Accepted Manuscript

Incidence of Hepatocellular Carcinoma After Direct Antiviral Therapy for HCV inPatients With Cirrhosis Included in Surveillance Programs

Pierre Nahon, Richard Layese, Valérie Bourcier, Carole Cagnot, Patrick Marcellin,Dominique Guyader, Stanislas Pol, Dominique Larrey, Victor De Lédinghen, DenisOuzan, Fabien Zoulim, Dominique Roulot, Albert Tran, Jean-Pierre Bronowicki,Jean-Pierre Zarski, Ghassan Riachi, Paul Calès, Jean-Marie Péron, Laurent Alric,Marc Bourlière, Philippe Mathurin, Jean-Frédéric Blanc, Armand Abergel, LawrenceSerfaty, Ariane Mallat, Jean-Didier Grangé, Pierre Attali, Yannick Bacq, ClaireWartelle, Thông Dao, Dominique Thabut, Christophe Pilette, Christine Silvain,Christos Christidis, Eric Nguyen-Khac, Brigitte Bernard-Chabert, David Zucman,Vincent Di Martino, Angela Sutton, Françoise Roudot-Thoraval, Etienne Audureau

PII: S0016-5085(18)34781-4DOI: 10.1053/j.gastro.2018.07.015Reference: YGAST 61999

To appear in: GastroenterologyAccepted Date: 12 July 2018

Please cite this article as: Nahon P, Layese R, Bourcier V, Cagnot C, Marcellin P, Guyader D, Pol S,Larrey D, De Lédinghen V, Ouzan D, Zoulim F, Roulot D, Tran A, Bronowicki J-P, Zarski J-P, Riachi G,Calès P, Péron J-M, Alric L, Bourlière M, Mathurin P, Blanc J-F, Abergel A, Serfaty L, Mallat A, GrangéJ-D, Attali P, Bacq Y, Wartelle C, Dao T, Thabut D, Pilette C, Silvain C, Christidis C, Nguyen-Khac E,Bernard-Chabert B, Zucman D, Di Martino V, Sutton A, Roudot-Thoraval F, Audureau E, for the ANRSCO12 CirVir group, Incidence of Hepatocellular Carcinoma After Direct Antiviral Therapy for HCV inPatients With Cirrhosis Included in Surveillance Programs, Gastroenterology (2018), doi: 10.1053/j.gastro.2018.07.015.

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Incidence of Hepatocellular Carcinoma After Direct Antiviral Therapy for HCV in

Patients With Cirrhosis Included in Surveillance Programs

Short title: Liver cancer and DAAs

Pierre Nahon1,2,3, Richard Layese4, Valérie Bourcier1, Carole Cagnot5, Patrick Marcellin6, Dominique Guyader7, Stanislas Pol8,9, Dominique Larrey10, Victor De Lédinghen11, Denis Ouzan12, Fabien Zoulim13, Dominique Roulot14, Albert Tran15,16, Jean-Pierre Bronowicki17, Jean-Pierre Zarski18, Ghassan Riachi19, Paul Calès20, Jean-Marie Péron21, Laurent Alric22, Marc Bourlière23, Philippe Mathurin24, Jean-Frédéric Blanc25, Armand Abergel26, Lawrence Serfaty27, Ariane Mallat28, Jean-Didier Grangé29, Pierre Attali30, Yannick Bacq31, Claire Wartelle32, Thông Dao33, Dominique Thabut34, Christophe Pilette35, Christine Silvain36, Christos Christidis37, Eric Nguyen-Khac38, Brigitte Bernard-Chabert39, David Zucman40, Vincent Di Martino41, Angela Sutton42,43,44, Françoise Roudot-Thoraval4, Etienne Audureau4 for the ANRS CO12 CirVir group. 1AP-HP, Hôpital Jean Verdier, Service d’Hépatologie, Bondy; 2Université Paris 13, Sorbonne Paris Cité, “Equipe labellisée Ligue Contre le Cancer”, F-93206 Saint-Denis; 3Inserm, UMR-1162, “Génomique fonctionnelle des tumeur solides”, F-75000, Paris, FRANCE. 4AP-HP, Hôpital Henri Mondor, Département de Santé Publique, and Université Paris-Est, A-TVB DHU, CEpiA (Clinical Epidemiology and Aging) Unit EA4393, UPEC, F-94000, Créteil; 5Unit for Basic and Clinical research on Viral Hepatitis, ANRS (France REcherche Nord & sud Sida-HIV Hépatites-FRENSH),

6AP-HP, Hôpital Beaujon, Service d’Hépatologie, Clichy; 7CHU Pontchaillou, Service d’Hépatologie, Rennes; 8AP-HP, Hôpital Cochin, Département d’Hépatologie; 9Inserm UMS20 et U1223, Institut Pasteur, Université Paris Descartes, Paris ; 10Hôpital Saint Eloi, Service d’Hépatologie, Montpellier; 11Hôpital Haut-Lévêque, Service d’Hépatologie, Bordeaux; 12Institut Arnaud Tzanck, Service d’Hépatologie, St Laurent du Var; 13Hospices Civils de Lyon, Service d’Hépatologie et Université de Lyon Lyon; 14AP-HP, Hôpital Avicenne, Service d’Hépatologie, Bobigny; 15CHU de Nice, Service d’Hépatologie, F-06202, Cedex 3, Nice; 16Inserm U1065, C3M, Team 8, “Hepatic Complications in Obesity”, F-06204, Cedex 3, Nice; 17Inserm 954, CHU de Nancy, Université de Lorraine, Vandoeuvre-les-Nancy; 18Hôpital Michallon, Service d’Hépatologie, Grenoble; 19Hôpital Charles-Nicolle, Service d’Hépatologie, Rouen; 20CHU d’Angers, Service d’Hépato-Gastroentérologie, Angers; 21Hôpital Purpan, Service d’Hépatologie, Toulouse; 22CHU Toulouse, Service de Médecine Interne-Pôle Digestif UMR 152, Toulouse; 23Hôpital Saint Joseph, Service d’Hépatologie, Marseille; 24Hôpital Claude Huriez, Service d’Hépatologie, Lille; 25Hôpital St André, Service d’Hépatologie, Bordeaux; 26Hôpital Hôtel Dieu, Service d’Hépatologie, Clermont-Ferrand; 27AP-HP, Hôpital Saint-Antoine, Service d’Hépatologie, Paris; 28AP-HP, Hôpital Henri Mondor, Service d’Hépatologie, Créteil; 29AP-HP, Hôpital Tenon, Service d’Hépatologie, Paris; 30AP-HP, Hôpital Paul Brousse, Service d’Hépatologie, Villejuif; 31Hôpital Trousseau, Unité d’Hépatologie, CHRU de Tours; 32Hôpital d’Aix-En-Provence, Service d’Hépatologie, Aix-En-Provence; 33Hôpital de la Côte de Nacre, Service d’Hépatologie, Caen; 34AP-HP, Groupe Hospitalier de La Pitié-Salpêtrière, Service d’Hépatologie, Paris; 35CHU Le Mans, Service d’Hépatologie, Le Mans; 36CHU de Poitiers, Service d’Hépatologie, Poitiers; 37Institut Mutualiste Montsouris, Service d’Hépatologie, Paris; 38Hôpital Amiens Nord, Service d’Hépatologie, Amiens; 39Hôpital Robert Debré, Service d’Hépatologie, Reims; 40Hôpital Foch, Service de Médecine Interne, Suresnes; 41Hôpital Jean Minjoz, Service d’Hépatologie, Besançon, 42CRB (liver disease biobank) Groupe Hospitalier Paris Seine-Saint-Denis BB-0033-00027 ; 43AP-HP, Hôpital Jean Verdier, Service de Biochimie, Bondy; 44Inserm U1148, Université Paris 13, Bobigny.

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ANRS CO12 CirVir group:

Pierre Nahon1, Patrick Marcellin2, Dominique Guyader3, Stanislas Pol4, Hélène Fontaine4, Dominique Larrey5, Victor De Lédinghen6, Denis Ouzan7, Fabien Zoulim8, Dominique Roulot9, Albert Tran10, Jean-Pierre Bronowicki11, Jean-Pierre Zarski12, Vincent Leroy12, Ghassan Riachi13, Paul Calès14, Jean-Marie Péron15, Laurent Alric16, Marc Bourlière17, Philippe Mathurin18, Sebastien Dharancy18, Jean-Frédéric Blanc19, Armand Abergel20, Lawrence Serfaty21, Ariane Mallat22, Jean-Didier Grangé23, Pierre Attali24, Yannick Bacq25, Claire Wartelle26, Thông Dao27, Dominique Thabut28, Christophe Pilette29, Christine Silvain30, Christos Christidis31, Eric Nguyen-Khac 32, Brigitte Bernard-Chabert 33, Sophie Hillaire34, Vincent Di Martino35. 1AP-HP, Hôpital Jean Verdier, Service d’Hépatologie, Bondy, Université Paris 13, Bobigny et INSERM U1162, Université Paris 5, Paris; 2AP-HP, Hôpital Beaujon, Service d’Hépatologie, Clichy; 3CHU Pontchaillou, Service d’Hépatologie, Rennes; 4AP-HP, Hôpital Cochin, Département d’Hépatologie et INSERM UMS20 et U1223, Institut Pasteur, Université Paris Descartes, Paris; 5Hôpital Saint Eloi, Service d’Hépatologie, Montpellier; 6Hôpital Haut-Lévêque, Service d’Hépatologie, Bordeaux; 7Institut Arnaud Tzanck, Service d’Hépatologie, St Laurent du Var; 8Hôpital Hôtel Dieu, Service d’Hépatologie, Lyon; 9AP-HP, Hôpital Avicenne, Service d’Hépatologie, Bobigny; 10CHU de Nice, Service d’Hépatologie, et INSERM U1065, Université de Nice-Sophia-Antipolis, Nice; 11Hôpital Brabois, Service d’Hépatologie, Vandoeuvre-les-Nancy; 12Hôpital Michallon, Service d’Hépatologie, Grenoble; 13Hôpital Charles-Nicolle, Service d’Hépatologie, Rouen; 14CHU d’Angers, Service d’Hépatologie, Angers; 15Hôpital Purpan, Service d’Hépatologie, Toulouse; 16CHU Toulouse, Service de Médecine Interne-Pôle Digestif UMR 152, Toulouse; 17Hôpital Saint Joseph, Service d’Hépatologie, Marseille; 18Hôpital Claude Huriez, Service d’Hépatologie, Lille; 19Hôpital St André, Service d’Hépatologie, Bordeaux; 20Hôpital Hôtel Dieu, Service d’Hépatologie, Clermont-Ferrand; 21AP-HP, Hôpital Saint-Antoine, Service d’Hépatologie, Paris; 22AP-HP, Hôpital Henri Mondor, Service d’Hépatologie, Créteil; 23AP-HP, Hôpital Tenon, Service d’Hépatologie, Paris; 24AP-HP, Hôpital Paul Brousse, Service d’Hépatologie, Villejuif; 25Hôpital Trousseau, Unité d’Hépatologie, CHRU de Tours; 26Hôpital d’Aix-En-Provence, Service d’Hépatologie, Aix-En-Provence; 27Hôpital de la Côte de Nacre, Service d’Hépatologie, Caen; 28AP-HP, Groupe Hospitalier de La Pitié-Salpêtrière, Service d’Hépatologie, Paris; 29CHU Le Mans, Service d’Hépatologie, Le Mans; 30CHU de Poitiers, Service d’Hépatologie, Poitiers; 31Institut Mutualiste Montsouris, Service d’Hépatologie, Paris; 32Hôpital Amiens Nord, Service d’Hépatologie, Amiens; 33Hôpital Robert Debré, Service d’Hépatologie, Reims; 34Hôpital Foch, Service d’Hépatologie, Suresnes; 35Hôpital Jean Minjoz, Service d’Hépatologie, Besançon. FRANCE. Grant Support : ANRS (France REcherche Nord & sud Sida-HIV Hépatites-FRENSH).

