Vol.2, No.12, 1413-1420 (2010) Health
doi:10.4236/health.2010.212210
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
Diagnostic accuracy of biochemical markers of fibrosis
in black African patient s wit h c hron ic hepatitis B
Alassan Kouamé Mahassadi1*, Alain Koffi Attia1, Fulgence M. Yao Bathaix1,
Narcisse Baudouin Agbé1, Stanislas Doffou1, Henriette Ya Kissi1,
Isidore Mouhenou Diomandé2, Paul Cales3, Thérese Ndri-Yoman1
1Service d’hépato-gastroentérologie, CHU de Yopougon, Abidjan, Côte d’Ivoire; *Corresponding Author: mahassadi@yahoo.com;
2Laboratoire d’anatomie pathologique, Faculté de médecine de Cocody, Abidjan, Côte d’Ivoire;
3Service d’hépato-gastroentérologie, CHU d’Angers, France.
Received 15 August 2010; revised 6 October 2010; accepted 11 October 2010
ABSTRACT
Contradictory results of the accuracy of bio-
chemical markers to p redict th e st age of fibrosis
in black Afri can p atients with chronic hepatitis B
(CHB) were previously published. We con-
ducted a prospective cohort study to determine
the diagnostic accuracy of aspartate aminotr ans-
ferase to platelet ratio (APRI), aspartate ami-
notransferase to alanine aminotransferase ratio
(AAR), platelet count, age-platelet (AP) index,
and FIB-4 index for the prediction of significant
fibrosis or cirrhosis in 117 black African p atient s
(median age: 38 years, males: 73%) with CHB
not previously treated. Among them, 45 had
significant fibrosis and 18 had cirrhosis using
the METAVIR score system. Factors associated
either with significant fibrosis or cirrhosis were
determined in logistic multivariate analysis.
Areas under receiver operating curve were as-
sessed and compared for APRI, AAR, AP index,
FIB-4 index and platelet count. Sensitivity,
specificity, positive and negative predictive
values were determined for each biochemical
markers. Multivariate analysis showed that as-
partate aminotransferase (p < 0.0001) and
platelets (p = 0.03) were the independent factors
associated with significant fibrosis and only
platelets (p = 0.01) were associated with cirrho-
sis. APRI (cut-off > 1.1) and FIB-4 index
(cut-off > 2.1) ruled out significant fibrosis with
high specificity of 84.7% and 86.1% respectively
and negative predictive values of 78.2% and
72.9% respectively. More accurately, APRI
(cut-off > 0.63) or FIB-4 index (cut-off > 1.26)
ruled out cirrhosis with high sensitivity of 94.4%
and 88.9% and high negative predictive values
of 98.1% and 96.3% respectively. In conclusion,
APRI and FIB-4 index are simple readily avail-
able markers to exclude significant fibrosis or
more accurately cirrhosis in black African pa-
tient s with CHB.
Keywords: Non Invasive Models; Fibrosis;
Cirrhosis; Hepatitis B; Su b-Saharan Africa
1. INTRODUCTION
Chronic hepatitis B (CHB) is the major cause of
chronic liver disease that affects approximately 350 mil-
lions individuals worldwide leading to cirrhosis and
hepatocellular carcinoma. Africa and Asia have the high-
est prevalence of hepatitis B virus infection worldwide
[1,2]. It is obvious that treatment of CHB is a challenge
for clinicians in Africa. The assessment of liver disease in
patients with CHB by the mean of liver biopsy is not a
mandatory but needed at baseline to exclude others
causes of liver disease or to evaluate the histologic dam-
age in the liver before the initiation of treatment after
long term follow up [2-4]. However, liver biopsy is an
invasive, costly and not completely safe mean that can
lead to severe complications with a potential risk of mor-
tality. In addition, it is limited by sampling error and poor
concordance between two observers [5,6].
Viral hepatitis C is the more prevalent chronic liver
disease in western countries [7]. Non invasive means are
constructed to determine the stage of fibrosis in patients
with chronic hepatitis C with acceptable accuracies and
therefore the need of liver biopsy can be obviated [8-14].
Several studies attempt to use some of these means in
patients with CHB and yield unsatisfactorily results
[15-17]. WAI et al. show that aspartate aminotransferase
(AST) to platelet ratio (APRI), aspartate aminotrans-
ferase to alanine aminotransferase (ALT) ratio (AAR)
and platelet count were not accurate in predicting either
significant fibrosis or cirrhosis among patients with
CHB. These findings are confirmed by Kim et al. for the
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1414
prediction of cirrhosis in patients with CHB. All these
tests are validated in Asian patients [16,17].
The diagnostic accuracy of biochemical markers for
the prediction of the stage of fibrosis or cirrhosis in
black African patients was not evaluated enough. One
study suggested that FIB-4 index was accurate to ex-
clude significant fibrosis in black African patients with
CHB [18]. Recently discordant results were published by
Bonnard et al. that demonstrated low accuracy of FIB-4
index and APRI for the prediction of significant fibrosis
or cirrhosis in this ethnic group of population [19].
The aim of this study was to evaluate the AAR, APRI,
platelet count, age-platelet (AP) index, and FIB-4 index
for the prediction of significant fibrosis and cirrhosis in
black African patients with CHB attending the hepatol-
ogy unit of the Teaching hospital of Yopougon in Abid-
jan, Ivory Coast, West Africa.
