad
Manuscript writing: All authors
Final approval of manuscript: All authors

11. Del Priore G, Zandieh P, Lee MJ: Treatment ofcontinuous data as categoric variables in obstetrics
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12. Royston P, Altman DG, Sauerbrei W: Dichotomizing continuous predictors in multiple regression: A bad idea. Stat Med 25:127-141, 2006
13. Toyoda H, Kumada T, Osaki Y, et al: Staging
hepatocellular carcinoma by a novel scoring system(BALAD score) based on serum markers. Clin Gastroenterol Hepatol 4:1528-1536, 2006
14. Toyoda H, Kumada T, Kiriyama S, et al: Impact
of surveillance on survival of patients with initialhepatocellular carcinoma: A study from Japan. Clin
Gastroenterol Hepatol 4:1170-1176, 2006
15. Chan SL, Mo FK, Johnson PJ, et al: Prospective validation of the Chinese University Prognostic
Index and comparison with other staging systems
for hepatocellular carcinoma in an Asian population.
J Gastroenterol Hepatol 26:340-347, 201116. Dyson J, Jaques B, Chattopadyhay D, et al:
Hepatocellular cancer: The impact of obesity, type 2
diabetes and a multidisciplinary team. J Hepatol
60:110-117, 201417. Johnson PJ, Qin S, Park JW, et al: Brivanib
versus sorafenib as first-line therapy in patients withunresectable, advanced hepatocellular carcinoma:
Results from the randomized phase III BRISK-FL
study. J Clin Oncol 31:3517-3524, 2013
18. Cheng AL, Kang YK, Lin DY, et al: Sunitinib
versus sorafenib in advanced hepatocellular cancer:
Results of a randomized phase III trial. J Clin Oncol
31:4067-4075, 2013
19. Liver Cancer Study Group of Japan: The General Rules for the Clinical and Pathological Study ofPrimary Liver Cancer (English ed). Tokyo, Japan,
Kanehara & Co, 2003
20. Taktak A, Eleuteri A, Lake S, et al: Evaluationof prognostic models: Discrimination and calibration
performance. Comput Intell Med 2007

21. Newson R: Confidence intervals for rank statistics: Somers’ D and extensions. Stata J 6:309, 2006
22. Newson RB: Comparing the predictive powers of survival models using Harrell’s C or Somers’
D. Stata J 10:339, 2010
23. D’Amico G, Garcia-Tsao G, Pagliaro L: Natural
history and prognostic indicators of survival in cirrhosis: A systematic review of 118 studies. J Hepatol
44:217-231, 2006
24. Fox R, Berhane S, Teng M, et al: Biomarkerbased prognosis in hepatocellular carcinoma: Validation and extension of the BALAD model. Br J Cancer
110:2090-2098, 2014
25. Durand F, Valla D: Assessment of the prognosis of cirrhosis: Child-Pugh versus MELD. J Hepatol
42:S100-S107, 2005 (suppl)
26. Botta F, Giannini E, Romagnoli P, et al: MELD
scoring system is useful for predicting prognosis inpatients with liver cirrhosis and is correlated withresidual liver function: A European study. Gut 52:
134-139, 2003
27. Bruix J, Sherman M, American Association for
the Study of Liver Diseases: Management of hepatocellular carcinoma: An update. Hepatology 53:
1020-1022, 201128. Bruix J, Sherman M, Practice Guidelines
Committee, American Association for the Study ofLiver Diseases: Management of hepatocellular carcinoma. Hepatology 42:1208-1236, 2005
29. Nankivell BJ: Creatinine clearance and theassessment of renal function. Aust Prescr 24:15-17,
2001
30. Miksad RA, Cohn AL, El-Khoueiry AB, et al:Use of staging and scoring systems in hepatocellular carcinoma (HCC): Lessons from U.S. regional
analysis of the GIDEON registry. J Clin Oncol 32,
2014 (suppl 3; abstr 323)