Abbreviations: DAA: direct-acting antiviral agent; HCC: hepatocellular carcinoma; PLC: primary

liver cancer; SBP: spontaneous bacterial peritonitis; SVR: sustained virological response.

Correspondence: Pierre Nahon, MD, PhD

Service d’Hépato-Gastroentérologie, Hôpital Jean Verdier, 93140 Bondy, France

Email: pierre.nahon@jvr.aphp.fr

Tel: 33-1-48-02-62-80

Fax: 33-1-48-02-62-02

Disclosures: Dr. Nahon received honoraria from Abbvie, Bayer, Bristol-Myers Squibb, and Gilead. He consults for Abbvie and Bristol-Myers Squibb. Dr. Zarski consults and is on the speakers’ bureau for Gilead, Bristol-Myers Squibb, Janssen, Siemens, and MSD. He consults for AbbVie. Dr. Pol consults for and received grants from Bristol-Myers Squibb, Gilead, Roche, and MSD. He consults for

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Gilead, Bristol-Myers Squibb, Boehringer Ingelheim, Janssen, AbbVie, Roche and MSD. Dr. Alric consults for and received grants from Bristol-Myers Squibb, MSD, and Gilead. He received grants from Roche and Janssen. Dr. Bourliere consults for and advises AbbVie, MSD, Janssen, Bristol-Myers Squibb,Roche, and Gilead. Dr. Di Martino consults for and advises Gilead and MSD. He advises Janssen and Bristol-Myers Squibb. Dr Bacq consults for Roche, Bristol-Myers Squibb, and Gilead. Conflicts of interest: none to declare Author contributions: Drs. Nahon and Audureau had full access to all data in the study and take responsibility for the integrity of data and the accuracy of data analysis. Study concept and design: Nahon, Audureau. Acquisition of data: Nahon, Bourcier, Layese, Marcellin, Guyader, Pol, Larrey, De Lédinghen, Ouzan, Zoulim, Roulot, Tran, Bronowicki, Zarski, Riachi, Calès, Péron, Alric, Bourlière, Mathurin, Blanc, Abergel, Serfaty, Mallat, Grangé, Attali, Bacq, Wartelle, Dao, Benhamou, Pilette, Silvain, Christidis, Capron, Bernard-Chabert, Zucman, Di Martino, Roudot-Thoraval, Maryam Hammouche, Karima Ben Belkacem. Analysis and interpretation of data: Nahon, Layese, Roudot-Thoraval, Audureau. Drafting of the manuscript: Nahon, Layese, Roudot-Thoraval, Audureau. Critical revision of the manuscript for important intellectual content: Nahon, Bourcier, Layese, Cagnot, Roudot-Thoraval, Audureau.

Statistical analysis: Layese, Audureau. Obtained funding: Prof Jean-Claude Trinchet Administrative, technical and material support: Nahon, Bourcier, Cagnot, Layese, Roudot-Thoraval, Audureau. Study supervision: Nahon, Audureau. Role of the Sponsor: The funding sponsor had no role in the design and conduct of the study, collection, management, analysis, interpretation of the data, and preparation, review, or approval of the manuscript.

Electronic word count: 6989/7000, Tables: 4, Figures: 3, Supplementary Tables: 14,

Supplementary Figures: 9, References: 38.

Acknowledgement: This work is dedicated to the memory of Professor Jean-Claude Trinchet.

ACKNOWLEDGMENTS

Scientific committee

P. Nahon (principal investigator), R. Layese and F. Roudot-Thoraval (data management), P.Bedossa,

M.Bonjour, V.Bourcier, S Dharancy, I.Durand-Zaleski, H.Fontaine, D Guyader, A.Laurent, V Leroy,

P.Marche, D.Salmon, V.Thibault, V.Vilgrain, J.Zucman-Rossi, C Cagnot (ANRS), V.Petrov-Sanchez

(ANRS).

Clinical centres (ward / participating physicians)

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CHU Jean Verdier, Bondy (P. Nahon, V.Bourcier); CHU Cochin, Paris (S.Pol, H.Fontaine); CHU

Pitié-Salpétrière, Paris (D. Thabut); CHU Saint-Antoine, Paris (L.Serfaty); CHU Avicenne, Bobigny

(D.Roulot); CHU Beaujon, Clichy (P. Marcellin); CHU Henri Mondor (A.Mallat); CHU Paul Brousse

(P. Attali); CHU Tenon, Paris (J.D.Grangé); CHRU Hôpital Nord, Amiens (D. Capron); CHU Angers

(P.Calès); Hôpital Saint-Joseph, Marseille (M.Bourlière); CHU Brabois, Nancy (J.P.Bronowicki);

Hôpital Archet, Nice (A.Tran); Institut Mutualiste Montsouris, Paris (F.Mal, C.Christidis); CHU

Poitiers (C.Silvain); CHU Pontchaillou, Rennes (D.Guyader); CH Pays d’Aix, Aix-en-Provence

(C.Wartelle); CHU Jean Minjoz, Besancon (V.Di Martino); CHU Bordeaux - Hôpital Haut-Leveque,

Pessac (V.de Ledinghen); CHU Bordeaux - Hôpital Saint-André, Bordeaux (JF.Blanc); CHU Hôtel

Dieu, Lyon (C.Trepo, F.Zoulim); CHU Clermont-Ferrand (A.Abergel); Hôpital Foch, Suresnes

(S.Hillaire); CHU Caen (T.Dao); CHU Lille (P.Mathurin); CH Le Mans (C.Pilette); CHU Michallon,

Grenoble (JP.Zarski); CHU St Eloi, Montpellier (D.Larrey); CHU Reims (B. Bernard-Chabert); CHU

Rouen (O.Goria, G.Riachi); Institut Arnaud Tzanck, St Laurent-du-Var (D.Ouzan); CHU Purpan,

Toulouse (JM.Péron, L.Alric); CHU Tours (Y.Bacq).

Funding/Support: This study was sponsored by the ANRS (France REcherche Nord & sud Sida-hiv

Hépatites: FRENSH). .

Role of the Sponsor: The funding sponsor had no role in the design and conduct of the study;

collection, management, analysis, interpretation of the data, and preparation, review, or approval of the

manuscript.

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ABSTRACT

Background & Aims: Retrospective studies have found an unexpectedly high incidence of hepatocellular

carcinoma (HCC) among patients with hepatitis C virus (HCV)-associated cirrhosis who received direct-acting

antiviral (DAA) agents. We analyzed data from the ANRS CO12 CirVir cohort to compare the incidence of

HCC in patients with cirrhosis who received DAA therapy vs patients treated with interferon (IFN). Methods:

Data were collected from 1270 patients with compensated biopsy-proven HCV-associated cirrhosis recruited

from 2006 through 2012 at 35 centers in France. For descriptive purpose, patients were classified as: patients

who received DAA treatment (DAA group, n=336), patients who achieved a sustained virologic response (SVR)

following an IFN-based regimen (SVR-IFN group, n=495), or patients who never received DAA treatment and

never had an SVR following interferon therapy (non-SVR group, n=439). The patients were included in HCC

surveillance programs based on ultrasound examination every 6 months, and clinical and biological data were

recorded. To account for confounding by indication due to differences in patient characteristics at treatment

initiation, we constructed a time-dependent Cox regression model weighted by the inverse probability of

treatment and censoring (IPTCW) to assess the treatment effects of DAA on time till HCC. Results: Compared

with patients in the SVR-IFN group, patients in the DAA group were older, higher proportions had diabetes or

portal hypertension, and liver function was more severely impaired. The crude 3-year cumulative incidences of

HCC were 5.9% in the DAA group, 3.1% in the SVR-IFN group, and 12.7% in the non-SVR group (overall

P<.001; unadjusted hazard ratio [HR] for HCC, 2.03; 95% CI, 1.07–3.84, P=.030 for the DAA group vs the

SVR-IFN group). HCC characteristics were similar among groups. Among patients with HCC, the DAA group

received less-frequent HCC screening than the other 2 groups (P=.002). After Cox analyses weighted by the

IPTCW, we found no statistically significant increase in risk of HCC associated with DAA use (HR=0.89; 95%

CI, 0.46-1.73) (P=0.73). Conclusions: Analysis of data from the ANRS CO12 CirVir cohort reveals that the

apparent increase in HCC incidence observed in patients with cirrhosis treated with DAAs compared to patients

who achieved SVR following an interferon therapy can be explained by patient characteristics (age, diabetes,

reduced liver function) and lower screening intensity.

