Nouveaux marqueurs non invasifs de la maladie du foie - Afef

Nouveaux marqueurs
non invasifs:
utilisation pronostique
Laurent CASTERA
Service d’Hépatologie, Hôpital Beaujon,
Clichy

Méthodes non invasives disponibles
2 approches différentes mais complémentaires
Approche « biologique »
Approche « physique »
Biomarqueurs
Elasticité hépatique
Castera & Pinzani. Lancet 2010; 375: 419-20

Biomarqueurs
Marqueurs « Direct »
Ac Hyaluronique
PIIINP
Laminine
Collagene Type IV
MMP
TIMP-1
TGF-beta
YKL-40
Marqueurs « Indirect »
Taux de Prothrombine
Taux de Plaquettes
Ratio ASAT/ALAT

Biomarqueurs: scores les plus étudiés
APRI =
AST x 100
Platelet
Fibrometre ®
®

Elasticité hépatique
FibroScan
Sandrin et al. UMB 2003; 29: 1705-13
Castera, Forns & Alberti. J Hepatol 2008; 48: 835-47

Elasticité hépatique
Acoustic Radiation Force Impulse Imaging (ARFI)
Nightingale et al. UMB 2002 ; 28: 227-35
Friedrich-Rust et al. Radiology 2009 ; 252: 595-604

Elasticité hépatique
Elasto-IRM
+90
Displacement (µm)
0
-90
Elastogram
10
8
6
4
2
0
Shear Stiffness (kPa)
Muthupillai et al. Science 1995; 269: 1854-7
Huwart et al. Gastroenterology 2008; 135: 32-40

over a large bandwidth. In parallel, SWS provides
a refined analysis in a larger box of these dispersive properties
of tissues by estimating frequency dependence of
the shear wave speed.
Elasticité hépatique
Statistical methods
The diagnosis performance of FS and SSI are
SuperSonic compared by using receiver operatingImaging
characteristic
(ROC) curves and box-and-whisker curves on the same
1366 Ultrasound in Medicine and Biology cohort. Volume A patient 37, Number was assessed 9, 2011 as positive or negative according
to whether the noninvasive marker value was
Contrary to FS, as vibration induced by the radiation greater than or less than to a given cutoff value, respectively.
Connected with any cutoff value is the probability
force creates a short transient excitation, the frequency
bandwidth of the generated shear wave is large, typically of a true positive (sensitivity) and the probability of a true
ranging from 60 to 600 Hz (Fig. 3). Such wideband negative (specificity). The ROC curve is a plot of
‘‘shear wave spectroscopy’’ can give a refined analysis sensitivity vs. (1-specificity) for all possible cutoff values.
of the complex mechanical behavior of tissue. As shown The most commonly used index of accuracy is the area
in Figure 3, the shear wave dispersion law can be assessed under the ROC curve (AUROC), with values close to
from displacement movies in the region-of-interest. 1.0 indicating high diagnosis accuracy. Optimal cutoff
Thus, the global elasticity imaged by SSI makes use
values for liver stiffness were chosen to maximize the
of higher frequency content and is also influenced by the
sum of sensitivity and specificity and positive and negative
predictive values were computed for these cutoff
dispersive properties of the liver tissues because it averages
the full mechanical response of the liver tissues
values. By using these cutoff values, the agreement
over a large bandwidth. In parallel, SWS provides
between FS and SSI was evaluated. Statistical analyses
were performed with Matlab R2007a software (Mathworks,
Natick, MA, USA) using the statistical analysis
a refined analysis in a larger box of these dispersive properties
of tissues by estimating frequency dependence of
toolbox and Medcalc software (Mariakerke, Belgium).
the shear wave speed.
RESULTS
Statistical methods
The diagnosis performance of FS and SSI are Liver stiffness mapping using SSI
compared by using receiver operating characteristic The Young’s modulus corresponding to the stiffness
(ROC) curves and box-and-whisker curves on the same of the liver tissues are presented for 4 patients in Figure 4.
cohort. A patient was assessed as positive or negative according
to whether the noninvasive marker value was sponding B-mode images on which the fat and muscle
The elasticity mapping is superimposed with the corre-
greater than or less than to a given cutoff value, respectively.
Connected with any cutoff value is the probability the elasticity is mapped only in the liver region.
region are well differentiated from the liver region and
of a true positive (sensitivity) and the probability of a true Figure 4a, b, c and d show the elasticity mapping for
negative (specificity). The ROC curve is a plot of patients who have been classified as predicted fibrosis
sensitivity vs. (1-specificity) for all possible cutoff values. levels F1, F2, F3 and F4, respectively.
The median elasticity derived from these maps are
Fig. 4. Bidimensional liver elasticity maps assessed using the
supersonic shear imaging (SSI) technique superimposed to
the corresponding B-scan. The Young’s modulus representing
the liver stiffness is represented in color levels. (a): patient
59 - F1. E 5 4.78 6 0.83 kPa (b): patient 51 - F2. E 5 10.64 6
1.10 kPa (c): patient 39 - F3. E 5 14.52 6 2.20 kPa (d): patient
Muller et al. UMB 2009; 35: 219-29
Bavu et al. UMB 2011;37: 1361-73