2. MATERIALS AND METHODS
2.1. Patients
All consecutive patients with positive serum hepatitis
B surface antigen (HBsAg) and HIV-negative referred to
the hepatology unit at Yopougon teaching hospital were
eligible for the study. CHB infection was considered if
HBsAg persists 6 months after the date of the onset of
acute hepatitis B infection. For those with unknown date
of the onset of acute hepatitis B infection, CHB was con-
sidered if HBsAg is present in a secondary blood test
performed 6 months after the date of the previous posi-
tive blood test [1,2]. The exclusion criteria were con-
comitant liver disease such hepatitis D superinfection,
hepatitis C coinfection, autoimmune hepatitis, decom-
pensated cirrhosis, hepatic schistosomiasis, if blood test
were positive for antibodies against schistosomiasis or
the presence in liver biopsy, granulomatous and fibrotic
reaction related to hepatic schistosomiasis [20] concomi-
tant treatment against HBV, and alcohol consumption
over 50 g/l. All patients gave the consent for liver biopsy
and data were used according to Helsinki declaration.
2.2. Methods
2.2.1. Clinical Dat a
Following clinical data collected: age, sex, occupation,
ethnicity, source of contamination, presumably date of
contamination, past history of vaccination, alcohol con-
sumption.
2.2.2. Biological Dat a
Before liver biopsy, blood test were performed in the
laboratory of the Yopougon teaching hospital and pro-
vided following variables, haemoglobin, hematocrit,
mean corpuscular volume, platelet count (Coulter T-540
Coulter Corporation Hialeah, Florida USA), prothrom-
bin index (Coagulometer Option 4 plus Biomerieux
Germany), AST, ALT (Automate Analyzer, Hitachi Ldt,
Tokyo, Japan). The upper limit of normal of AST and
ALT were different according to sex and regarding the
normal values assigned by the laboratory AST: 31 and
36 IU/L, ALT: 34 and 43 IU/L, for respectively male and
female.
2.2.3. Virological Assay
HBsAg, hepatitis B e antigen (HBeAg), and antibody,
antibody to hepatitis B core antigen (Anti-HBc) were
performed using commercial assays (Cobas, Roche Di-
agnostics, Mannheim) if treatment was needed according
to the result of liver histology, ALT level or viral load
[3,4]. All virological assays were assessed at the Centre
Intégré de Recherche Bioclinique d’Abidjan (CIRBA)
laboratory of Abidjan.
2.2.4. Histological Assessment
Liver biopsies if not contraindicated were performed
after liver ultrasonography within 7 days after blood
testing. Needles of 1.6 mm diameter (Hepafix, Braun,
Melsungen) were used for all patients and liver biopsy
was performed according the Menghini technique [5].
Liver biopsy specimens were formalin-fixed, paraffin-
embedded and stained with hematoxilin-eosin-safran and
perls coloration for iron load. Necroinfammatory activity
and fibrosis stage were assessed by one senior patholo-
gist (DMI), who was blinded to the clinical examination
and blood tests and according to the METAVIR semi
quantitative system [21]. The fibrosis stage was as fol-
low: F0: no fibrosis, F1: portal fibrosis, F2: fibrosis with
few septa, F3: fibrosis with numerous septa, F4: cirrho-
sis. The grade of activity was as follow: A0: no histo-
logical activity, A1: mild activity, A2: moderate activity,
A3: severe activity. The length of biopsy specimen was
not recorded for all patients.
2.2.5. Diagnostic Target
Two diagnostic targets (significant fibrosis and cirrho-
sis) assessed by the histologic findings after liver biopsy
were used to identify four groups of patients. Patients
with significant fibrosis (F2, F3, and F4) were compared
to those without significant fibrosis (F0 and F1) and pa-
tients with cirrhosis (F4) were compared with those
without cirrhosis (F0, F1, F2, and F3).
2.2.6. Statisti cal Analysis
Continuous variables were expressed as median and
interquartile range and qualitative variables were ex-
pressed as percentage. Mann-Withney U test and χ2 or
Fischer test (if appropriated) were used to compare
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1415
quantitative and qualitative variables. The correlations
between AST, ALT and platelet count with the stage of
fibrosis were assessed by the non parametric Spearman’s
rho test (rho). The AAR, APRI, AP index and FIB-4 in-
dex were determined by formula previously published
and resumed in Table 1 [8,11,13,14]. Variables signifi-
cantly associated with significant fibrosis or cirrhosis in
univariate analysis were tested using a multivariate lo-
gistic regression. The diagnostic accuracy with the best
cut-off point that maximizes the sensitivity and the
specificity and express as sensitivity, specificity, predic-
tive positive and negative values were determined by the
receiver operating characteristic curve (ROC) for platelet
count, AAR, APRI, AP index and FIB-4 index. The areas
under ROC of platelet count, AAR, APRI, AP index and
FIB-4 index of each group were compared according to
the Henley and Mac Neil test [22]. Value of area under
ROC of 1.0 indicated an ideal test whereas value of 0.5
indicated that the test was not significant. All tests were
two-tailed and performed by SPSS for Windows version
11.0 (SPSS Inc., Chicago, IL). P value under 0.05 was
considered as significant.