KEY WORDS: ANRS; CirVir; liver cancer; risk factors

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INTRODUCTION

The increasingly widespread use of direct-acting antiviral agents (DAAs) has constituted a major

breakthrough in the treatment of hepatitis C virus (HCV) infection, because of the high rates of

sustained virological response (SVR) achieved and an excellent safety profile.1 The eradication of

HCV in patients with cirrhosis is associated with a reduced occurrence of life-threatening

complications, whether liver-related2 or even extra-hepatic,3 and subsequently improved survival.4

These conclusions have so far been restricted to cirrhotic patients who achieved SVR following

interferon-based regimen,5 in whom HCC screening is however still recommended considering the

persistence of an annual incidence of liver cancer ranging from 0.4% to 2% in these patients.2, 4, 6, 7 The

observation of such clinical outcomes indeed necessitates the long-term follow-up of large patient

cohorts in order to accurately assess the potential benefits of viral eradication in the longer term and to

perform accurate analyses which take account of competing risks of death.8 Whether such benefits will

be translated to patients who achieved HCV clearance following the use of DAAs remains an open

question, as these regimens have only been used widely since 2014, at least in countries such as

France which implemented early-access programmes for patients with the most advanced forms of

chronic liver disease.9

Despite a lack of long term follow-up, there have recently been several alarming reports suggesting

“unexpectedly high” rates of HCC incidence under and following DAA regimens in cirrhotic patients.

This situation initially concerned tumor recurrence after implementation of curative procedures such

as hepatic resection or ablation,10 as well as the occurrence of HCC in cirrhotic patients included in

surveillance programs.11-13 Regarding the latter, an HCC incidence ranging from 3% to 5% under of

following DAAs therapy has been observed after the first months of DAAs implementation,

considered at least comparable to the one observed in untreated patients, but in any case higher than

that observed in patients achieving SVR with interferon-based regimen in the literature. All these

studies reported retrospective single-center experiences of initial DAAs implementation, based on

mostly uncontrolled small size series of patients usually presenting with a more severe phenotype of

advanced cirrhosis as compared with that of patients included in clinical trials or derived from now

historical cohorts of patients treated with interferon-based regimen. Despite their methodological

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limitations, these alarming data deserve clarification in large prospective multicentric cohorts of

patients.

The ANRS CO12 CirVir is a prospective cohort of patients with viral compensated cirrhosis who have

been followed since 2006.8 A systematic data collection and homogeneous surveillance protocol is

implemented and similarly applied throughout the entire CirVir cohort, thus allowing an accurate

assessment of pre-defined outcomes that cover the whole spectrum of complications occurring in this

population.3, 14 Based on data from the CirVir cohort, the aims of the present report were first to

accurately assess the raw incidence of HCC under or following DAAs therapy and to compare it to the

one observed under DAA-free regimens. Secondly, we sought to examine and account for the

influence of potential confounders that may at least partially explain differences according to

therapeutic eras (interferon- or DAAs-based), so as to provide an estimation of the HCC incidence and

risk actually attributable to DAAs regimens.

METHODS

This study was sponsored and funded by the ANRS. The protocol had obtained approval from the

Ethics Committee (Comité de Protection des Personnes, Aulnay-sous-Bois, France) and complied with

the ethical guidelines of the 1975 Declaration of Helsinki. All patients gave their written informed

consent to participate in the cohort. The full CirVir protocol is available via the ANRS website

(http://anrs.fr).

Patient selection

The present work was an ancillary study derived from the CirVir cohort8 with specific goals and

objectives redefined according to the STROBE statement.15 Patients were recruited in 35 French

clinical centres between 2006 and 2012. Their selection criteria were: a) aged over than 18 years; b)

histologically-proven cirrhosis, whatever the timing of the biopsy; c) HCV antibody-positive,

whatever the level of viral replication; d) absence of previous complications of cirrhosis (particularly

ascites, gastrointestinal haemorrhage or HCC; e) patients belonging to Child-Pugh class A; f) absence

of severe uncontrolled extrahepatic disease resulting in an estimated life expectancy of less than 1

year. The screening assessment included the usual clinical and biological parameters. Missing

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biological data were determined on frozen serum samples provided by the CRB (Liver Disease

Biobank, Groupe Hospitalier Paris Seine-Saint-Denis BB-0033-00027). A Doppler ultrasound (US)

examination was also performed to verify the inclusion and non-inclusion criteria. Patient information

was recorded in a computerised database by a clinical research associate specifically dedicated to the

ANRS CO12 CirVir cohort in each centre. Past and ongoing alcohol and tobacco consumptions were

quantified in all patients and recorded at inclusion. Their past medical history was also recorded.

Follow-up

The patients were seen by physicians every 6 months, and the usual clinical and biological data were

recorded. Doppler US examinations were performed every 6 months. In a given patient, it was

recommended that US be performed at the same centre by an experienced operator. A report was

completed by each operator, mentioning the presence or not of focal liver lesions. If such lesions were

detected by US, a diagnostic procedure using contrast-enhanced imaging (CT-scan or MRI) and/or

guided biopsy was performed according to the 2005 AASLD guidelines16 updated in 2011.17 A

diagnosis of HCC was thus established by either histological examination performed by an

experienced pathologist or based on probabilistic non-invasive criteria (mainly dynamic imaging

revealing early arterial hypervascularisation and portal washout) according to the different time

periods (before and after 2011). When the HCC diagnosis was established, treatment was determined

using a multidisciplinary approach according to the EASL-EORTC and AASLD guidelines for

HCC.16-18 All patients were followed uniformly according to these international recommendations,

irrespective of their SVR status and antiviral regimen. Two definitions were used to assess consistency

with surveillance guidelines so as to identify suboptimal follow-up, i) considering patients with

optimal follow-up as those with a surveillance time frame, the period elapsing between the last

surveillance imaging and the diagnosis of HCC from imaging findings being <7 months, and those

with a suboptimal follow-up as those with a surveillance timeframe of 7 months or longer; or

alternatively ii) considering overall adequacy of follow-up by computing the rates of imaging

procedures actually performed prior to the diagnosis of HCC in patients diagnosed with liver cancer

divided by the theoretical number of half-yearly imaging procedures during this timeframe.

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Regular endoscopic surveillance was ensured. In the event of oesophageal varices, preventive therapy

was recommended using either beta-blockers or endoscopic ligation.19

All events that occurred during follow-up, whether they were liver-related or not, were recorded based

on the information obtained from the medical files of patients in each centre. In particular, all episodes

of liver decompensation encompassing ascites, hepatic encephalopathy and gastro-intestinal bleeding

were described, as well as their severity, management according to international recommendations and

outcome. All extra-hepatic events occurring during follow-up were also recorded.3 Likely cause(s) of

death were established. Patients who underwent liver transplantation were censored for analysis at the

date of transplantation. All treatments, including antiviral therapy, were recorded at inclusion, and any

modifications during follow-up were notified, particularly if there were any severe adverse events. All

the data recorded during follow-up were monitored secondarily by the same panel of three clinical

research associates located at institution 2 (AP-HP, Hôpital Jean Verdier, Service d’Hépatologie,

Bondy, Université Paris 13). All medical diagnoses of events occurring during follow-up were

confirmed by two senior hepatologists (authors VB and PN). When a given event occurred during

interferon-based treatment, this was clearly specified in the database.

Antiviral therapy and viral replication

All patients included in the CirVir cohort received at least one interferon- or DAA-based therapy.

Before February 2014, all commercially available antiviral therapies initiated during follow-up were

interferon-based (except for patients included in clinical trials testing DAAs). Patients with HCV

genotype 1 or 4 infection received peg-interferon (Peg-IFN) plus a standard dose of ribavirin (RBV,

1,000 mg/day if body weight was <75 kg or 1,200 mg/day if body weight was >75 kg) for 48 weeks.

Patients with HCV genotype 2 or 3 infection received Peg-IFN plus low-dose RBV (800 mg/day) for

16 or 24 weeks. After 2011, genotype 1 patients could also receive either 12 weeks of telaprevir (TVR,

750 mg every 8h) in combination with Peg-IFN and RBV, then 36 weeks of Peg-IFN/RBV, or 4

weeks (lead-in phase) of Peg-IFN and RBV and then 44 weeks of Peg-IFN/RBV and boceprevir

(BOC, 800 mg every 8h) according to the European label. Since February 2014, sofosbuvir-containing

regimens have gradually become available to treat cirrhotic patients in France and are prescribed and

reimbursed for all HCV genotypes. Patients could have been included before 2014 in phase II or III

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clinical trials testing these molecules. All patients included in the CirVir cohort had received at least

one course of interferon-based therapy before receiving DAAs.

Sustained virological response (SVR) was defined as undetectable HCV RNA levels using a

qualitative polymerase chain reaction (PCR) assay (<50 IU/mL) at the end of a 12-week untreated

follow-up period.20 No re-infections or relapses, as defined by detectable HCV RNA in a patient who

had previously achieved an SVR, were observed during the follow-up period.

Statistical analyses

HCC incidence was considered the primary endpoint of interest for the present analysis, while results

relating to secondary endpoints, including liver decompensation, extrahepatic cancers, overall survival

and causes of death are provided as supportive data. Patients were censored if they did not reach the

outcome until December 31, 2016 or last follow-up date before end of study.