Biomarqueurs vs. FibroScan
Avantages & inconvénients
Critères Biomarqueurs FibroScan
Détection cirrhose
Bonnes
performances
Meilleures
performances
Applicabilité 95% 81%
Rapidité résultats 1-3 jours 10 min
Castera L. Gastroenterology 2012; in press

Plan
Intérêt pour prédire les complications
- Hypertension portale
- Carcinome hépatocellulaire
Intérêt pour prédire la survie

-TSAO ET AL.
Now There Are Many (Stages) Where Before There
Was One: In Search of a Pathophysiological
Classification of Cirrhosis
Guadalupe Garcia-Tsao, 1 Scott Friedman, 2 John Iredale, 3 and Massimo Pinzani 4
HEPATOLO
HEPATOLOGY, Vol. 51, No. 4, 2010
changes, and more faithfully reflects its progression, notably activated reversibility
and prognosis, ultimately linkingbroblasts, these param-
as well as key cytokines su
hepatic stellate ce
eters to clinically relevant outcomes andgrowth therapeutic factor and transforming grow
strategies. The Child-Pugh and Model for roles End-Stage of bone marrow–derived cells a
epithelial-mesenchymal transition a
Liver Disease (MELD) scores are currently deployed to
tion, but it is unlikely that these sour
define prognosis by modeling hepatic dysfunction, but do
provide a major contribution to hep
not provide direct evidence of the stage or dynamic trix in chronic state human liver disease
of cirrhosis. The need for more refined cirrhosis proteases staging thatisdegrade scar and the p
especially germane given the increasing use them of effective are better understood. Moreo
antiviral treatments in patients with hepatitis understanding B virus of distinctive pathoge
(HBV) and hepatitis C virus (HCV) cirrhosis at different and thestages and from differ
emergence of effective antifibrotic agents, that wherein fibrosiswe
may be customized acco
and underlying cause.
must define favorable or unfavorable endpoints that correlate
with a discrete clinical outcome in patients with
Cirrhosis in experimental model
may be reversible. 24 Following withd
cirrhosis.
stimulus, a dense micronodular cirrh
The normal liver has only a small amount modeling of fibrous to a more attenuated, m
tissue in relation to its size. As a result of continued However, liver some septa will persist, like
injury, however, there is progressive accumulation laid down of early extracellular
matrix, or scar. Although different“mature” chronic liver (i.e., cross-linked).
in the injury and ar
diseases are characterized by distinct patternsMoreover, of fibrosisin experimental mode
deposition, 1 may be the site of neoangiogenesis.
the development of cirrhosis represents a
already present in chronic inflamm
common outcome leading to similar clinical
concurrent
consequences
that impose an increasing burden inaclinical role prac-
the pathogenesis of portal
with the fibrogenic proce
tice.
effectiveness of therapeutic angioge
only improving fibrosis, but also in
For more than a century and a half, the description
of a liver as “cirrhotic” was sufficient to connote
both a pathological and clinical status, and to assign
the prognosis of a patient with liver disease. However,
as our interventions to treat advanced liver disease
have progressed (e.g., antiviral therapies), the inadequacy
of a simple one-stage description for advanced fibrotic
liver disease has become increasingly evident. Until recently,
refining the diagnosis of cirrhosis into more than
one stage hardly seemed necessary when there were no
interventions available to arrest its progression. Now,
however, understanding the range of potential outcomes
based on the severity of cirrhosis is essential in order to
predict outcomes and individualize therapy. This position
paper, rather than providing clinical guidelines, attempts
to catalyze a reformulation of the concept of cirrhosis
from a static to a dynamic one, creating a template for
further refinement of this concept in the future.
We already make the clinical distinction between compensated
and decompensated cirrhosis, and are incrementally
linking these clinical entities to quantitative variables
such as portal pressure measurements and emerging noninvasive
diagnostics. Moreover, mounting evidence suggests
that cirrhosis encompasses a pathological spectrum
which is neither static nor relentlessly progressive, but
rather dynamic and bidirectional, at least in some pa-
cation of chronic tients. liver Thus, disease there a pressing basedneed on histological, redefine cirrhosis Garcia-Tsao clinical, hemodynamic, et al. Hepatology and biological 2010; sure, parameters. is suggested 51: 1445-9. by dataIn fromthe anima
Anatomical-Pathological Context
n
, there is no clinical a manner
evidence
that better
of
recognizes
cirrhosis,
itsthe underlying
HVPGrelation-
been established in humans.
is below 6 mmHg, and at this stage there is fibrogenesis and 27 Altho
ne