3. RESULTS
3.1. Study Sample
Between January 2002 and December 2005, a total of
136 patients were recruited. Twenty four patients were
excluded (7 patients with chronic hepatitis C, 12 patients
with both CHB and C, 3 patients with hepatic steatosis
and 2 patients with sclerosing cholangitis). The remain-
ing 117 patients were included (73.3% were male). All
of them were Ivoirians and black Africans with a median
age (interquartile range) of 38 years (30-46). The base-
line characteristics are summarised in Tab le 2. Signifi-
cant fibrosis and cirrhosis were found respectively in 45
(42.2%) and 18 (40%) patients.
3.2. Factors Associated with Significant
Fibrosis or Cirrhosis
Patients with significant fibrosis or cirrhosis had
Table 1. Formulas of biochemical markers for the prediction of
necroinflammatory activity and fibrosis stage.
Tests Formulas
AAR AST/ALT
APRI (AST [ULN]/platelet count [103/mL]) × 100
AP index
Age (years): <30 = 0; 30-39 = 1; 40-49 = 2;
50-59 = 3; 60-69 = 4; 70 = 5
Platelet count (× 103/mL): 225 = 0; 200-224 = 1;
175-199 = 2; 150-174 = 3; 125-149 = 4; < 125 = 5
FIB-index Age[years] × AST [IU/L]/(platelet count [103/mL] ×
(ALT1/2 [IU/L])
AAR: aspartate aminotransférase to alanine aminotransferase ratio,
APRI: Aspartate aminotransferase to platelet count ratio, AP index:
age-platelet index.
Table 2. Baseline characteristic of 117 patients included.
all patients
(n = 117)
Age (years ) [median (IQR)] 38 (30-46)
Black Africans [n (%)] 117 (100)
Sex (male) [n (%)] 86 (73.5)
Blood parameters
ALT (IU/L) [median (IQR)] 45 (29-105)
ALT (ULN) [median (IQR)] 1.1 (0.7-2.6)
AST (IU/L) [median (IQR)] 44 (27-86)
AST (ULN) [median (IQR)] 1.3 (0.8-2.5)
Platelet count (× 103/mL) [median (IQR)] 196 (140.5-250)
Prothrombin time (%) [median (IQR)] 90 (80-100)
Metavir fibrosis stage
No fibrosis (F0) [n (%)] 52 (44.4)
Portal fibrosis (F1) [n (%)] 20 (17.1)
Few septa (F2) [n (%)] 16 (13.7)
Numerous septa (F3) [n (%)] 11 (9.4 )
Cirrhosis (F4) [n (%)] 18 (15.4)
Metavir histologic activity
No activity (A0) [n (%)] 45 (38.5)
Mild activity (A1) [n (%)] 30 (25.6)
Moderate activity (A2) [n (%)] 21 (17.9)
Severe activity (A3) [n (%)] 21 (17.9)
AST: aspartate aminotransferase, ALT: alanine aminotransferase,
ULN: upper limit of normal, IQR: interquartile range.
higher level of ALT (ULN) or AST (ULN) and lower
platelet count than those without significant fibrosis or
cirrhosis in univariate analysis (Table 3). AST (ULN)
and ALT (ULN) levels correlated positively (both corre-
lation coefficients rho = 0.4, p < 0.0001) whereas plate-
let count correlated negatively (rho = –0.28, p = 0.002)
with the stage of fibrosis. Overall comparison demon-
strated significant difference between AST or Platelets
count and the stage of fibrosis (Figure 1). In logistic
multivariate analysis, AST (p < 0.0001) and platelet
count (p = 0.03) were independent predictors of signifi-
cant fibrosis whereas platelet count was the only inde-
pendent factor associated with cirrhosis (p = 0.01). The
median values (with interquartile range) of biochemical
markers are summarised in Table 4. Besides AAR for
significant fibrosis, biochemical markers showed sig-
nificant but modest area under ROC either for the pre-
diction of significant fibrosis (fibrosis stage F2) or
cirrhosis (F4) in our study (Table 5).
3.3. Comp ari son of Biochemical Pa rameters
for the Prediction of Significant
Fibrosis
As illustrated in Figure 2(a), APRI, platelet count,
FIB-4 index and AP index had similar diagnostic accu-
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1416
Table 3. Univariate analysis of parameters between patients with and without significant fibrosis, and between patients with and
without cirrhosis.