We initially conducted descriptive analyses and univariate comparisons of the characteristics of

patients according to treatment allocation and SVR status, so as to provide a direct representation of

the differences potentially existing in patients features at key time points. To do so, patients were

classified into three groups: patients who had received DAAs (DAA group, considering characteristics

at the date of initiation of DAA therapy), patients who achieved an SVR following an interferon-based

regimen (SVR-IFN group, considering characteristics at the date of initiation of interferon therapy

enabling the SVR), and non-SVR patients who failed to achieve SVR by means of an interferon-based

regimen and subsequently never received DAAs (non-SVR group, considering characteristics at the

date of enrolment in the cohort). Descriptive results are presented as medians [interquartile range

(IQR)] for continuous variables and as numbers (percentages) for categorical data. The characteristics

of patients at enrolment (no-SVR) or treatment initiation (SVR-IFN and DAA), and at the diagnosis of

HCC were compared between the three groups of patients using one-way ANOVA or the Kruskal-

Wallis rank sum test for continuous variables and the chi-square or Fisher’s exact test for categorical

variables. Since this grouping relies on a combination of treatment and future virologic outcome itself

affected by treatment, such results are provided for descriptive purpose only and have no causal

interpretation.

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Two different approaches were then used to explore the treatment effect of DAAs on time till HCC,

accounting for potential differences in characteristics of patients at the time of DAAs initiation and

their influence on HCC risk assessment.

First, we used time-dependent multivariate Cox proportional hazards regression method to assess the

association between treatment by DAAs and hazard of HCC, conditional on covariates at baseline for

all patients and on covariates at the time of DAA initiation for those patients having ultimately

received DAAs. In addition to the DAA variable, other time-dependent covariates included clinical

and biological features measured at baseline and updated at DAA initiation (namely, AST, ALT, GGT,

AFP, prothrombin time, albumin, bilirubin, platelet count, BMI, dyslipidemia, diabetes, ongoing

alcohol/tobacco/drug consumption), while time-independent covariates (including demographics and

genotype C) were analysed based on baseline values. Post-treatment covariate information that could

be influenced by treatment was not analysed after DAA initiation. The association between DAAs and

hazard of HCC was assessed by multivariate analysis, entering all variables associated with HCC risk

at the p<0.2 level in univariate analysis, then applying a backward stepwise approach to retain

significant factors at the p<0.05 level in the final model (Model 1). SVR status was then further

entered as a time-dependent binary variable, using two approaches to examine its interaction with

treatment by DAA on their effects on HCC occurrence, i.e. first by entering both individual variables

and testing the DAA*SVR interaction term (Model 2), second by entering a multi-categorical variable

based on the 4 possible combinations between the variables (i.e. No DAA-No SVR / No DAA-SVR /

DAA-No SVR/ DAA-SVR) (Model 3). Treatment and SVR status were systematically retained in the

models as the main predictors of interest.

Second, a marginal structural Cox model using inverse probability of treatment and censoring weights

(IPTCW)21, 22 was developed to estimate the causal effect of DAAs versus no DAAs use on time till

HCC occurrence. This approach relies on the weighting of each observation by the inverse of the

patient's probability of receiving the observed treatment (IPT) given his/her observed values for the

confounders, creating a pseudo-population in which the exposure is independent of the measured

confounders. IPT weights can typically be further corrected for potential informative censoring, by

multiplying initial weights by the inverse probability of being censored (IPC) given covariate history,

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yielding the IPTCW used in the marginal structural model. For the present work, treatment by DAAs

was considered as the main time-dependent exposure of interest, while treatment by IFN was not

analysed as such since a large majority of patients (1205/1270 [95%]) had already been treated at least

once by IFN prior to their inclusion in the CirVir cohort. IPTCW were computed at repeated time

points to control for i) time-independent and -dependent confounders (as previously described for time

dependent Cox modelling) predicting treatment by DAAs using all available pre-treatment follow-up

information, and for ii) informative censoring using all available follow-up information until censoring

or end of study [Dec 31, 2016]). Informative censoring was defined as the first event occurring among

death, liver transplantation and loss to follow-up defined as missing follow-up information for more

than one year at end of study. We used the ‘ipw’ package developed by van der Wal et al (Van der

Wal W.M. & Geskus R.B. (2011). ipw: An R Package for Inverse Probability Weighting. Journal of

Statistical Software, 43(13), 1-23. http://www.jstatsoft.org/v43/i13/.) for the R environment, that

allows handling time-fixed or time-varying exposures and confounders, using a survival model to

model the time to first occurrence of exposure (IPT) or censoring (IPC). We used stabilized weights to

limit the variability in weights distribution that can occur when few values of exposure/censoring are

found in some subgroups.23 Stabilized weights were estimated by considering baseline covariates for

the numerator and baseline and time-dependent covariates for the denominator. Finally, using IPTCW

estimated from the product of treatment and censoring weights, a weighted Cox regression model with

robust standard errors estimation was developed to estimate the treatment effect of DAA on time till

HCC. Assuming no unmeasured confounding and correct model specification, treatment effects

estimated from this model have causal interpretation. In addition to this approach only entering DAA

into the weighted Cox model (Model 1) and as previously described, SVR status was further entered as

a time-dependent binary variable along with the DAA*SVR interaction term (Model 2), and as a

multi-categorical variable based on the combinations between SVR and DAA (Model 3).

Because conventional Kaplan-Meier curves are inadequate to depict survival curves according to time

dependent exposures, we used a clock reset approach2 to build cumulative incidence curves as a

function of the different patient groups of interest. Considering the previously described 3-groups

categorisation, patients from the non-SVR group switching to SVR-IFN were censored at the time of

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SVR, while those patients switching to DAAs were censored at the time of DAA initiation. Follow-up

subsequent to the switch was then reset as time zero for those patients in the SVR-IFN or DAA group,

respectively. Survival curves using this approach were provided for illustrative purpose, along with

unadjusted p-values formally estimated using time-dependent Cox proportional hazard modelling, as

previously detailed.

Sensitivity analyses were performed to document the robustness of the results i) using 4- or 5-groups,

ii) after further stratifying patients treated with DAA into patients with SVR, non SVR and/or missing

information on SVR status, iii) according to the intake of boceprevir/telaprevir in patients with HCV

genotype 1, iv) in patients who never experienced a liver decompensation before treatment initiation,

v) excluding patients having already achieved SVR at enrolment, and vi) in patients with no history of

liver decompensation within 3 months and screened within 6 months before treatment initiation. For

the IPTCW weighted Cox analysis, using unstabilized and/or truncated weights (removing extreme

weights at 1% and 99% percentiles) yielded essentially similar results both in magnitude of estimates

and statistical significance; only results using stabilized untruncated IPTCW are thus shown.

Assumptions that enabled the use of Cox regression were verified. Statistical analyses were performed

using Stata 13.0 (StataCorp, College Station, TX) and R 3.4.2 (R Foundation, Vienna, Austria). A P

value <0.05 was considered to be statistically significant.

RESULTS

Inclusion period and baseline characteristics of patients (Table 1)

A total of 1,822 cirrhotic patients were included in this study, 151 of whom were subsequently

excluded from the analysis after a review of individual data because of either non-compliance with the

inclusion criteria (n=142) or withdrawal of their consent (n=9). The final analyses were therefore

performed in 1,671 patients, 1,323 of whom had HCV-related compensated cirrhosis. Of these, 53

were excluded because of missing data relative to their antiviral treatment, so the remaining 1,270

patients constituted the study population. For descriptive purpose, this was then divided into the DAAs

group (n=336), SVR-INF group (n=495) and non-SVR group (n=439, see consort diagram, Suppl

Figure 1). Follow-up was recorded up to 31 December 2016, at which date the median duration of

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follow-up since inclusion was 67.5 months [IQR: 45.0; 92.1]. Table 1 shows baseline characteristics

for the three groups, considering time of enrolment for non-SVR patients and time at initiation of

treatment for SVR-IFN and DAA groups. When compared with the SVR-IFN group, DAAs patients

were older, had higher rates of diabetes, higher rates of endoscopic portal hypertension and lower

platelet counts. Although all patients had compensated cirrhosis at inclusion in the CirVir cohort,

DAAs patients presented with higher rates of decompensation episodes before treatment initiation and

their liver function was more impaired (Table 1).

Crude incidence of HCC as a function of antiviral regimen

During follow-up, a first hepatic focal lesion was observed in 441 patients (34.7%) with a 5-year

cumulated incidence (CumI) estimated as 33.9%. Following a diagnostic procedure, more than half of

these focal liver lesions remained indeterminate or were considered to be benign (n=234, 53.7%). The

rates and incidences of non-HCC hepatic focal lesions were similar according to treatment allocation

(Suppl Figure 2). A definite diagnosis of primary liver cancer (PLC) was established in the remaining

207 patients: HCC (n=200) and intra-hepatic cholangiocarcinoma (n=7). The PLC 5-yr CumI was

14.7%. The characteristics of HCC at diagnosis are shown in Table 2. Overall, a large majority of

patients with HCC fell within the Milan criteria and curative treatment as first-line therapy was

implemented in most of them. The HCC characteristics of patients were similar at diagnosis in all

groups, except for higher AFP levels in non-SVR patients. Overall survival after HCC diagnosis did

not differ according to treatment allocation (12-months overall survival: 79.4% vs. 87.9% 76.6%,

P=0.09). The median ratio of imaging techniques actually performed during follow-up was the lowest

in DAAs patients prior to treatment initiation, suggesting their poor compliance with HCC

surveillance when compared with the two other groups (Table 2). Additionally, among patients from

the DAA group, 253/336 (75.3%) had an HCC screening interval <7 months before treatment

initiation, as compared to 478/495 (96.6%) in the SVR-IFN group (P<0.0001). No statistically

significant difference was found in outcome between patients who received telaprevir- or boceprevir-

based therapy and those who received Interferon-based therapy alone without these molecules (Suppl

Table 1,2,3 and Suppl Figure 3). DAAs patients had a shorter follow-up (21.2 months [IQR: 13.5 –