Un peu d’histoire
“ Quand le foie est dur
le pronostic est mauvais ”
Socrate (V ème siècle av J.C)

Mesure de l’élasticité hépatique
Normale
5.5
Cirrhose
15
?
65
3
75 kPa

Valeur pronostique de l’élasticité
hépatique au cours de la cirrhose ?
15 27 49 54
75
63 kPa
VO grade II / III
Ascite
N=711 patients CLD
F3F4 144
CHC
RVO
Foucher et al. Gut 2006; 55: 403-8.

Plan
Intérêt pour prédire les complications
- Hypertension portale
- Carcinome hépatocellulaire
Intérêt pour prédire la survie

Importance du gradient portal (HVPG)
HVPG
≥ 10 mm Hg
Risque
Formation de VO
Décompensation
CHC
≥ 12 mm Hg
≥ 16 mm Hg
Rupture de VO
Décès
Garcia-Tsao & Bosch. N Engl J Med 2010; 362: 823-32

Corrélation élasticité hépatique et HVPG
30
24
Pearson’s coefficient = 0.84
p < 0.001
HVPG (mm Hg)
18
12
6
0
0
8
16
24
32
40
48
56
64
72
80
Liver stiffness (kPa)
N= 124 patients avec
récidive VHC post TH Carrion et al. Liver Transpl 2006; 12: 1791-8.

Correlation élasticité hépatique et HVPG
HEPATOLOGY, Vol. 45, No. 5, 2007
oui… mais
R²= 0.61
P

Correlation élasticité hépatique et HVPG
HEPATOLOGY, Vol. 45, No. 5, 2007
oui… mais
R²= 0.61
P10-12 mmHg
R²= 0.67
la pression P

Corrélation avec les Varices
Oesophagiennes
P

Prédiction des VO grade II-III
Fibroscopie AUROC = évitée 0.83 69 %
46%
54%
3 19
75
VO < II
95%
4 patients
Mal classés
VO ≥ II
48%
47 patients
Mal classés
Kazemi et al. J Hepatol 2006; 45: 230-5