Affiliations
Philip J. Johnson, Sarah Berhane, and Daniel Palmer, University of Liverpool, Liverpool; Philip J. Johnson and Daniel Palmer, The
Clatterbridge Cancer Centre National Health Service (NHS) Foundation Trust, Bebington; Mabel Teng, Addenbrooke’s Hospital, Universityof Cambridge, Cambridge; Helen L. Reeves, Northern Institute for Cancer Research and the Hepatopancreatobiliary Multidisciplinary Team,8© 2014 by American Society of Clinical Oncology

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Liver Function in Patients With HCC

Newcastle upon Tyne NHS Foundation Trust, The Freeman Hospital, Newcastle upon Tyne; James O’Beirne, The Sheila Sherlock Liver
Centre, Royal Free Hospital, London; Richard Fox and Anna Skowronska, School of Cancer Sciences, University of Birmingham,
Birmingham, United Kingdom; Chiaki Kagebayashi and Shinji Satomura, Wako Life Sciences, Mountain View, CA; Rebecca Miksad, BethIsrael Deaconess Medical Center, Institute for Technology Assessment, Massachusetts General Hospital, and Harvard Medical School, Boston,
MA; Winnie Yeo, Frankie Mo, and Stephen L. Chan, State Key Laboratory in Oncology in South China, Sir Y. K. Pao Centre for Cancer,
Chinese University of Hong Kong, Hong Kong Cancer Institute; Paul Lai, Prince of Wales Hospital, Chinese University of Hong Kong, Hong
Kong, China; Mercedes Iñarrairaegui and Bruno Sangro, Clinica Universidad de Navarra, and Centro de Investigacion Biomedica en Red deEnfermedades Hepaticas y Digestivas, Pamplona, Spain; Toshifumi Tada, Takashi Kumada, and Hidenori Toyoda, Ogaki Municipal Hospital,
Ogaki, Gifu, Japan.
■ ■ ■www.jco.org© 2014 by American Society of Clinical Oncology

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Johnson et al

AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

Assessment of Liver Function in Patients With Hepatocellular Carcinoma: A New Evidence-Based Approach—The ALBI Grade
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are
self-held unless noted. I ⫽ Immediate Family Member, Inst ⫽ My Institution. Relationships may not relate to the subject matter of this manuscript. For more
information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or jco.ascopubs.org/site/ifc.
Philip J. Johnson
Honoraria: Bayer
Consulting or Advisory Role: Astellas
Travel, Accommodations, Expenses: Bayer, Wako Life Sciences
Sarah Berhane
No relationship to disclose
Chiaki Kagebayashi
Employment: Wako Life Sciences
Shinji Satomura
Employment: Wako Life Sciences
Mabel Teng
No relationship to disclose
Helen L. Reeves
No relationship to disclose
James O’Beirne
Speakers’ Bureau: Gilead Sciences
Travel, Accommodations, Expenses: Bristol-Myers Squibb
Richard Fox
No relationship to disclose
Anna Skowronska
No relationship to disclose
Daniel Palmer
Honoraria: Bayer, Celgene, Astellas Pharma
Consulting or Advisory Role: Bayer, Celgene, Astellas PharmaFrankie Mo
No relationship to disclose
Paul Lai
Consulting or Advisory Role: Novartis
Mercedes Iñarrairaegui
No relationship to disclose
Stephen L. Chan
No relationship to disclose
Bruno Sangro
Consulting or Advisory Role: Bayer Schering Pharma, Sirtex Medical,
MedImmune, Bristol-Myers Squibb, Transgene, Guerbet
Speakers’ Bureau: Bayer Schering Pharma, Sirtex Medical
Travel, Accommodations, Expenses: Bayer Schering Pharma, Sirtex
Medical, Gilead Sciences
Rebecca Miksad
Consulting or Advisory Role: Optum Insight, Acceleron Pharma, Onyx
Research Funding: Bayer/Onyx (Inst), NewLink (Inst), Genentech(Inst), Daiichi Sankyo (Inst), ArQule (Inst), Acceleron Pharma (Inst)Toshifumi Tada
No relationship to disclose
Takashi Kumada
No relationship to disclose
Hidenori Toyoda
No relationship to disclose

Winnie Yeo
Honoraria: Roche
Consulting or Advisory Role: Novartis, GlaxoSmithKline, Boehringer
Ingelheim, Eisai, Pfizer© 2014 by American Society of Clinical Oncology