26.9]) as compared with SVR-IFN patients (64.4 months [IQR: 45.2 – 90.8]) or non-SVR patients

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(47.4 months [IQR: 24.7 – 68.9], P<0.001). DAAs patients had a lower crude incidence of HCC (3-

year cumulative incidence, 3-yr CumI=5.9% [95% CI: 3.5 ; 9.9] ) when compared to non-SVR

patients (CumI 3-yrs=12.7% [95% CI: 10.5 ; 15.4], HR=0.48 [95% CI : 0.27 ; 0.86], P=0.014) but a

higher crude incidence when compared to SVR-IFN patients (3-yr CumI=3.1% [95% CI: 1.8 ; 5.1],

HR=2.03 [95% CI: 1.07 ; 3.84], P=0.030, Figure 1). At end-point, 62 DAAs patients were considered

as either “non-SVR status” (n=23), either had missing data regarding HCV replication or were under

therapy (n=39). Although these patients had a higher HCC incidence as compared to DAAs patients

who achieved SVR, they did not differ in terms of baseline or HCC characteristics (Suppl Tables 4 and

5). Incidence of HCC in DAAs group was 2.6 [95% CI: 1.6 ; 4.4] per 100 person-years (1.4 [95% CI:

0.7 ; 2.9] per 100 person-years in DAAs SVR and 12.0 [95% CI: 6.0 ; 24.1] per 100 person-years in

DAA Non-SVR/MD). Among the DAAs group, the 23 patients who did not achieve SVR had the

highest incidence of HCC (1-yr CumI=23.5%, Suppl Table 6 and Suppl Figure 4). A more detailed

analysis according to treatment allocation and SVR status (see Suppl Table 7) confirmed that patients

who achieved SVR following DAAs therapy did not have a significantly higher risk of developing

HCC as compared with those who achieved SVR following interferon-based regimen. Additionally,

when considering the rates of HCC recorded during the different therapeutic eras, we did not observe

an increase in HCC incidence when DAAs became commercially available in France in February 2014

in the setting of early-access programs dedicated to patients with cirrhosis (Suppl Figure 5). Before

this date, only 2 cases of HCC were recorded in the few patients who had access to these new drugs in

the setting of clinical trials.

The different DAAs regimens implemented are described in Suppl Table 8. When considering the

incidence of HCC in the DAAs group as a function of treatment allocation, none of these

combinations was specifically associated with the onset of liver cancer (Suppl Figure 6).

Crude incidence of liver decompensation, extrahepatic cancers, causes of death and survival as a

function of antiviral regimen

Overall, 222 patients (17.5%) presented with at least one episode of liver decompensation, defined by

the occurrence of ascites (n=174), hepatic encephalopathy (n=65) or gastrointestinal bleeding (related

to portal hypertension in 43 out of 69 cases), with a corresponding 3-yr CumI of 16.2%. DAAs

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patients had a lower incidence of liver decompensation (3-yr CumI=6.1%) when compared with non-

SVR patients (3-yr CumI=11.9%, HR=0.37 [95% CI: 0.20; 0.68], P=0.001, Figure 2A). A total of

1,603 extrahepatic events were recorded in 698 patients. One hundred and fifty-seven vascular events

occurred in 113 patients while 104 extrahepatic cancers were reported in 88 patients and 209 patients

experienced a first symptomatic episode of BI. DAAs patients had a similar 3-yr CumI for

cardiovascular events, extrahepatic cancers and BI when compared with SVR-IFN patients (2.0% vs

3.7%, P=0.22; 7.9% vs 4.6%, P=0.59 and 2.3% vs 7.5%, P=0.55 respectively), and had lower

incidences of vascular events or BI when compared with non-SVR patients (HR=0.23 [95% CI: 0.08 ;

0.66] P=0.007 and HR=0.34 [95% CI: 0.15 ; 0.75] P=0.007 respectively) [Suppl Figure 7A, 7B and

7C].

During the same time-frame, 209 patients (16.5%) died, which corresponded to a 3-yr survival rate of

88.7%. Fifty patients were transplanted, 37 for end-stage liver disease and 13 for HCC. Ninety-one

patients (51.1%) died of liver-related complications, while 87 extrahepatic events (48.9%) were

responsible for the remaining deaths [MD=31]. DAAs patients had similar crude overall survival to

that of non-SVR patients (unadjusted HR=0.57 [95% CI: 0.25; 1.33], P=0.19), and poorer outcome

than SVR-IFN patients (unadjusted HR=2.97 [95% CI: 1.12; 7.89], P=0.029, Figure 2B). However, no

significant difference persisted after minimal multivariate adjustment for age, bilirubin, AFP and

platelet count (aHR=1.00 [95% CI: 0.22; 4.60], P=0.996).

Confounders for a higher incidence of HCC under or following DAA therapy

Table 3 shows the features associated with the occurrence of HCC according to univariate and

multivariate time-dependent Cox regression analyses. . Under multivariate analysis, factors associated

with the development of liver cancer encompassed an increased age, past excessive alcohol

consumption, virological parameters (HCV genotype 1) and impaired liver function (decreased

platelet count and increased GGT levels), while no statistically significant association was found

between DAA use and HCC risk (model 1; HR = 0.81 [0.44 ; 1.49], p=0.49). . Further entering SVR as

a time-dependent variable (models 2 and 3) revealed significantly decreased hazard ratios (model 2:

HR=0.44 [0.29 ; 0.69], p=0.0003), without any interaction with the DAA variable as shown by the

non-significant interaction term (model 2: p=0.70) and the similarly decreased HR associated with

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SVR under DAA or without DAA (model 3). The same results were observed after excluding from the

analyses patients who experienced a first episode of hepatic decompensation before treatment

initiation (See Suppl Tables 9, 10, 11 and Suppl Figure 8) or after exclusion of patients who obtained

SVR before inclusion in the Cirvir cohort (Suppl Table 12). Because liver function impairment and

lower screening intensity were identified as potential confounders, we also performed analyses in the

subgroup of 1162 patients who did not experience decompensation within 3 months and underwent a

screening procedure within 6 months before therapy initiation (Suppl Table 13), again yielding very

similar results with no indication of a modified risk under DAA. . Additionally, Suppl Table 14 reports

the results of screening imaging prior to treatment initiation in the 15 patients who developed an HCC

following DAAs initiation. This description shows that 8/15 patients had an appropriate screening

procedure (mostly US) within 6 months before DAAs initiation that did not show any focal lesion. The

remaining patients either had an inappropriate screening interval (n=2) or were detected with at least

one liver focal lesion (n=5) 6 months prior to DAAs therapy. Finally, we compared HCC incidence

between patients who had a normal screening examination in the recommended timeframe versus

others. We observed that patients screened within 6 months before DAAs initiation and without

detectable nodule had a lower HCC incidence than other DAAs patient (Suppl Figure 9).

Table 4 shows the results from the marginal structural Cox model weighted by the IPTCW to formally

analyze the treatment effect of DAA on time till HCC while allowing causal interpretation of results

from observational data. Stabilized IPTCW were computed based on the following time-dependent or

-independent covariates: age, gender, BMI, past excessive and ongoing alcohol intake, tobacco

consumption, diabetes, total bilirubin, AFP levels, prothrombin time, AST levels, GGT levels, HCV

genotype and past history of liver decompensation. Weights had symmetric distribution with mean

(±SD) of 0.995 (±0.250). Under this approach, no statistically significant increase in risk of HCC was

associated with DAA use (model 1: HR=0.89 [0.46 ; 1.73], p=0.735, Figure 3). Similarly to previous

analyses, SVR was associated with significantly decreased HR regardless of DAA treatment status

(models 2 and 3).

DISCUSSION

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When DAAs first became available, the management of HCV was revolutionised. Most of the first

patients to receive these new drugs suffered from cirrhosis and had previously failed to achieve an

SVR after many months and sometimes several lines of interferon-based therapy, experiencing

numerous adverse events or even life-threatening complications. Meanwhile, liver failure had

progressed in some of them and hepatic complications may even have occurred, while significant

numbers of patients were totally lost to follow-up until the approval of DAAs. Hopes and expectations

were therefore high among both patients and physicians, when early-access programmes finally

allowed implementation of the new drugs in these patients with the most severe forms of liver disease

who in some cases had even been missed by HCC surveillance programmes. This general air of

enthusiasm was somewhat shattered by reports of an unexpectedly high incidence of HICC in the short

term following the prescription of DAAs.11, 12 A fact that should be considered with caution when

looking at the potential selection of specific profiles for the patients who initially experienced these

new drugs was that some of them were indeed either more prone to developing HCC because of an

advanced stage of cirrhosis, or their prior screening for HCC had been suboptimal and failed to ensure

the early detection of liver tumours that were perhaps already present when the DAA therapy was

implemented.

The initial alarming reports led to scientific controversy with the multiplication of short publications

focused on mostly single center experiences, a fact that stressed the need for clarification by large

prospective and multicentric data.24 This effort has already started with the combined analysis of three

longitudinal French cohorts (including CirVir) which did not confirm the deleterious effects of DAAs

on tumor recurrence rates following curative HCC procedure.9 As for the occurrence of a first HCC in

HCV-infected patients, the only available multicentric report are up to now restricted to the

retrospective analysis of registries, which did not suggest an abnormally high incidence of HCC under

DAAs.25-27 However, all these studies suffer from methodological limitations: lack of systematic

histological proof of cirrhosis,25-27 exclusion of HCC cases detected during the first months following

DAAs initiation,26 HCC diagnosis restricted to coding systems26, 27 and the absence of details regarding

application of HCC surveillance programs in these populations.26, 27 The multicentre and prospective

design of the Cirvir cohort, covering all these different therapeutic eras, has offered an enormous

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advantage, and the present analyses were able to clarify some important points, and notably: 1) a more

accurate estimate of the incidence of HCC among DAAs patients when compared to that seen in non-

SVR individuals or those who achieved and SVR by means of an interferon-based regimen, and 2) the

identification of possible confounders and explanations for these initial alerts which suggested a

possible link between these new drugs and cancer progression.