Performance pour la prédiction des VO
FibroScan
ients Patients Authors, Etiologies Etiologies
PatientsStudy
Etiologies Child-Pugh Child-Pugh Study End
(n) [Ref.] design (n) design A (%) A design (%) point
]
]
]
]
]
]
]
]
165 Kazemi CLD CLDRetro.
165 Retro. CLD n.a. n.a. Retro. OV
et al., [45] mono. mono. mono. LOV
End Prevalence Child-Pugh Prevalence Cut-offs End AUC Cut-offs Prevalence Se AUC SpCut-offs
SePPV
Sp AUC NPV PPV Se +LR NPV Sp -LR +LR Saved PPV -LR NPV Saved +LR
point OV A (%)
OV (kPa) (%) point (kPa) OV (%) (%)(kPa)
(%) (%) (%) (%) (%) (%) (%) endoscopy (%) (%)
(%)
endos
(%)
OV 45 n.a.
LOV 28
4513.9
OV
2819.0
LOV
0.83 13.9 45
0.84 19.0 28
95
91
0.83 43 13.9 9557
0.84 60 19.0 9148
47 Vizzutti HCV HCV Pro. 47 Pro. HCV 60 60 Pro. OV OV 660 6617.6 OV 0.76 17.6 66 90 0.76 43 17.6 9077 430.76 66 7790 1.6 6643 0.23 1.6 74 77 0.23 66 741.6
et al., [36] mono. mono. mono.
211 Pritchett CLD CLDRetro.
211 Retro. CLD n.a. n.a. Retro. OV
et al., [48] mono. mono. mono. LOV
OV
n.a.
LOV 37
n.a. 19.5 OV
3719.8
LOV
89 Bureau CLD CLDPro.
89 Pro. CLD 34 34 Pro. OV OV 72 34 7221.1
OV
et al., [37] mono. mono. mono. LOV LOV 48 4829.3
LOV
70 Castera HCV HCV Retro. 70 Retro. HCV 100 100 Retro. OV OV 36 100 3621.5
OV
et al., [46] mono. mono. mono. LOV LOV 19 1930.5
LOV
0.74 19.5 n.a. 76
0.76 19.8 37 91
0.85 21.1 72
0.76 29.3 48
0.84 21.5 36
0.87 30.5 19
84
81
76
77
0.74 66 19.5 7656
0.76 56 19.8 91 91
0.85 71 21.1 84
0.76 61 29.3 81
0.84 78 21.5 7668
0.87 85 30.5 7756
102 Pineda, HIV-HCV HIV-HCV Pro. 102 Pro. HIV-HCV 76 76 Pro. CROV* CROV* 13 76 1321.0 CROV* 0.71 21.0 13 100 0.71 32 21.0 100 25 320.71 100 25100 1.5 100 32 0.0 1.5 44 25 0.0 100 441.5
et al., [47] multi. multi. multi.
183 Nguyen CLD CLDRetro.
183
58 et HCV/HBV al. [49] HCV/HBV mono. 58
103 Alcohol Alcohol 103
Retro. CLD 63 63 Retro. LOV LOV 22 63 2248.0
LOV 0.76 48.0 22
mono. HCV/HBV mono. 17 1719.8
0.73 19.8 17
Alcohol
25 2547.2
0.77 47.2 25
73
89
85
0.76 73 48.0 7344
0.73 55 19.8 8927
0.77 64 47.2 8544
124 Malik CLD CLDRetro.
124 Retro. CLD n.a. n.a. Retro. OV OV 51 n.a. 5120.0 OV 0.85 20.0 51 n.a. 0.85 n.a. 20.0 n.a. 80 n.a. 0.85 75 80n.a. 75n.a. n.a. 80 n.a. 75 n.a.
et al., [50] mono. mono. mono.
430.83
91
60.84
95
660.74
82
560.76
55
710.85
610.76
780.84
850.87
94
730.76
90
550.73
97
640.77
93
5795
1.7
4891
2.3
5676
2.2
91 91 2.1
9143
0.13
9560
0.14
8266
0.36
556
0.16
1.7 66 57
2.3 69 48
2.2 n.a. 56
2.1 69 91
Thabut, Moreau & Lebrec. Hepatology 2011; 53: 683-94
Castera, Pinzani & Bosch. J Hepatol 2012; in press
84 2.9
81 2.1
6876
3.5
5677
5.1
4473
2.7
2789
2.0
4485
2.4
71 0.22
61 0.31
8478
0.31
9485
0.27
9073
0.37
9755
0.20
9364
0.23
2.9 81
2.1 71
3.5 73 68
5.1 79 56
2.7 73 44
2.0 60 27
2.4 69 44
0.13 91
0.14 95
0.36 82
0.16 55
0.22
0.31
0.31 84
0.27 94
0.37 90
0.20 97
0.23 93
661.7
692.3
n.a. 2.2
692.1
812.9
712.1
73.5
795.1
732.7
602.0
692.4