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Liver Function in Patients With HCC

Acknowledgment
We gratefully acknowledge the help of all those who contributed to the collection of the data sets used in this study. From Hong Kong, JaneKoh played a major role in data collection and tabulation, and similar roles were fulfilled by Sara Carrillo and Janet Morse in Pamplona andBirmingham, respectively. The US data abstraction team included Atinuke Babalola, Ugonna Nwosu, Olubunmi Oladunjoye, and Bethany
Burns. We also thank all those who played roles in managing the patients in this study, including the Newcastle upon Tyne Hospitals National
Health Service Foundation Trust and the Queen Elizabeth Hospital University Trust multidisciplinary teams. Additional support for datacollection and analysis came from the Biomedical Research Unit at the University of Birmingham and Liverpool Health Partners. Finally, we areindebted to Pfizer and Bristol-Myers Squibb who generously gave us access to data from studies in which they acted as sponsor.
Appendix

Table A1. Univariable Analysis of Whole Japan Cohort
Variable

HR

SE

z

P⬎z

95% CI of HR

Sex (male)
Age
Log10 bilirubin
INR
Albumin
Tumor size, cm
Tumor number
Macroscopic vascular invasion
TNM stage
I
II
III
IV

1.21
1.00
4.91
1.09
0.91
1.14
1.32
5.40

0.085
0.00360.59
0.055
0.00520.0091
0.029
0.41

2.70
0.17
13.25
1.67
⫺17.39
16.53
12.68
22.38

.007
.865
⬍ .001.094⬍ .001⬍ .001⬍ .001⬍ .0011.05 to 1.39
0.99 to 1.0077
3.88 to 6.21
0.99 to 1.20
0.90 to 0.92
1.12 to 1.16
1.26 to 1.37
4.66 to 6.27

1
1.53
2.70
10.16

0.15
0.27
1.09

4.26
9.86
21.55

⬍ .001⬍ .001⬍ .001

1.26 to 1.86
2.22 to 3.29
8.23 to 12.55

Abbreviations: HR, hazard ratio; INR, international normalized ratio.

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Johnson et al

Table A2. Multivariable Cox Regression Using Stepwise Forward Selection of Variables (entire Japanese cohort)
HR