Fibrosis stage
F0-1 (n = 72) F2-4 ( n = 45) p-value F0-3 ( n = 99) Cirrhosis (F4)
(n = 18) p-value
Age (years) [median (IQR)] 39 (30-46) 35.5 (29-45.3) 0.9 38 (30-45) 41 (29-53) 0.5
Sex (male)[ n (%)] 52 (44.4) 34 (29.1) 0.7 72 (61.5) 14 (12) 0.8
ALT (UI/L) [median (IQR)] 39 (25.3-53.5) 85 (40.3-167.5) < 0.0001 41 (28-77) 114 (73.8-188.8)< 0.0001
ALT (ULN) [median (IQR)] 1.0 (0.7-1.3) 2.4 (1-4) < 0.0001 1.0 (0.7-1.8) 2.7 (1.9-4.4) < 0.0001
AST (UI/L) [median (IQR)] 38.5 (24.3-51.5) 70 (38-148) < 0.0001 41 (25-72) 85.5 (45.8-155) 0.002
AST (ULN) [median (IQR)] 1.6 (0.7-1.5) 2.3 (1.1-4.7) < 0.0001 1.2 (0.8-2.1) 2.5 (1.3-4.9) 0.002
Platelets count (103/mL) [median (IQR)] 215 (166.3-271) 153.5 (127.8-213.8) < 0.0001 208 (150-263) 139 (120.8-197)0.001
Prothrombin time [median (IQR)] 90 (80-75) 87.5 (79.8-100) 0.4 90 (80-100) 80.5 (78.8-96.3)0.1
ALT: alanine aminotransferase, AST: aspartate aminotransferase, F0-1: non significant fibrosis, F2-4: significant fibrosis, F0-3: no cirrhosis, F4: cirrhosis, ULN:
upper limit of normal, IQR: interquartile range.
Table 4. Distribution of biochemical markers values.
AAR: Aspartate aminotransferase to alanine aminotransferase ratio, APRI: Aspartate aminotransferase to platelet count ratio, AP index: age-platelet index, IQR:
interquartile range.
Table 5. Diagnostic accuracy of biochemical markers for the prediction of significant fibrosis and cirrhosis.
Cut-off
Area under
the ROC
(95% CI)
Sensitivity
(95% CI)
(%)
Specificity
(95% CI)
(%)
PPV
(95% CI)
(%)
NPV
(95% CI)
%
Diagnostic of significant
fibrosis
Platelet count (× 103/ mL) < 163 0.7 (0.61-0.78) 60 (44.3-74.3) 77.8 (66.4-86.7) 62.8 (46.7-77) 75.7 (64.3-84.9)
AAR - 0.54 (0.45-0.63) - - - -
APRI > 1.1 0.76 (0.67-0.84) 62.2 (46.5-76.2) 84.7 (74.3-92.1) 71.8 (55.1-85) 78.2 (67.4-86.7)
AP index > 3 0.67 (0.58-0.75) 66.7 (51.0-80.0) 65.3 (53.1- 76.1) 54.5 (40.6-68) 75.8 (63.3-85.8)
FIB-4 index < 2.1 0.70 (0.6-0.78) 48.89 (33.7-64.2) 86.1 (75.9-93.1) 68.7 (50-83.9) 72.9 (62.2-82)
Diagnostic of cirrhosis
Platelet count (× 103/ mL) 139 0.74 (0.65-0.82) 55.6 ( 30.8-78.5) 86.9 (78.6-92.8) 43.5 (23.2-65.5) 91.5 (83.9-96.3)
AAR 0.69 0.64 (0.54-0.72) 50.0 (26.1-74) 78.8 (69.4-86.4) 30.0 (14.7-49.4) 89.7 (81.3-95.2)
APRI > 0.63 0.76 (0.68-0.84) 94.4 (72.6-99.1) 53.5 (43.2-63.6) 27.0 (16.6-39.7) 98.1 (90.1-100)
AP index > 3 0.69 (0.60-0.78) 77.8 (52.4-93.6) 58.6 (48.2-68.4) 25.5 (14.7-39) 93.5 (84.3-98)
FIB-4 index > 1.26 0.68 (0.59-0.76 ) 88.9 (65.3-98.6) 52.5 (42.2-62.7) 25.9 (15.3-37.9) 96.3 (87.3-99,5)
AAR: Aspartate aminotransferase to alanine aminotransferase ratio, APRI: Aspartate aminotransferase to platelet count ratio, AP index: age-platelet index.
racy for the prediction of significant fibrosis. However-
better performances were observed with APRI and FIB-4
index (Tab le 5 ). With a cut-off > 1.1 of APRI, signifi-
cant fibrosis could be correctly excluded in 61 (52%) of
117 patients with 78.2% of NPV. Similar results were
obtained with FIB-4 index (cut-off > 2.1) that identified
correctly 62 (53%) of 117 as patients with no significant
fibrosis. However the number of false negative patients
was lower with FIB-4 index than APRI (8.5% and
14.5 % respectively).
3.4. Comparison of Biochemical Parameters
for the Prediction of Cirrhosis
All biochemical markers had better performances to
exclude cirrhosis (Figure 2(b)) with high negative pre-
dictive values > 80%. APRI and FIB-4 index had maxi-
mal sensitivity respectively 94.4% and 88.9% (Table 5).
All patients (n = 117 )
Significant fibrosis
Fibrosis stage F2-4
(n = 45)
cirrhosis
Fibrosis stage F4
(n = 18)
Platelet count (103/mL) [median (IQR)] 205.51 (140.5-205) 152 (127.5-210) 139 (120.8-197)
AAR [median (IQR)] 1.0 (0.69-1.32) 0.9 (0.58-1.58) 0.78 (0.49-1.14)
APRI [median (IQR)] 0.72 (0.4-1.85) 1.75 (0.68-3.62) 1.65 (0.87-4.10)
AP index [median (IQR)] 3.0 (2-5) 4 (3-6) 4.0 (3.5-6.3)
FIB-4 index [median (IQR)] 1.35 (0.78-2.20) 1.89 (1.24-4.30) 1.74 (1.46-2.77)
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1417
Figure 1. Box plots of AST (a) or platelet count (b) according to the stage of fibrosis defined by META-
VIR score system. The box represents the interquartile range; the top and the bottom of the box are re-
spectively the 25 th and 75 th percentile. The line across the box is the median. The lower and upper values
are indicated by the whiskers. The circles represent the outliers.