Performance pour la prédiction des VO
Biomarqueurs
Test, Patients
[Ref.] (n)
Etiologies Test, PatientsStudy
Etiologies Patients Child-Pugh Study EtiologiesEnd
Child-Pugh Study Prevalence Child-Pugh End Cut-offs Prevalence End AUCPrevalence
Cut-offs Se Sp AUCut-offs
PPV Se
[Ref.] (n) design (n) A (%) design point A design (%) OV A point (%)
(kPa) OV point (%) OV (kPa)
(%) (%)(kPa)
(%)
AUC Sp NPV
(%)
PPV Se +LR Sp NPV -LRPPV
+LR Saved NPV -LR +LRSaved
-LR
(%)
(%) (%) endoscopy (%) endoscopy
(%) (%)
Platelet 510 CLD Platelet 510 Retro. CLD 510 79Retro.
CLD CROV* 79Retro.
2879 CROV* 89 28CROV* 0.6528 89 55 75 0.65 894955 0.65 75 80 49 55 2.17 75 80.61492.17 66 800.61 2.17 66 0.61
count, [54] count, [54] multi. multi. multi.
AST/ALT 510 CLD AST/ALT 510 Retro. CLD 510 79Retro.
CLD CROV* 79Retro.
2879 CROV* 1.1 28CROV* 0.6428 1.1 71 57 0.64 1.16071 0.64 57 82 60 71 1.63 57 82 0.52601.63 61 820.52 1.63 61 0.52
ratio, [54] ratio, [54] multi. multi. multi.
APRI, 510 [54] CLD APRI, 510 [54] Retro. CLD 510 79Retro.
CLD CROV* 79Retro.
2879 CROV* 1.5 28CROV* 0.5728 1.5 57 0.57 1.53557 0.57 76 357 1.30 57 0.76351.30 57 760.76 1.30 57 0.76
multi. multi. multi.
Forns’, 510 CLD Forns’, 510 Retro. CLD 510 79Retro.
CLD CROV* 79Retro.
2879 CROV* 8.8 28CROV* 0.6628 8.8 71 62 0.66 8.85871 0.66 62 82 58 71 1.88 62 82 0.47581.88 66 820.47 1.88 66 0.47
index, [54] index, [54] multi. multi. multi.
Lok 510 CLD Lok 510 Retro. CLD 510 79Retro.
CLD CROV* 79Retro.
2879 CROV* 1.5 28CROV* 0.7028 1.5 71 68 0.70 1.55071 0.70 68 84 50 71 2.25 684 0.42502.25 69 840.42 2.25 69 0.42
index, [54] index, [54] multi. multi. multi.
Fib-4, 510 [54] CLD Fib-4, 510 [54] Retro. CLD 510 79Retro.
CLD CROV* 79Retro.
2879 CROV* 4.3 28CROV* 0.6328 4.3 71 56 0.63 4.34071 0.63 56 82 40 71 1.60 56 82 0.53401.60 820.53 1.60 60 0.53
multi. multi. multi.
Fibroindex, 510 CLD Fibroindex, 510 Retro CLD 510 79Retro
CLD CROV* 79Retro
2879 CROV* 2.5 28CROV* 0.6528 2.5 51 76 0.65 2.55051 0.65 76 75 50 51 2.06 76 75 0.65502.06 70 750.65 2.06 70 0.65
[54] [54] multi. multi. multi.
Fibrotest®, 99 CLD Fibrotest®, 99 Retro. CLD 99 42Retro.
CLD LOV 42Retro.
7242 LOV 0.85 72LOV 0.772 0.8584 53 0.77 0.85 8684 0.77 53 50 86 84 1.78 53 50.28861.78 500.28
1.78 0.28
[55] [55] mono. mono. mono.
PC/SDR, 218 CLD PC/SDR, 218 Pro. CLD 218 51Pro.
CLD OV 51Pro.
5451 OV 909 54OV 0.8654 90992 67 0.86 9097792 0.86 67 87 77 92 2.77 67 87 0.13772.77 80 870.13 2.77 80 0.13
[56] [56] multi. multi. multi.
Capsule 288 CLD Capsule 288 Pro. CLD 288 69Pro.
CLD OV 69Pro.
6369 OV n.a. 63OV
endoscopy,
[57]
endoscopy, multi.
[57]
multi. LOV multi. 27 LOV n.a. 27LOV
Lapalus 120 CLD Lapalus 120 Pro. CLD 120 48Pro.
CLD OV 48Pro.
6248 OV n.a. 62OV
et al., [58] et al., [58] multi. multi. LOV multi. 29 LOV n.a. 29LOV
n.a. 63 n.a. 84
n.a. 27 n.a. 78
n.a. 62 n.a. 77
n.a. 29 n.a. 77
88 n.a. n.a. 9284
96 n.a. n.a. 8778
86 n.a. n.a. 9077
88 n.a. n.a. 7577
n.a. 88 77
n.a. 96 92
n.a. 86 69
n.a. 88 90
92 84 7.00 88 77 0.18927.00
86 770.18
7.00 86
878
19.5096
92 0.238719.50
79 920.23
19.50 79
90 77 5.42 869
0.28905.42
690.28
5.42
75 77 6.69 88 90.26756.69
85 900.26 6.69 85
Thabut, Moreau & Lebrec. Hepatology 2011; 53: 683-94
Castera, Pinzani & Bosch. J Hepatol 2012; in press
0.18
0.23
0.28
0.26