As shown in Table 1, patients who benefited from DAAs during follow-up as part of the CirVir cohort

did indeed present with a specific phenotype when compared with SVR-IFN patients. While in the

latter group it has always been recommended that interferon should be initiated in perfectly

compensated patients,20 it is now clear that a significant percentage of patients in whom DAAs were

implemented experienced a gradual deterioration of liver function even though this had been initially

compensated at inclusion several years previously, as suggested by their impaired hepatic function

parameters (prothrombin time, serum bilirubin and albumin levels). Similarly, these patients also

displayed more frequent endoscopic signs of portal hypertension. Even more strikingly, more than

10% of patients in this subgroup experienced at least one episode of liver decompensation between

inclusion in the cohort and the implementation of DAAs. All these features suggesting a more

advanced form of liver disease, combined with older age and higher rates of comorbidities (diabetes in

particular) favour liver carcinogenesis and might explain the apparently higher incidence of HCC in

the DAAs group (Figure 1), at least in the longer term.28 In this context, a comparison of HCC

incidence in these patients cannot be directly assessed with that observed in clinical practice and

reported in the literature of “historical” patients who achieved SVR by means of an interferon-based

therapy.4 This fact was strongly supported by the results of multivariate models (Table 3) after

adjusting for a variety of potentially influent factors, as well as the estimates from the marginal

structural model weighted by IPTCW to correct for confounding by indication and informative

censoring(Table 4 and Figure 3). Both approaches indeed suggest that when a correction was made for

these differentiated clinical features, the incidence of HCC in SVR patients was similar regardless of

treatment allocation.

The comparison of the DAAs group with patients who did not achieve an SVR under interferon and

never received DAAs during follow-up of the CirVir cohort is also informative. Indeed, while baseline

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characteristics differed less markedly (Table 1), the outcome of this subgroup in the short and medium

terms was generally more favourable. It indeed appears that achieving an SVR through the use of

DAAs was beneficial, with a clear reduction in HCC incidence (Figure 1), as well as in liver

decompensation (Figure 2A) and, to a lesser extent, in extrahepatic complications (Suppl Figure 7). In

particular, we did not observe any specific signals suggestive of a higher incidence of extrahepatic

cancers in the DAAs group. Overall, these findings suggest that implementation of DAAs, even in the

most advanced forms of cirrhosis, is beneficial regardless of the controversy surrounding this issue.29

The analysis of tumour burden at the diagnosis of HCC did not reveal any particular differences in

terms of aggressiveness (Table 2) as a function of anti-HCV treatment. Only AFP levels were notably

higher in the non-SVR group when compared with patients who achieved an SVR following an

interferon- or DAAs-based regimen, an elevation which was most probably related to persistent HCV

replication.30 However, although no significant difference was noted regarding the period elapsing

between the last two imaging examinations before an HCC diagnosis, the compliance of DAAs

patients during follow-up of the cohort appeared to be poorer when compared with the other two

groups. Indeed, when considering the median ratio of liver imaging examinations actually performed

versus the theoretical schedule for such investigations in the setting of HCC surveillance during

follow-up in the three groups, compliance with screening intervals was perhaps poorer among DAAs

patients. This finding is in line with clinical practice, suggesting that some patients who failed to

achieve an SVR in the interferon era were lost to follow-up thus interrupting their surveillance

programme, and only returned to liver units when DAAs finally became available. It is agreed that on

the one hand, none of the standard imaging techniques can offer 100% sensitivity in detecting HCC,31

and on the other hand that this often triggers recall procedures so as to accurately determine the origin

of non-specific focal lesions.32 This fact was emphasised by the number of focal lesions detected

during follow-up of the Cirvir cohort (n=422) which finally led to a definite diagnosis of PLC in only

207 cases, despite the fact that similar rates and incidences of non-HCC focal hepatic lesions were

detected in the different treatment allocation groups (Suppl Figure 2). Consequently, both the quality

of imaging examinations and the number of recall procedures may have been reduced in the DAAs

group with irregular prior follow-up, and it is tempting to speculate that in some patients DAAs may

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have been initiated although difficult-to-detect cancerous lesions were already present. Such

hypothesis is also strongly supported by the analysis of screening imaging prior to treatment initiation

which shows that half of patients who developed HCC following DAAs did not have an appropriate

screening interval or had been detected with a liver focal lesion that could have corresponded to the

emergence of an occult HCC (Suppl Table 14). Furthermore, we also observed a higher HCC

incidence in these patients as compared to those who had a normal screening examination within 6

months before DAAs initiation (Suppl Figure 9). Shortly after the initial reports suggesting higher

rates of tumor relapse following the implementation of curative procedures,10 some authors have

hypothesised that a rapid reduction in HCV viral load may impact tumour immunity through a

triggered imbalance between pro-tumour and anti-tumour immune functions,33 or even increased

angiogenesis.34 The degree to which such effects may accelerate tumour growth, at least temporarily

during DAA treatment in patients with undetectable tumours, and the apparently increased incidence

of HCC during a short period remains an open question. Finally, a very small subgroup of DAAs

patients (N=23) who were not identified as having achieved an SVR (for whatever reason) displayed

the highest incidence of HCC (Suppl Figure 4). Although it is difficult on a case-by-case basis to

accurately determine whether treatment was discontinued because of an HCC diagnosis, an association

in such patients between persistent HCV replication and the development of liver cancer has recently

been reported by others.35 Among possible explanations have been suggested the potential influence of

the neo-vascularisation of HCC foci which could impair the penetration of DAAs, lower accessibility

of HCV to drugs within tumor cells or alterations of inflammatory process in tumoral

macroenvironment.36 Beyond these speculations and until further notice, the association between

active tumor and treatment failure persisting after adjustment for HCC/HCV clearance predictors

reported by several studies37, 38 provides a further indirect argument to suggest the occult presence of

cancerous lesions before DAAs were implemented in patients who received DAAs in the CirVir

cohort.

Among the strengths of our study are its large sample size and prospective design, with a thorough

follow-up of patients with viral compensated cirrhosis that allowed an accurate assessment of

outcomes, and the conduct of several complementary analyses to provide robust results that account

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for the differing characteristics of patients according to treatment allocation and SVR status. Our study

has also some limitations worth noting, including the varying time periods and length of follow-up

according to treatment allocations and, relatedly, the relatively short follow-up in patients under DAAs

after this treatment was made available in France in 2014. While an early increase that subsequently

plateaued after 2 years was apparent for HCC incidence after DAA, interpretation of our findings

relating to medium-long term should remain cautious, considering the lower numbers of patients still

under observation at that time and the resulting loss in accuracy in the HCC incidence estimates.

Whether such trends relate to actual temporal evolution patterns in patients under DAAs should be

confirmed in future CirVir updates and other large cohort studies. Also, despite thorough follow-up

procedures and multivariate analysis strategies accounting for known influent risk factors, residual

confounding cannot be ruled out due to some parameters not collected or missing in some patients.

Finally, as recall procedures may include repeated sequential explorations by contrast-enhanced

procedures, one cannot rule out that liver focal nodules considered as benign at the time of analyses

might in fact correspond to lesions in transition towards cancerization process.

In summary, our experience of the CirVir cohort suggests that patients who received DAAs have an

apparent increased risk of HCC development when compared to patients who achieved an SVR by

means of an interferon-based regimen. However, this 2-fold increase in risk is modest, limited in time

and can at least partially be explained by confounders linked to the specific profile of patients bearing

higher risk factors for the development of liver cancer. Our analyses also suggest that prior HCC

surveillance programmes may have been less efficient in these patients, thus the hampering number

and quality of recall procedures and raising doubts as to the possibility of treatment implementation in

patients with under-diagnosed cancerous focal lesions. Because it is not possible to rule out an

influence of these molecules in promoting the growth of a pre-existing tumour through their

immunological effects, physicians should be encouraged to ensure rigorous recall procedures in the

event of unspecified focal lesions. A pragmatic attitude could be to systematically perform a contrast-

enhanced imaging technique if a suspicious nodule is detected on US examination before DAAs

implementation; in case of doubt, all recommended procedures including sequential contrast-enhanced

procedures at various time points should be performed and initiation of DAA therapy should be

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delayed until elimination of an emerging oncologic process. Apart from this specific situation and

based on our data, DAAs implementation does not appear to be associated with an increased risk of

HCC development and must be acknowledged as a major improvement in the management of patients

with HCV-related cirrhosis.

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FIGURE LEGENDS Figure 1. Crude incidence of HCC as a function of antiviral therapy. Patients receiving DAAs had a lower HCC incidence when compared with non-SVR patients but a higher incidence versus patients who achieved an SVR following an interferon-based regimen. Figure 2. Incidence of liver decompensation and deaths as a function of antiviral therapy. A. Patients treated with DAAs or who achieved an SVR following interferon-based therapy had lower incidences of liver decompensation when compared to non-SVR patients. B. DAAs patients had intermediate survival rates when compared to non-SVR patients and patients who achieved an SVR following interferon-based therapy. Figure 3. Incidence of HCC as a function of DAA treatment using Inverse Probability of Treatment and Censoring Weighting.

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27. Kanwal F, Kramer J, Asch SM, et al. Risk of Hepatocellular Cancer in HCV Patients Treated With Direct-Acting Antiviral Agents. Gastroenterology 2017;153:996-1005 e1.

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36. Hengst J, Falk CS, Schlaphoff V, et al. Direct-Acting Antiviral-Induced Hepatitis C Virus Clearance Does Not Completely Restore the Altered Cytokine and Chemokine Milieu in Patients With Chronic Hepatitis C. J Infect Dis 2016;214:1965-1974.

37. Beste LA, Green PK, Berry K, et al. Effectiveness of hepatitis C antiviral treatment in a USA cohort of veteran patients with hepatocellular carcinoma. J Hepatol 2017;67:32-39.

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Table 1. Baseline characteristics of patients.