Figure 2. Receiver operating characteristic curve of the five biochemical markers for the prediction of sig-
nificant fibrosis (a) or cirrhosis (b) according to the METAVIR stage of fibrosis in black African patients
with chronic hepatitis B. APRI: aspartate aminotransferase to platelet count ratio, AAR: aspartate ami-
notransferase to alanine aminotransferase ratio, AP: age-platelet index and FIB-4 index.
With a cut-off > 0.63 of APRI, cirrhosis was correctly
excluded in 52 (52.5%) patients among 117 with a NPV
of 98.1%. Among 18 patients with histological proven
cirrhosis, 17 (94.4%) were correctly classified and 1
(1.9 %) patient was false negative. Applying a cut-off >
1.26 of FIB-4 index, we found similar results, 51 (51.5%)
patients of 117 correctly classified as patients with no
cirrhosis. Thus 16 (88.9%) patients of 18 with cirrhosis
were diagnosed and 2 (3.8%) were false negative.
4. DISCUSSION
We demonstrated in this study that biochemical mark-
ers previously assessed in chronic hepatitis C such as
APRI, AAR, FIB-4 index, platelet count and AP index
had low accuracy regarding their respective areas under
ROC, to predict the presence of significant fibrosis or
cirrhosis among black Africans with CHB. However
some of them could be used to exclude more accurately
cirrhosis in low medicalized countries of Africa.
Indeed we found that in patient with cirrhosis, APRI
and FIB-4 index enabled to eliminate cirrhosis with high
degree of certainty better than that published by Bonnard
et al., in Burkina Faso [19]. This is probably related to
the size of our sample twice larger. Indeed our patients
(a) (b)
(a) (b)
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1418
were slightly older than those from Mayotte and some of
them had platelet count in normal range despite moder-
ate to severe fibrosis (Figure 1(b)) leading to misclassi-
fication of FIB-4 index. The length of liver biopsy frag-
ment was probably not large enough in our study to en-
hance the accuracy of FIB-4 index as previously demon-
strated [18]. In other hand the interaction of parasitosis
or other blood transmitted diseases as malaria and CHB
both prevalent in sub-Saharan African countries could
reduce the global performance of these biochemical
markers in African patients [24]. Nevertheless APRI and
FIB-4 index could be used to monitor patient with CHB
when liver biopsy is difficult to perform. Both were ac-
curate to exclude cirrhosis among black Africans with
high degree of NPV. This probably means that APRI and
FIB-4 index are more reliable when cirrhosis occurs in
sub Saharan African patients with CHB than westerners
or other black people. Recent studies conducted in Asia
demonstrated discordant results of APRI and FIB-4 in-
dex for the prediction of stage of fibrosis. Wu et al.,
founded low accuracy of APRI and FIB-4 index to pre-
dict significant fibrosis comparable to our findings [25].
However these two biochemical markers showed better
performances to predict severe fibrosis. Kim et al. dem-
onstrated that FIB-4 allowed detecting cirrhosis with
high degree of certainty than APRI, and AAR [26].
These recent findings emphasized the difficulty to pro-
vide definite and invariable performance of biochemical
markers in patients with CHB whatever the geographical
area. This study was conducted in West Africa where the
endemicity of HBV is high and enrolled only black Af-
ricans. Most of them acquired HBV infection perinataly
or during childhood which is the most common route of
transmission of HBV in this area [1]. Liver damage (fi-
brosis and cirrhosis) occurs mainly in adulthood with a
high risk of onset of hepatocellular carcinoma. This ex-
plained that 45% of patients in our study had significant
fibrosis or cirrhosis and were eligible for treatment [1,2].
We were not able to seek the date of the onset of acute
hepatitis B infection, to determine viral load or HBeAg
and antibody for most of patients because of the high
cost of their determination and high number of missing
values. These parameters were not included in the analy-
sis. Despite these limitations, this study pointed out
some specificities in a population of black African pa-
tients. Firstly, AST and platelet count were independent
predictors of significant fibrosis and only platelet count
were associated with cirrhosis in multivariate analysis.
Secondly, biochemical markers assessed in this study
with significant values of area under ROC had high abil-
ity to exclude patients with cirrhosis. Each of them
showed high NPV > 85%. Regarding the area under
ROC, our study confirmed the findings made by Wai et
al. and Kim et al. in Asian patients [16,17]. Furthermore
our study is consistent with that of Hongo et al., in
which the areas under the ROC of APRI and AP index
were also modest respectively 0.76 and 0.74 [23]. In
contrast to the study of Wai et al. in which only platelet
count were an independent factor associated either with
significant fibrosis or cirrhosis in multivariate analysis in
a cohort of Asian patients [16], our study suggest that
black African patients experience more flares of hepatitis
B with intermittent elevation of transaminases because
of immune pressure and high prevalence of HBeAg
negative CHB that lead to severe liver damage [2,27,28].