Performance pour la prédiction des VO
Biomarqueurs vs. FibroScan
Endoscopies évitées
VO
VO II-III
Ratio ASAT/ALAT
Index de Lok
FibroScan
Fibrotest
Taux de Prothrombine
Taux de plaquettes
APRI
81%
77%
73%
70%
70%
69%
66%
76%
77%
79%
64%
79%
76%
63%
N=70 patients cirrhose C
Castera et al. J Hepatol 2009; 50: 59-68.

Combinaison élasticité hépatique
taille de la rate + plaquettes = LSPS
Liver stiffness Spleen diameter to Platelet ratio Score
LSPS =
LSM (kPa) x Spleen diameter (cm)
Platelet (10 9 /L)
N = 401 patients VHB cirrhotiques (evaluation 280; validation 121)
VO « haut risque » (Baveno V): 32%
Kim et al. Am J Gastroenterol 2010; 105:1382-90

LSPS
Performance détection VO à «haut risque »
Fibroscopie AUROC évitée 0.95 83%
62.8%
24.8%
3.5 5.5
Absence de VOHR
95%
VOHR +
93%
Kim et al. Am J Gastroenterol 2010; 105:1382-90

1658
LIVER LIVER
Kim et al.
Entire population (n = 577)
1658
LIVER
1.0
LSPS
Patients with LSPS ≥ 5.5
Risque
Entire
de rupture de VO
Patients population with (n LSPS = 577) 3.5–5.5
Cumulative EV bleeding risk
Cumulative EV bleeding risk
Kim et al.
0.8
1.0
0.6
0.8
0.60.4
0.40.2
0.20.0
Cumulative EV bleeding risk
0
Patients with Entire LSPS population < 3.5 (n = 577)
Patients with LSPS ≥ 5.5
1.0
Patients with LSPS Patients 3.5–5.5 with LSPS ≥ 5.5
Patients with LSPS < 3.5
Patients with LSPS 3.5–5.5
0.8
0.6
0.4
0.2
Patients with LSPS < 3.5
1 2 3 4
No. at 0.0 risk
Years
0.0
No. at risk
Patients with
0 107 1 76 2 51 3 33 4 18
LSPS N=577 ≥ 5.5 patients VHB
Subgroup 2
Kim et al. Am J Gastroenterol 2011; 106:1654-62
No. at risk
0.0
Years
Patients with
Subgroup 1
Cumulative EV bleeding risk
1.0
0.8
0.6
0.4
0.2
Cumulative EV bleeding risk
1
0
0
0
0
0
0

Résumé
L’élasticité hépatique est bien corrélée avec le
gradient portal et la présence (taille?) des VO.
Les performances de l’élastométrie et des
biomarqueurs sont cependant insuffisantes pour
remplacer la fibroscopie pour la recherche de
VO.

Plan
Intérêt pour prédire les complications
- Hypertension portale
- Carcinome hépatocellulaire
Intérêt pour prédire la survie

factors considered significant are older age, male gender,
and serum albumin level.
L
Liaisons dangereuses ?
chro
liver
adva
error
p

