Profiling of routine serum parameters and APP evolution in

cirrhosis following HCV eradication for stratification of HCC risk: a trajectory clustering analysis from the ANRS CO12 CirVir cohort

*Service d’Hépatologie

Hôpital Jean Verdier

Bondy – Université Paris 13

Pierre Nahon* , Richard Layese, Valérie Bourcier, Carole Cagnot,

Patrick Marcellin, Dominique Guyader, Stanislas Pol, Dominique Larrey,

Françoise Roudot-Thoraval, Etienne Audureau,

and ANRS CO12 CirVir group

Financial Disclosures

• Honoraria or consultation fees: Abbvie, Astra-Zeneca, Bayer,

Bristol-Myers Squibb, Gilead Sciences, IPSEN

Identifying residual risk of HCC following HCV eradication in compensated

cirrhosis: Machine learning approaches (decision tree analysis)

CirVir CO12

JCO, in revision

N=836

Longitudinal and sequential assessment of biological

parameters for early HCC detection

Are routine serum parameters estimating liver functionOr inflammation and AFP levels correlated with HCC development?

What influence in case of control of the cause of liver disease ?

Objectives of the study

In patients with compensated HCV-related cirrhosis included in HCC surveillance programsand baseline active viral replication :

To identify specific longitudinal profiles of routine serum parameters

(RSP) and AFP evolution before and after HCV eradication in patients

with cirrhosis which could be associated with higher risk of HCC

occurrence.

Based on the analysis of protocol-driven collected data from a nationalprospective cohort covering INF and DAA therapeutic eras

The ANRS CO12 CirVir prospective cohort:

inclusion criteria - design

Inclusions

n=1822

FOLLOW-UP

Median: 67.5 months

March

2006

June

2012

December

2016End point

DESIGN

• Biopsy-proven Child-Pugh A cirrhosis

• HCV- or HBV-related cirrhosis

• Anti-HCV+ or HBsAg+

• Absence of previous decompensation or HCC

Trinchet JC, et al. Hepatology 2015, Ganne et al, Hepatology 2016, Nahon et al, Gut 2017, Nahon et al, Gastroenterology 2017 and 2018

• Prospective multicentre study (35 French hospitals)

• Visits: every 6 months (HCC screening)

• Biobanks: at inclusion and every year

Statistical analysis

• Serum AFP and RSP (ALT, AST, GGT, PT, albumin, bilirubin, platelets) were

assessed every 6 months.

• For the present analysis, only patients with at least 3 available AFP and RSP

sequential measurements were included

– Population #1: No/before SVR

• Patients who did not achieve SVR

• OR period before achievement of SVR

– Population #2: After SVR

• Period after achievement of SVR

• Trajectory analysis was based on a k-means approach for clustering individuals with

similar trajectories of AFP and RSP over time.

SVR

…

…

Flow-chart

N=106 excluded

• N=69 Incorrect inclusion criteria

• N=6 Withdrawal of consent

• N=31 HCV/HBV co-infection

N=606 excluded

• N=258 achieved SVR before inclusion

• N=348 with <3 sequential measurements on AFP/RSP

Population #1 No SVR/before SVR

N=717

Population #2 After SVR

N=413 (57.6%)

HCV-infected patientsN=1429

Considered patients

N=1323

Included patients

N=717

Baseline characteristicsBaseline characteristics (N=717)

Gender, males 440 (61.4%)

Age, years 57.1 (±10.5)

HCV Genotype 1 522 (74.3%)

Body Mass Index, kg/m² Mean (±SD) 26.4 (±5.0)

Normal weight <25 272 (42.0%)

Overweight [25-30[ 260 (40.2%)

Obesity ≥30 115 (17.8%)

Past excessive alcohol intake 222 (32.1%)

Diabetes 143 (19.9%)

Dyslipidaemia 42 (5.9%)

Hypertension 197 (27.5%)

Oesophageal varices 199 (33.7%)

Creatinine, µmol/L 72.9 (±31.1)

eGFR 99.2 (±25.9)