Indeed, cirrhosis and hepatocellular carcinoma occurred
more rapidly in patients with HBeAg negative CHB and
hepatocellular carcinoma related to HBV is more preva-
lent among blacks Africans [29,30]. Similar to others
studies, in patients with CHB even in those with chronic
hepatitis C, we found an association between platelet
count and cirrhosis as demonstrated by others [31,32].
Chronic hepatitis B is a public health concern in West
Africa where the vaccination against hepatitis B infec-
tion is not widely implemented in most sub-Saharan Af-
rican countries. Antiviral treatments are expensive for
most patients with severe liver damage. Pathologists
with a high experience in liver histologic examination
are not widely available. There is a need for accurate,
readily available and routinely feasible blood markers
for the prediction of significant fibrosis or cirrhosis in
Africa. Previous reports showed that combination of
biochemical markers that included hyaluronidase, alpha2
macroglobulin or serum globulin are accurate to predict
significant fibrosis or cirrhosis in patients with CHB but
most of then have low values of area under the ROC or
are not routinely incorporated in the panel of blood tests
in most hospital laboratories even in Europe than in Af-
rica [15,33,34]. Hui et al. demonstrate that a score in-
cluding body mass index, platelet count, serum albumin
and total bilirubin was accurate in predicting the absence
of significant fibrosis but needs complicated calculation
[35]. Mohamadnejad et al., published a score to assess
significant fibrosis only in patient with HBe Ag negative
CHB [36]. Hongbo et al. also demonstrated that combi-
nation of biochemical markers may enhance diagnosis
accuracy for either the prediction (AP index with AST in
parallel interpretation) or the exclusion (AP index with
gammaglutamyltransferase in serial interpretation) of
significant fibrosis in patient with CHB [23]. However,
we think that the procedure of calculation and interpreta-
tion is not easy to fulfil in clinical practice. Bonnard et al.
found that Elastometry were more reliable than APRI
and FIB-4 index to predict significant fibrosis in black
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1419
African patients but the device for it determination is
expensive and not available in most hospitals of sub Sa-
haran African countries [19]. Liver biopsy remains in
this area the only means to quantify liver fibrosis in pa-
tients with CHB. Guidelines and consensus conferences
recommend to monitor patients with cirrhosis by routine
alpha-fetoprotein determination and liver ultrasonogra-
phy every 6 months [2,3]. Close surveillance is recom-
mended to detect the onset of oesophageal varices if
absent at the time of the diagnosis of cirrhosis by routine
endoscopy [37,38]. Lamivudine, a nucleoside analogue
is widely used in Africa as part of highly antiretroviral
therapy in HIV infected patients. It is a cost effective
drug affordable to most Africans for the treatment of
CHB.
However, patients with cirrhosis treated by lami-
vudine need close surveillance because of the risk of
hepatitis flares and liver decompensation during treat-
ment [2,39].
Most of these recommendations are difficult to fulfil
in developing countries of Africa. Biochemical markers
such as APRI, and FIB-4 index easy to determine and
cost effective could be used to identify African patients
with CHB who do not have cirrhosis, and in whom close
surveillance could be delayed during treatment by lami-
vudine.
5. CONCLUSION
This study demonstrated that biochemical markers
currently used in chronic hepatitis C, had low accuracy
regarding their areas under ROC. However APRI and
FIB-4 index could be used to exclude cirrhosis in black
African patients with CHB with high certainty. Further
studies enrolling a large sample of black African patients
with CHB are needed to establish the clinical relevance
of the accuracy of biochemical markers in African pa-
tient.
REFERENCES
[1] Lavanchy, D. (2004) Hepatitis B virus epidemiology,
disease burden, treatment and current and emerging
prevention and control measures. Journal of viral
hepatitis, 11, 97-107.
[2] Lok, S.F. and Mc Mahon, B.J. (2007) Chronic hepatitis B.
Hepatology, 45, 507-539.
[3] EASL (2009) Clinical practice guidelines: management.
Journal of Hepatology, 50, 227-242.
[4] Keffe, E.B., Dieterich, D.T., Han, S.H., Jacobson, I.M.,
Martin, P., Schiff, E.R. and Tobias, H.A. (2008) A
treatment algorithm for the management of chronic
hepatitis B virus in the United States: 2008 update.
Clinical G astroe nter olog y and H ep atolo gy, 6, 1315-1341.
[5] Bravo, A., Sheth, S.G. and Chopra, S. (2001) Liver
biopsy. New England Journal of Medicine, 344, 495-500.
[6] Skripenova, S., Trainer, D.T., Krawitt L.E. and Blaszyk
H. (2007) Variability of grade and stage in simultaneous
paired liver biopsies in patients with hepatitis C. Journal
of Clinical Pathology, 60, 321-324.
[7] Lauer, M.G. and Walker, B.D. (2001) Hepatitis C virus
infection. New England Journal of Medicine, 345, 41-50.
[8] Poynard T., Bedossa, P. and METAVIR, CLINIVIR,
cooperative study. (1997) Age and platelet count: A
simple index for predicting the presence of histological
lesions in patients with antibodies to hepatitis C virus.
Journal of Viral Hepatitis, 4, 199-208.
[9] Imbert-Bismuth, F., Ratzui, V., Pieroni, L., Charlotte, F.,
Benhamou, Y. and Poynard T. (2001) Biochemical
markers of liver fibrosis in patients with hepatitis C virus
infection: a prospective study. Lancet, 357, 1069-1075.