Elasticité hépatique & cancer du foie
890 JUNG, KIM, ET AL.
Hépatite B
N= 1130 patients VHB
using LSM an
ferences in the
nalysis, we ass
histology at en
patients had L
>13 kPa. In p
of HCC estim
cantly differe
5.1%) and p
(0.87% versus
contrast, amo
developed m
diagnosed ac
55.9%) than w
Jung et al. Hepatology 2011; 53: 885-94

Plan
Intérêt pour prédire les complications
- Hypertension portale
- Carcinome hépatocellulaire
Intérêt pour prédire la survie

Elasticité hépatique & survie
Koch et al. Critical Care 2011, 15:R266
en réanimation
http://ccforum.com/content/15/6/R266
Page 5 of 15
Figure 1 Liver stiffness measurements in the intensive care unit (ICU) setting. Critically ill medical patients were included into this study
uponN=108 admission topatients; the ICU. Transient 8 liver cirrhotiques
elastography was assessed at admission, on Day 3, on Day 7, and subsequently once per week. The
setting of our study is displayed in the upper panel; stiffness measurements were performed at the bedside with a portable FibroScan ®
apparatus, alongside classical hemodynamic and respiratory monitoring as well as typical ICU treatment measures. The numbers of patients
Koch et al. Crit Care 2011; 15: R266

Page 11 of 15
Page 11 of 15
Koch et al. Critical
Elasticité
Care 2011, 15:R266
hépatique
Koch et al. Critical Care 2011,
&
15:R266
survie
http://ccforum.com/content/15/6/R266
http://ccforum.com/content/15/6/R266
Page 12 of 1
en réanimation
Survie en réanimation
Survie après sortie réanimation
Sans cirrhose
Sans cirrhose
Koch et al. Crit Care 2011; 15: R266

S
an
: 0.815 (0.727-0.903)
1.0
the prediction of liver
0.2
Elasticité hépatique
survie
0.0
sans complications
0 200 400 600 800
Days
84.1%, respectively
B
1.0
LS

ICAL–LIVER,
CLINICAL–LIVER,
PANCREAS, AND AND
IARY BILIARY TRACT TRACT
Elasticité hépatique & survie
Figure 2. Overall survival probability according to liver stiffness, biomarkers, and liver biopsy. (A) O
N=1457 Figure patients 2. Overall VHC
the diagnosis of severe survival fibrosis Vergniol probability or cirrhosis. et according al. (B) Overall Gastroenterology to survival liver stiffness, according biomarkers, 2011; to different 140: and cut-offs 1970-9 liver biops of live