Total bilirubin, µmol/L 15.0 (±8.4)

AST IU/L 86.4 (±56.1)

xN 2.4 (±1.6)

ALT IU/L 101.6 (±79.4)

xN 2.4 (±1.9)

GGT IU/L 154.2 (±159.4)

xN 3.3 (±3.6)

Alkaline phosphatase IU/L 119.2 (±70.7)

xN 0.9 (±0.4)

Serum albumin, g/L 40.5 (±4.7)

Alpha-foetoprotein, ng/mL 15.5 (±29.9)

Platelet count, 10^3/mm3 131.4 (±56.6)

Prothrombin t ime (%) 86.4 (±12.5)

3 clusters Population #1 No SVR/before SVR, N=717

« Inflammatory » and high AFP levels (n=190, 26%)

« Liver failure » (n=198, 28%)

Least impaired values (n=329, 46%)

Cluster A

Cluster B

Cluster C

ALT AST

AFPGGT

3 clusters Population #1 No SVR/before SVR, N=717

« Inflammatory » and high AFP levels (n=190, 26%)

« Liver failure » (n=198, 28%)

Least impaired values (n=329, 46%)

Cluster A

Cluster B

Cluster C

PT PLATELETS

BILIRUBINALBUMIN

Influence of pre-SVR clusters on HCC riskTotal HCC=142 (19.8%)

Cluster CCluster BCluster A

P<0.001

« Inflammatory » and high AFP

levels (n=190, 26%)

« Liver failure »

(n=198, 28%)

Least impaired values

(n=329, 46%)

Cluster A

Cluster B

Cluster C

HC

C c

um

ula

tive

in

cid

en

ce

Time (months)

Population #1 No SVR/before SVR, N=717

Population #1 No SVR/before SVR, N=717

« Inflammatory » and high AFP levels (n=190, 26%, HCC=25.3%)

« Liver failure » (n=198, 28%, HCC=26.8%)

Least impaired values (n=329, 46%, HCC=12.5%)

Cluster A

Cluster B

Cluster C

Cluster C Cluster B Cluster A

N=329 N=198 N=190

Mean (±SD) Mean (±SD) Mean (±SD) p-values

Gender, males 212 (65.2%) 113 (56.5%) 115 (59.9%) 0.121

Age, years 56.6 (±10.7) 59.5 (±10.7) 55.3 (±9.4) 0.0003

HCC occurrence (%) 41 (12.5%) 53 (26.8%) 48 (25.3%) <0.0001

Death (%) 44 (13.4%) 41 (20.7%) 62 (32.6%) <0.0001

Past excessive alcohol intake 108 (34.1%) 55 (28.6%) 59 (32.4%) 0.444

Body Mass Index, kg/m² 25.9 (±4.9) 27.1 (±5.3) 26.5 (±4.6) 0.039

Diabetes 56 (17.2%) 45 (22.5%) 42 (21.9%) 0.251

Dyslipidaemia 22 (6.8%) 8 (4.0%) 12 (6.3%) 0.408

Hypertension 73 (22.5%) 64 (32.0%) 60 (31.3%) 0.023

Oesophageal varices 51 (20.4%) 95 (54.3%) 53 (32.1%) <0.0001

HCV Genotype 1 236 (73.8%) 150 (76.5%) 136 (72.7%) 0.835

AS

AT

(U

LN

)G

GT

(UL

N)

Population #2 After SVR, N=413

Elevated biochemical parameters (n=95, 23.0%, HCC=13.7%)

Persisting liver impairment (n=109, 26.4%, HCC=15.6%)

Least impaired values (n=228, 55.2%, HCC=7.5%)Cluster A

Cluster B

Cluster C

AF

P

AST ALT

AFPGGT

TP

(%

)

BIL

IRU

BIN

(U

LN

)

Population #2 After SVR, N=413

Elevated biochemical parameters (n=95, 23.0%, HCC=13.7%)

Persisting liver impairment (n=109, 26.4%, HCC=15.6%)