SE

z

P⬎z

95% CI

3.75
0.90
1.30
2.74
1.02
1.45

1.36
0.00940.058
0.61
0.00650.16

3.64⫺10.04
5.89
4.53
3.41
3.35

⬍ .001⬍ .001⬍ .001⬍ .001.001.001

1.84 to 7.63
0.88 to 0.92
1.19 to 1.42
1.77 to 4.24
1.01 to 1.03
1.17 to 1.80

3.43
0.91
1.21
2.32
1.02

0.84
0.013
0.057
0.77
0.0094

5.04
⫺6.92
4.08
2.55
2.37

⬍ .001⬍ .001⬍ .001.011.018

2.12 to 5.55
0.88 to 0.93
1.10 to 1.33
1.21 to 4.44
1.0038 to 1.04

2.75
0.96
2.76
1.13

0.49
0.016
0.92
0.045

5.67
⫺2.63
3.06
2.98

⬍ .001
.009
.002
.003

1.94 to 3.91
0.92 to 0.99
1.44 to 5.30
1.04 to 1.22

0.91
10.25

0.022
5.52

⫺4.07
4.32

⬍ .001⬍ .0010.87 to 0.95
3.56 to 29.48

3.67
0.92

1.43
0.016

3.34
⫺5.16

.001
⬍ .0011.71 to 7.89
0.89 to 0.95

2.30
0.90
1.02
1.32

0.51
0.00970.0072
0.16

3.71
⫺9.79
2.97
2.22

⬍ .001⬍ .001.003.026

1.48 to 3.56
0.88 to 0.92
1.01 to 1.04
1.03 to 1.68

1.76
0.91

0.45
0.011

2.21
⫺7.58

.027
⬍ .0011.07 to 2.91
0.89 to 0.94

3.13
0.95

0.76
0.012

4.72
⫺4.44

⬍ .001⬍ .0011.95 to 5.02
0.92 to 0.97

Variable
Tumor size ⬍ 3 cm
Macroscopic vascular invasion
Albumin, g/L
Tumor number
Log10 bilirubinAge
Sex (male)
Tumor size 3-5 cm
Macroscopic vascular invasion
Albumin, g/L
Tumor number
Log10 bilirubin
Age
Tumor size 5.1-10 cm
Macroscopic vascular invasion
Albumin, g/L
Log10 bilirubin
Tumor number
Tumor size ⬎ 10 cm
Albumin, g/L
Log10 bilirubinStage I
Log10 bilirubin
Albumin, g/LStage II
Log10 bilirubin
Albumin, g/L
Age
Sex (male)Stage III
Log10 bilirubin
Albumin, g/LStage IV
Log10 bilirubin
Albumin, g/L
Abbreviation: HR, hazard ratio.

CohortEurope
Japan
China
US

Overall Survival(probability)

1.0

0.8

n
2,168
2,596
1,108
505

Median survival,
months (95% CI)
17.8 (16.3 to 19.1)
47.2 (44.6 to 49.5)
7.2 (6.4 to 8.2)
18.6 (15.8 to 23.4)

40

60

0.6

0.4

0.2

0

20

Time (months)
Fig A1. Kaplan-Meier curves showing survival in the Japanese, European, Chinese, and US cohorts.

© 2014 by American Society of Clinical Oncology

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Liver Function in Patients With HCC

A

ALBIMedian survival,
gradenmonths (95% CI)
1
327
2
854
46.5 (42.5 to 51)
3
131
16.6 (11.6 to 24.1)
Harrell’s C and Somers’s D: 0.61 and 0.22

1.0

B
1.0

0.8

Survival(probability)

Survival(probability)

0.8

0.6

0.4

0.2

0

0.6

0.4

0.2

20

40

60

0

Time (months)

C

D

40

60

Child-PughMedian survival,
gradenmonths (95% CI)
A
866 65.3 (55.6 to 78.3)
B
337 29.4 (22.8 to 32.8)
C81
14.1 (9.7 to 19.4)
Harrell’s and Somers’s D: 0.64 and 0.27

1.0

0.8

Survival(probability)

0.8

Survival(probability)

20

Time (months)

ALBI
Median survival,
gradenmonths (95% CI)
1323
85.6 (61.1 to )2845
45.8 (40.4 to 50.1)
3
116
13.8 (9.6 to 18.7)
Harrell’s C and Somers’s D: 0.61 and 0.23

1.0

0.6

0.4

0.2

0

Child-PughMedian survival,
gradenmonths (95% CI)A875
60 (51.9 to 70.7)
B
347
30.3 (27.2 to 38)
C90
16 (9.3 to 18.8)
Harrell’s C and Somers’s D: 0.63 and 0.26

0.6

0.4

0.2

20

40

Time (months)

60

0

20

40

60

Time (months)

Fig A2. Application of the Albumin-Bilirubin (ALBI) model to the training and validation sets. Kaplan-Meier curves depicting survival according to ALBI and Child-Pugh(C-P) grade in the (A and B) Japanese training set and (C and D) validation set.

www.jco.org© 2014 by American Society of Clinical Oncology

Information downloaded from jco.ascopubs.org and provided by at OOGAKI SHIMIN BYOIN on December 15, 2014 from
Copyright © 2014 American Societyof Clinical Oncology. All rights reserved.
61.114.81.70

Johnson et al

Bilirubin (µmol/L)Albumin (g/L)

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60

6
8
10
12
14
16
18
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60

ALBI grade 3

ALBI grade 2

ALBI grade 1

Fig A3. Heat map for rapid assessment of the Albumin-Bilirubin (ALBI) grade.

© 2014 by American Society of Clinical Oncology

JOURNAL OF CLINICAL ONCOLOGY

Information downloaded from jco.ascopubs.org and provided by at OOGAKI SHIMIN BYOIN on December 15, 2014 from
Copyright © 2014 American Societyof Clinical Oncology. All rights reserved.
61.114.81.70