Biomarqueurs & survie
Fibrotest
Overall survival probability according to liver stiffness, biomarkers, and liver biopsy. (A) Overall survival according to published cut-offs for
sis of severeN=537 fibrosis or cirrhosis. patients (B) Overall VHC survival according to different cut-offs of N=1457 liver stiffness patients (kPa). OverallVHC
survival (95% confidence
ing liver stiffness: 9.5 kPa: 96% (94%–98%); 9.5 kPa: 77% (72%–82%); 20 kPa: 66% (61%–71%); 30 kPa: 57% (50%–64%); 40
37%–57%); Ngo et 50 al. kPa: Clin 42% Chem (29%–55%). 2006; (C) 52: Overall 1887-96 survival according to different cut-offs of FibroTest. Overall survival (95% confidence
Vergniol et al. Gastroenterology 2011; 140: 1970-9

Biomarqueurs & survie
ELF score
Hepatology
planeMeier curve of
s from liver-related
anced liver fibrosis
planeMeier curve of
s from liver-related
sy. *HRs derived
ional hazards model
sted for age, gender,
ion, smoking,
disease, treatment
tre of recruitment.
N=457 patients
Parkes et al. Gut 2010; 59: 1245-51

CPT in predicting 1-year mortality. As expected, the performance
of each index / test deteriorated at later time points but HA and CPT
remained highly predictive at year 3, and HA at year 5. Figure 1
shows survival plots for several of the predictors
APRI
of a liver-related
0.0
outcome using the cutoff values as shown. As demonstrated in the
Years
Surv
Biomarqueurs & survie
0.2
0 1 2 3 4 5 6 7
Surv
1.0
APRI
1.0
CPT
0.8
< 1.5
0.8
≤ 6
Survival function
0.6
0.4
> 1.5
Survival function
0.6
0.4
> 6
Survival function
0.2
0.2
7
0.0
0 1 2 3 4 5 6 7
Years
0.0
0 1 2 3 4 5 6 7
Years
MELD
N=303patients
1.0
VHC; Figure 207 1 . Survival VIH curves for each of the assessed markers using the cutoff values s
Nunes et al. Am J Gastroenterol 2010; 105: 1346-53

Méthodes non invasives & survie
résumé
Tests
Patients
n
Etiologie
Type étude
Durée suivi
Complications
n
AUC
Décès
n/n*
AUC
Fibrotest®
537
VHC
Prospective
5 ans
29
0.96
20/9
0.95
1457
VHC
Prospective
5 ans
-
-
77/39
0.80
1074
VHB
Retro + prospective
4 ans
50
0.89
36/27
0.94
218
OH
Prospective
8 ans
-
-
85/42
0.79
Fibrometre®
218
OH
Prospective
8 ans
-
-
85/42
0.80
Hepascore®
218
OH
Prospective
8 ans
-
-
85/42
0.78
APRI
303
VIH-VHC
Prospective
3 ans
-
-
79/33
0.88
FIB-4
303
VIH-VHC
Prospective
3 ans
-
-
79/33
0.87
ELF®
161
CBP
Prospective
7 ans
42
0.68
1
-
457
MCF
Prospective
7 ans
61
0.87
39
-
Elastométrie
100
MCF
Prospective
2 ans
41
0.84
0
-
1457
VHC
Prospective
5 ans
-
-
77/39
0.82

Take Home messages
Les méthodes non invasives sont utilisées de façon
croissante en pratique notamment pour le diagnostic de
cirrhose mais ne peuvent remplacer la fibroscopie pour la
recherche des VO.
La mesure de l’élasticité hépatique pourrait être
intéressante pour classer les patients cirrhotiques en
groupes à risque en termes de complications et de survie.