Least impaired values (n=228, 55.2%, HCC=7.5%)Cluster A

Cluster B

Cluster C

PT PLATELETS

BILIRUBINALBUMIN

Population #2 After SVR, N=413

Elevated biochemical parameters

(n=95, 23.0%, HCC=13.7%)

Persisting liver impairment

(n=109, 26.4%, HCC=15.6%)

Least impaired values

(n=228, 55.2%, HCC=7.5%)Cluster A

Cluster B

Cluster C

HC

C c

um

ula

tive

in

cid

en

ce

Time (months)

Influence of pre-SVR clusters on HCC riskTotal HCC=47 (11.4%)

Population #2 After SVR, N=413

Elevated biochemical parameters (n=95, 23.0%, HCC=13.7%)

Persisting liver impairment (n=109, 26.4%, HCC=15.6%)

Least impaired values (n=228, 55.2%, HCC=7.5%)Cluster A

Cluster B

Cluster C

Cluster A Cluster B Cluster C

N=228 N=109 N=95

Mean (±SD) Mean (±SD) Mean (±SD) p-values

Gender, males 137 (63.4%) 75 (65.8%) 50 (60.2%) 0.727

Age, years 54.6 (±9.1) 57.6 (±9.5) 53.0 (±8.4) 0.001

HCC occurrence 17 (7.5%) 17 (15.6%) 13 (13.7%) 0.026

Death 8 (3.7%) 6 (5.3%) 4 (4.8%) 0.783

Past excessive alcohol intake 73 (34.8%) 33 (29.2%) 23 (29.1%) 0.486

Body Mass Index, kg/m² 25.9 (±4.9) 26.7 (±4.5) 26.4 (±4.3) 0.322

Diabetes 33 (15.3%) 19 (16.7%) 13 (15.7%) 0.947

Dyslipidaemia 19 (8.8%) 5 (4.4%) 2 (2.4%) 0.077

Hypertension 52 (24.1%) 33 (28.9%) 15 (18.1%) 0.212

Oesophageal varices 23 (13.8%) 45 (45.5%) 14 (22.2%) <0.0001

HCV Genotype 1 138 (65.4%) 92 (82.1%) 57 (70.4%) 0.009

Treatedtoo late? ?

Conclusions

• This exploratory descriptive approach underlines that liver function

impairment (“liver failure cluster”) or elevated biochemical parameters

(“inflammatory cluster”) in HCV cirrhosis define two different profiles

representing more than 50% of compensated patients in whom the risk of

HCC is increased.

• This clustering approach also highlighted that these 2 profiles can persist

despite SVR, and define subgroups of patients with an increased residual

risk of HCC

• These analyses based on novel statistical approaches suggest that 1) HCC

surveillance could be refined and improved according to the longitudinal

monitoring of these routine parameters over time, 2) these clustering

approaches could be enriched by the incorporation of novel circulating

biomarkers useful for HCC early detection.

• Centres: Aix en Provence, Amiens,

Angers, Besançon, Bicêtre, Bobigny,

Bondy, Bordeaux, Caen, Clermont-

Ferrand, Clichy, Créteil, Grenoble,

Le Mans, Lille, Lyon, Marseille, Nancy,

Nice, Paris-Cochin, Paris Institut

Montsouris, Paris Pitié Salpêtrière, Paris-

St Antoine, Paris-Tenon, Pessac, Reims,

Rouen, Rennes, St Laurent du Var,

Suresnes, Toulouse, Tours

Aix-en-

Provenc

e

Marseille

Nice

St

Laurent-

du-Var

Montpellier

Toulouse

Bordeaux

Pessac

Clermont-

Ferrand

Lyon

Grenoble

Besançon

Nancy

Reims

Lille

AmiensRouen

Rennes

Caen

Tours

Poitiers

Angers

Le Mans Ile-de-France

(n= 11)

35 centres

ANRS CO12 CirVir group

Trinchet JC, et al. Hepatology 2015;62:737–50. ANRS, Agence Nationale de Recherches sur le Sida et les hépatites