Baseline features Number of

patients DAAs group

n=336 SVR-IFN group

n=495 Non-SVR group

n=439 P–value

Male gender 1270 212 (63.1) 326 (65.9) 267 (60.8) 0.28 Age (years) 1270 59.2 [54.0 – 67.2] 55.5 [48.9 – 62.9] 57.6 [49.9 – 68.0] <0.001 Place of birth 1095 0.44

Europe 245 (84.8) 354 (82.5) 321 (85.2) Sub-Saharan Africa 13 (4.5) 11 (2.6) 10 (2.6) North Africa 29 (10.0) 56 (13.0) 40 (10.6) South East Asia 2 (0.7) 8 (1.9) 6 (1.6) HIV co-infection 1256 16 (4.8) 18 (3.7) 20 (4.6) 0.69 Past excessive alcohol intake 1213 0.011

No 236 (74.2) 315 (66.7) 271 (64.1) Yes 82 (25.8) 157 (33.3) 152 (35.9) Ongoing alcohol consumption 1087 0.004 † 0 211 (89.0) 344 (77.5) 308 (75.9) <10 22 (9.3) 65 (14.6) 63 (15.5) 10 – 50 3 (1.3) 27 (6.1) 27 (6.6) 50 – 100 1 (0.4) 8 (1.8) 6 (1.5) >100 0 0 2 (0.5) Tobacco consumption 1103 <0.001 Never 115 (46.6) 175 (39.3) 161 (39.2) Past 88 (35.6) 107 (24.1) 103 (25.0) Ongoing 44 (17.8) 163 (36.6) 147 (35.8) Drug use 1236 0.75 Never 213 (66.6) 329 (68.1) 307 (70.9) Past 103 (32.2) 149 (30.9) 122 (28.2) Ongoing 4 (1.2) 5 (1.0) 4 (0.9) BMI (kg/m²) 995 26.3 [23.3 – 29.7] 25.9 [23.2 – 29.1] 26.0 [23.1 – 28.7] 0.56 BMI (kg/m²) 995 0.55 <25 77 (39.9) 168 (40.3) 157 (40.8) [25 ; 30[ 69 (35.8) 169 (40.5) 155 (40.3) ≥30 47 (24.3) 80 (19.2) 73 (18.9) Diabetes 1262 82 (24.6) 85 (17.4) 103 (23.5) 0.019 Dyslipidaemia 1263 26 (7.8) 35 (7.1) 25 (5.7) 0.48 Arterial hypertension 1250 119 (36.5) 137 (28.3) 146 (33.3) 0.039 Oesophageal varices 797 61 (35.3) 55 (17.2) 102 (33.4) <0.001

Table 1. Baseline characteristics of patients (continued).

Baseline features Number of patients

DAAs group n=336

SVR-IFN group n=495

Non-SVR group n=439 P–value

Child-Pugh* 1270 <0.001 A 173 (51.5) 458 (92.5) 439 (100) B 19 (5.7) 1 (0.2) 0 C 1 (0.3) 0 0 Missing data 143 (42.6) 36 (7.3) 0 Creatinine (µmol/L) 1152 72.0 [62.0 - 82.0] 71.0 [62.0 - 80.0] 70.7 [61.9 - 80.0] 0.68 eGFR (MDRD) 1152 95.0 [80.9 ; 117.2] 96.2 [82.1 ; 113.4] 95.6 [80.8 ; 112.9] 0.80 Serum ferritin (µg/L or ng/mL)

945 261.0 [102.0 – 456.0] 200.0 [101.0 – 397.0] 365.0 [163.0 – 707.0] <0.001

Serum albumin (g/L) 1123 40.2 [37.0 – 43.0] 43.0 [40.0 – 46.0] 39.7 [36.1 – 43.0] <0.001 Total bilirubin (µmol/L) 1172 13.6 [10.0 – 20.0] 10.0 [7.0 – 14.0] 13.0 [10.0 – 18.0] <0.001 Alpha-foetoprotein (ng/mL) 1097 8.1 [4.8 – 16.0] 4.0 [2.6 – 6.0] 8.6 [5.0 – 16.2] <0.001 Platelet count (103/mm3) 1190 128.0 [91.0 – 170.0] 158.0 [111.0 – 206.0] 118.0 [83.0 – 155.0] <0.001 Prothrombin time (%) 1120 87.0 [76.0 - 98.0] 90.5 [81.0 - 100.0] 85.0 [76.0 – 95.0] <0.001

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AST (IU/L) 1202 75.0 [48.0 - 111.0] 37.0 [27.0 – 60.0] 72.5 [50.0 - 105.0] <0.001 ALT (IU/L) 1202 78.0 [49.0 - 125.0] 39.0 [25.0 – 74.0] 73.5 [50.0 – 115.0] <0.001 GGT (IU/L) 1174 101.5 [61.0 – 208.0] 54.0 [31.0 - 99.0] 111.0 [67.0 - 199.0] <0.001 HCV Genotype 1197 <0.001 1 229 (70.0) 256 (58.0) 329 (76.7) 2 10 (3.1) 43 (9.8) 15 (3.5) 3 45 (13.8) 99 (22.4) 41 (9.5) 4 37 (11.3) 34 (7.7) 39 (9.1) 5 6 (1.8) 6 (1.4) 5 (1.2) 6 0 3 (0.7) 1 (0.2) Anti-HBc antibodies 1260 0.36 Negative 225 (67.2) 317 (64.6) 270 (62.2) Positive 110 (32.8) 174 (35.4) 164 (37.8) Liver decompensation between inclusion and the initiation of antiviral therapy

1268 34 (10.1) 2 (0.4) 0 <0.001

Past history of extrahepatic cancer

1270 24 (7.1) 20 (4.0) 29 (6.6) 0.11

Past history of cardiovascular events

1265 36 (10.8) 34 (6.9) 54 (12.3) 0.016

GFR, glomerular filtration rate; MDRD, modification of diet in renal disease †P value obtained by the following regroupment of modalities of variable alcohol consumption (1, 0 or<10; 2, 10–50; and 3,>50). * Missing data included 85 DAAs patients and 19 SVR-IFN patients in Child-Pugh A-B

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Table 2. Characteristics of hepatocellular carcinoma.

Characteristics DAAs group n=336

SVR-IFN group n=495

Non-SVR group n=439

P-value

Number (%) of HCC patients 15 (4.5) 31 (6.3) 154 (35.1) <0.001** Child-Pugh 0.45 A 4 (26.7) 15 (48.4) 62 (40.3) B 3 (20.0) 1 (3.2) 14 (9.1) C 1 (6.7) 1 (3.2) 5 (3.2) Missing data*** 7 (46.7) 14 (45.2) 73 (47.4) A-B 3/7 6/14 46/73 B-C 2/7 0 1/73

Diameter of largest nodule (mm) ≤ 20 6 (46.2) 17 (65.4) 71 (55.5) 21-30 3 (23.1) 6 (23.1) 30 (23.4) 31-50 3 (23.1) 1 (3.8) 15 (11.7) 0.74 > 50 1 (7.7) 2 (7.7) 12 (9.4) MD 2 5 26 Portal invasion 2 (14.3) 2 (7.4) 11 (8.3) 0.64 MD 1 4 22 Within Milan criteria 10 (71.4) 24 (88.9) 110 (80.3) 0.36 1 nodule ≤ 50 mm 5 16 85 2 or 3 nodules ≤ 30 mm 5 8 25 Outside Milan criteria 4 (28.6) 3 (11.1) 27 (19.7) MD 1 4 17

AFP level at HCC diagnosis (ng/mL)

Median [Q1-Q3] 9.0 [4.4 – 35.1] 4.8 [3.0 – 12.0] 19.6 [8.2 – 102.0] <0.001 MD 4 11 43 Time of last imaging examination before HCC diagnosis (months)

6.1 [3.0 – 8.6] 6.3 [5.7 – 11.4] 6.8 [5.6 – 9.4] 0.57

Imaging examinations performed/theoretical number during follow-up in HCC patients (%) (between inclusion and HCC diagnosis)

78.6 [42.9 – 92.3] 91.7 [75.0 – 100] 100 [80 – 100] 0.002

HCC treatmenta 0.35* - Curative intent 7 (58.3) 22 (78.6) 93 (66.4) Transplantation 0 1 (3.6) 13 (9.3) Resection 4 (33.3) 6 (21.4) 20 (14.3) Ablation 3 (25.0) 15 (53.6) 71 (50.7) - Palliative intent or no treatment

5 (41.7) 6 (21.4) 47 (33.6)

TACE 2 (16.7) 4 (14.3) 32 (22.9) Other palliative approach 1 (8.3) 1 (3.6) 5 (3.6) Biotherapy 1 (8.3) 1 (3.6) 8 (5.7) Best supportive care 2 (16.7) 0 10 (7.1) No treatment 0 0 4 (2.9) - MD 3 3 14 a Included one or several associated therapeutic procedures *Curative intent versus palliative intent or no treatment

** Test from univariate Cox regression model*** Among patients classified in “Missing data”, most of them had a Child-Pugh score “A-B” or “B-C”.