[10] Pohl, A., Behling C., Oliver D., Kilani, M., Monson P.
and Hassanein, T. (2001) Serum aminotransferase levels
and platelets counts as predictors of degree of fibrosis in
chronic hepatitis C infection. American Journal of
Gastroenterology, 96, 3142-3146.
[11] Myer,s R.P., De Torres, M., Imbert-Bismut, F., Ratziu,
V., Charlotte, F. and Poynard T. (2003) Biochemical
markers of fibrosis in patients with chronic hepatitis C. A
comparison with prothrombin time, platelet count and
age-platelet index. Digestive Diseases and Sciences, 48,
146-153.
[12] Forns, X., Ampurdanes, S., Llovet, J.M., Aponte, J.,
Quinto, L., Bauer-Martinez, E., Bruguera, M.,
Sanchez-Tapias, J.M. and Rodes R. (2002) Identification
of chronic hepatitis C patients without hepatic fibrosis by
a simple predictive model. Hepatology, 36, 987-992.
[13] Wai, C-T., Greenson, J.K., Fontana, R.J., Kalbfleisch,
J.D., Marrero, J.A., Conjeevaram, H.S. and Lok, A.S.F.
(2003). A simple non-invasive index can predict both
significant fibrosis and cirrhosis in patients with chronic
hepatitis C. Hepatology, 38,518-526.
[14] Vallet-Pichard, A., Mallet, V., Nalpas, B.,Verkarre,V.,
Nalpas, A., Dhalluim-Venier, V., Fontaine, H. and Pol, S.
(2007). FIB-4 index an inexpensive and accurate markers
of liver fibrosis in HCV infection. Comparison with liver
biopsy and fibrotest. Hepatology,46, 32-35.
[15] Myers, R.P., Tainturier, M-H., Ratziu, V., Piton, A.,
Thibault, V., Imbert-Bismut, F., Messous, D., Charlotte,
F., Di-Martino,V., Benhamou Y. and Poynard T. (2003)
Prediction of liver histological lesions with biochemical
markers in patients with chronic hepatitis B. Journal of
Hepatology, 39, 222-230.
[16] Wai, C-T., Cheng, C.L., Wee, A., Dan , Y.Y., Chua, W.,
Mak, B., AM, Oo. and Lim, S.G. (2006). Non-invasive
models for predicting histology in patients with chronic
hepatitis B. Liver international, 26, 666-672.
[17] Kim, B.K., Kim, S.A., Park, Y.N., Cheong, J.Y., Kim,
H.S., Park, J.Y., Cho, S.W., Han, K.-H., Chon, C.Y.,
Moon, Y.M. and Ahan, S.H. (2007) Non invasive models
to predict liver cirrhosis in patients with chronic hepatitis
B. Liver international, 27, 969-976.
[18] Mallet, V., Dhalluin-Venier, V., Roussin, C., Bourlière
M., Pettinelli, M.E., Giry, C., Vallet-Pichard, A., Fontaine,
H. and Pol, S. (2009) The accuracy of FIB-4 for the
diagnostic of mild fibrosis in chronic hepatitis B. Alimentary
Pharmacology and Th erapeutics , 29, 409-415.
A. K. Mahassadi et al. / Health 2 (2010) 1413-1420
Copyright © 2010 SciRes. Openly accessible at http://www.scirp.org/journal/HEALTH/
1420
[19] Bonnard, P., Sombié, R., Lescure, F.X., Bougouma, A.,
Guiard-Schmid, J.B., Poynard, T., Cales, P., Housset, C.,
Callard, P., Le Pendeven, C., Drabo, J., Carrat, F. and
Pialoux, G. (2010) Comparison of elastography, serum
marker scores, and histology for the assessment of liver
fibrosis in hepatitis B virus (HBV)-infected patients in
Burkina Faso. American Journal of Tropical Medicine
and Hygiene, 82, 454-458.
[20] Plorde, J.J. and Jong, C.E. (1983) Schistomiasis. In:
Petersdrof, R., Adams, R.D., Braunwald, E., Isselbacher,
K.J., Martin, J.D., et al., Eds., Harrison’s Principles of
Internal Medecine, MacGrw-Hill, Inc., New York, 1217-
1222.
[21] The French METAVIR Cooperative Study Group (1994)
Intraobserver and interobserver variations in liver biopsy
interpretation in patients with chronic hepatitis C.
Hepatology, 20, 15-20.
[22] Hanley J.A. and McNeil, B.J. (1983) A method of
comparing the areas under receveir operating characteristic
curves derived from the same cases. Radi ology, 148,
839-843.
[23] Hongbo, L., Xiaohui, L., Hong, K., Wei, W. and Yon, Z.
(2007) Assessing routine and serum markers ol liver
fibrosis in chronic hepatitis B patients using parallel and
serial interpretation. Clinical biochemistry, 40,562-566.
[24] Ignatus, C.M., Emeka, E.N., and Blessing, N.E. (2008)
Effect of malaria parasitemia on liver enzyme tests.
International Journal of Tropical Medecine, 3, 49-52.
[25] Wu, S.D., Wang, J.Y. and Li, L. (2010) Staging of liver
fibrosis in chronic hepatitis B patients with a composite
predictive model: A comparative study. World Journal of
Gastroenterology, 16, 501-517.
[26] Kim, B.K., Kim do, Y., Park, J.Y., Ahn, S.H., Chon,
C.Y., Kim, J.K. Paik, Y.H., Lee, K.S., Park, Y.N. and
Han, K.H. (2010) Validation of FIB-4 and comparison
with other simple noninvasive indices for predictiong
liver fibrosis and cirrhosis in hepatitis B virus-infected
patients. Liver international, 45, 355-360.
[27] Zarsky, J.P., Marcellin, P., Leroy, V., Trepo, C., Samuel,
D., Ganne-Carrie N., Barange, K., Canva, V., Doffoel M.,
Cales, P. and Fédération Nationale des Pôles de Références
et des Réseaux Hépatites. (2006) Characteristics of patients
with chronic hepatitis Bin France: Predominant frequency
of HBe antigen negative cases. Journal of hepatology, 45,
355-360.
[28] Suzuki, S., Sugauchi F., Orito, E., Kato, H., Usuda, S.,
Siransy, L., Arita, I., Sakamoto, Y., Yoshihara, N; El-
Gohary, A., Ueda, R. and Mizokami, M. (2003) Distribution
of hepatitis B virus (HBV) genotype among HBV
carriers in the Côte d’Ivoire: Complete genome sequence
and phylogenetic relatedness of HBV genotype E.
Journal of Medical Virology, 69, 946-953.
[29] Baptista, M., Kramvis, A., and Kew, MC. (1999) High
prevalence of 1762 (T) 1764(A) mutations in the basic
core promoter of hepatitis B virus isolated from black
Africans with hepatocellular carcinoma compared with
asymptomatic carriers. Hepatology, 29, 946-953.
[30] Kew, M.C. (2002) Epidemiology of hepatocellular carcinoma.
Toxicology, 27, 35-38.
[31] Karasu, Z., Tekin, F., Ersoz, G., Gunsar, F., Batur, Y.,
Ilter, T. and Akarca, U.S. (2007) Liver fibrosis is
associated with decreased peripheral platelet count in
patients with chronic hepatitis B and C. Digestive
Diseases and Sciences, 52, 1535-1539.
[32] Goulis, J., Chau, T.N., Jordan. S, Metha, A.B., Watkinson,
A., Rolles, K. and Burroughs, A.K. (1999) Thrombopoietin
concentrations are low in patients with cirrhosis and
thrombocytopenia and are restored after orthotopic liver
transplantation. Gut, 44, 754-758.
[33] Zeng, M.D., Lu, L.G., Mao, Y.M., Qui, D.K., Li, M.B.,
Wan, C.W., Chen, J.Y., Wang, X., Gao, C.F. and Zhou,
X.Q. (2005) Prediction of significant fibrosis in HbeAg-
positive patients with chronic hepatitis B by a non-
invasive model. Hepatology, 42, 1437-1445.
[34] Schmilovitz-Weiss, H., Tovar, A., Halpern, M., Sulkes,
J., Braun, M. and Rotman, Y. (2006) Predictive value of
serum globulin levels for the extent of hepatic fibrosis in
patients with chronic hepatitis B infection. Journal of
viral hepatitis, 13, 671-677.
[35] Hui, A.Y., Chan, H.L., Wong, V.W., Liew, C.T., Chim,
A.M., Chan, F.K. and Sung, J.J. (2005) Identification of
chronic hepatitis B patients without significant liver
fibrosis by a simple non invasive predictive model.
American Journal of Gastroenterology, 100, 616-623.
[36] Mohamadnejad, M., Montazeri, G., Fazlollahi, A.,
Zamani, F., Nasiri, J., Nobakht, H., Forouzanfar, M.H.,
Abedian, S., Tavangar, S.M., Mohamadkhani, A., Ghoujeghi,
F., Estakhri, A., Nouri, N., Farzadi, Z., Najjari, A. and
Malekzadeh, R. (2006) Noninvasive markers of liver
fibrosis and inflammation in chronic hepatitis B-virus
related liver disease. American Journal of Gastroenterology,
101, 2537-2545.
[37] Cales, P., Desmorat, H., Vinel, J.P., Caucanas, J.P.,
Ravaud, P., Gerin, P., Brouet, P. and Pascal, J.P. (1990)
Incidence of large oesophageal varices in patients with
cirrhosis: Application to prophylaxis of first bleeding.
Gut, 31, 1298-1302.
[38] de Franchis, R. and Baveno, V. (2010) Faculty Revising
consensus in portal hypertension: report of the Baveno V
consensus workshop on methodology of diagnosis and
therapy in portal hypertension. Journal of hepatology, 53,
762-768.
[39] Marrone, A., Zampino, R., Karayannis, P., Cirillo, G.,
Cesaro, G., Guerrera, B., Riccioti, R., Del Giudice, E.M.,
Utili, R., Adinolfi, L.E. and Ruggiero, G. (2005) Clinical
reactivation during lamivudine treatment correlates with
mutations in the precore/core promoter and polymerase
regions of hepatitis B virus in patients with anti-Hepatitis
B e-positive chronic hepatitis. Alimentary Pharmacology
and Therapeutics, 22, 707-714.