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Table 3. Features associated with the onset of HCC: univariate and multivariate time-dependent Cox regression models

Univariate analysis Multivariate analysis Model 1 Model 2 Model 3 HR (95% CI) P HR (95% CI) P HR (95% CI) P HR [95% CI] P DAA 0.89 (0.51;1.56) 0.692 0.81 (0.44;1.49) 0.493 0.93 (0.46;1.91) 0.853 - SVR 0.26 (0.17;0.38) <0.0001 - 0.44 (0.29;0.69) <0.0001 - DAA*SVR interaction - - 0.78 (0.22;2.76) 0.702 DAA-SVR status <0.0001 0.001

No DAA - No SVR* Ref - - Ref No DAA - SVR 0.25 (0.17;0.38) <0.0001 - - 0.44 (0.29;0.69) <0.0001 DAA - No SVR* 0.80 (0.42;1.52) 0.492 - - 0.93 (0.46;1.91) 0.853 DAA - SVR 0.24 (0.08;0.67) 0.007 - - 0.32 (0.11;0.93) 0.036

Age > 50 yrs 1.41 (1.01;1.97) 0.043 1.72 (1.19;2.49) 0.004 1.67 (1.16;2.41) 0.006 1.67 (1.16;2.41) 0.006 Past excessive alcohol consumption 1.50 (1.12;2.00) 0.006 1.66 (1.22;2.25) 0.001 1.66 (1.22;2.26) 0.001 1.66 (1.22;2.26) 0.001 Past history of malignancy 1.69 (1.00;2.86) 0.051 Dyslipidemia 0.70 (0.36;1.36) 0.287 Ongoing alcohol consumption 0.821

0 or <10 Ref 10-50 0.96 (0.53;1.72) 0.885 >50 0.65 (0.16;2.60) 0.539

Platelet count (103/mm3) <0.0001 <0.0001 <0.0001 <0.0001 <100 3.00 (2.10;4.28) <0.0001 2.53 (1.75;3.68) <0.0001 2.36 (1.62;3.43) <0.0001 2.36 (1.62;3.43) <0.0001 [100 ; 150] 2.00 (1.39;2.88) <0.0001 1.68 (1.15;2.46) 0.007 1.59 (1.08;2.32) 0.018 1.59 (1.08;2.32) 0.018 > 150 Ref Ref Ref Ref

AST (IU/L) <0.0001 ≤N Ref ]N ; 2N] 2.69 (1.72;4.18) <0.0001

> 2N 3.55 (2.32;5.43) <0.0001 ALT (IU/L) <0.0001

≤N Ref ]N ; 2N] 1.61 (1.09;2.37) 0.017 > 2N 2.05 (1.44;2.93) <0.0001

Serum AFP level >7 ng/mL 2.40 (1.81;3.19) <0.0001 Prothrombin time ≤ 80% 1.91 (1.44;2.55) <0.0001 Serum albumin ≤ 35 g/L 2.12 (1.45;3.10) <0.0001 Total bilirubin > 17 µmol/L 1.40 (1.03;1.91) 0.031 Oesophageal varices 2.18 (1.58;3.00) <0.0001 Past history of liver decompensation 4.47 (1.92;10.45) 0.001 GGT levels <0.0001 <0.0001 0.006 0.006

≤N Ref Ref Ref ]N ; 2N] 2.51 (1.54;4.08) <0.0001 2.04 (1.24;3.34) 0.005 1.89 (1.15;3.10) 0.012 1.89 (1.15;3.10) 0.012 > 2N 3.58 (2.29;5.60) <0.0001 2.55 (1.61;4.04) <0.0001 2.14 (1.35;3.41) 0.001 2.14 (1.35;3.41) 0.001

BMI (kg/m²) 0.99 (0.96;1.02) 0.486 Diabetes 1.23 (0.89;1.71) 0.211 Past history of CV events 1.21 (0.76;1.95) 0.421 HCV Genotype 1 1.83 (1.30;2.57) 0.001 1.70 (1.19;2.44) 0.004 1.56 (1.09;2.25) 0.015 1.56 (1.09;2.25) 0.015 Multivariate Cox Analysis entering either DAA (Model 1), DAA, SVR status and DAA*SVR interaction term (Model 2) or DAA and SVR status as a multicategorical variable (Model 3) *No SVR or SVR status missing

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Table 4. Treatment effect of DAA on time till HCC occurrence: time-dependent Cox regression model weighted by the inverse probability of treatment and censoring (IPTCW)

Without IPTCW With IPTCW

HR CI95% p-value HR CI95% p-value

Treatment effect on HCC risk

Model 1

DAA 1.01 (0.56;1.81) 0.982 0.89 (0.46;1.73) 0.735

Interaction analyses

Model 2

DAA 0.91 (0.46;1.81) 0.796 0.86 (0.39;1.93) 0.722

SVR 0.29 (0.19;0.44) <0.0001 0.29 (0.19;0.44) <0.0001

DAA*SVR interaction term 1.11 (0.32;3.81) 0.873 1.01 (0.28;3.72) 0.985

Model 3

DAA-SVR status No DAA - No SVR* Ref <0.0001 Ref <0.0001

No DAA - SVR 0.29 (0.19;0.44) <0.0001 0.29 (0.19;0.44) <0.0001

DAA - No SVR* 0.91 (0.46;1.81) 0.796 0.86 (0.39;1.93) 0.722

DAA - SVR 0.29 (0.10;0.83) 0.021 0.25 (0.09;0.70) 0.008 Weighted Cox Analysis entering either DAA (Model 1), DAA, SVR status and DAA*SVR interaction term (Model 2) or DAA and SVR status as a multicategorical variable (Model 3) *No SVR or SVR status missing

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Suppl Table 1. Baseline characteristics of patients in Non-SVR or SVR-IFN groups with HCV genotype 1, according to Boceprevir (BOC)/Telaprevir (TVR) intake.

Baseline features Number of

patients

Non-SVR or SVR-IFN

Genotype 1

Total

n=585

Non-SVR or SVR-IFN

Genotype 1

Without BOC/TVR n=427

Non-SVR or SVR-IFN

Genotype 1

With BOC/TVR n=158

P–value

Male gender 585 342 (58.5) 234 (54.8) 108 (68.4) 0.003 Age (years) 585 58.2 [51.5 – 67.5] 59.4 [52.0 – 68.0] 56.0 [49.7 – 63.1] 0.002 Place of birth 499 0.74

Europe 441 (88.4) 322 (87.3) 119 (91.5) Sub-Saharan Africa 7 (1.4) 6 (1.6) 1 (0.8) North Africa 44 (8.8) 35 (9.5) 9 (6.9) South East Asia 7 (1.4) 6 (1.6) 1 (0.8) HIV co-infection 579 19 (3.3) 14 (3.3) 5 (3.2) 0.95 Past excessive alcohol intake 562 0.95

No 393 (69.9) 285 (69.9) 108 (70.1) Yes 169 (30.1) 123 (30.1) 46 (29.9) Ongoing alcohol consumption 521 0.065 † 0 393 (75.4) 296 (74.8) 97 (77.6) <10 80 (15.4) 57 (14.4) 23 (18.4) 10 – 50 38 (7.3) 34 (8.6) 4 (3.2) 50 – 100 9 (1.7) 8 (2.0) 1 (0.8) >100 1 (0.2) 1 (0.2) 0 Tobacco consumption 536 0.25 Never 225 (42.0) 175 (44.1) 50 (36.0) Past 138 (25.8) 99 (24.9) 39 (28.0) Ongoing 173 (32.3) 123 (31.0) 50 (36.0) Drug use 575 0.002 Never 421 (73.2) 321 (76.2) 100 (64.9) Past 147 (25.6) 98 (23.3) 49 (31.8) Ongoing 7 (1.2) 2 (0.5) 5 (3.3) BMI (kg/m²) 492 25.8 [23.2 – 28.8] 25.8 [22.9 – 28.7] 25.8 [23.7 – 29.3] 0.40 BMI (kg/m²) 492 0.40 <25 207 (42.1) 155 (41.3) 52 (44.5) [25 ; 30[ 189 (38.4) 150 (40.0) 39 (33.3)

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≥30 96 (19.5) 70 (18.7) 26 (22.2) Diabetes 584 129 (22.1) 99 (23.2) 30 (19.1) 0.29 Dyslipidaemia 585 36 (6.2) 28 (6.6) 8 (5.1) 0.50 Arterial hypertension 584 199 (34.1) 147 (34.4) 52 (33.1) 0.77 Oesophageal varices 392 109 (27.8) 81 (28.6) 28 (25.7) 0.56

† P-value computed by the following merging of categories of the variable Alcohol Consumption (1 - “0” or “<10; 2 - “10-50; 3 - “> 50”)

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Suppl Table 1. Baseline characteristics of patients in Non-SVR or SVR-IFN groups with HCV genotype 1, according to Boceprevir (BOC)/Telaprevir (TVR) intake (continued).

Baseline features Number of

patients

Non-SVR or SVR-IFN

Genotype 1

Total

n=585

Non-SVR or SVR-IFN

Genotype 1

Without BOC/TVR n=427

Non-SVR or SVR-IFN

Genotype 1

With BOC/TVR n=158

P–value

Creatinine (µmol/L) 558 70.0 [60.0 – 80.0] 70.7 [61.9 – 80.7] 68.1 [57.0 – 77.0] 0.12 eGFR (MDRD) 558 95.2 [81.3 – 113.2] 93.3 [79.1– 111.1] 101.3 [85.4 – 119.6] 0.002 Serum ferritin (µg/L or ng/mL) 507 292.0 [138.0 – 611.0] 273.0 [135.0 – 574.0] 374.5 [160.0 – 681.5] 0.15 Serum albumin (g/L) 556 40.7 [37.1 – 44.0] 41.0 [37.0 – 44.0] 40.7 [37.7 – 43.5] 0.62 Total bilirubin (µmol/L) 571 12.0 [9.0 – 17.4] 12.0 [9.0 – 17.0] 13.0 [8.0 – 18.8] 0.58 Alpha-foetoprotein (ng/mL) 551 6.4 [4.0 – 13.4] 6.1 [3.9 – 12.0] 7.3 [4.0 – 15.3] 0.17 Platelet count (10

3/mm

3) 567 133.0 [93.0 – 179.0] 133.0 [93.0 – 176.0] 133.0 [92.0 – 185.0] 0.89

Prothrombin time (%) 547 87.0 [78.0 – 96.0] 87.0 [77.0 – 96.0] 87.5 [80.0 – 97.0] 0.27 AST (IU/L) 574 60.0 [38.0 – 91.0] 62.0 [36.0 – 91.0] 57.5 [42.5 - 92.0] 0.38 ALT (IU/L) 575 64.0 [37.0 – 107.0] 63.0 [35.0 – 104.0] 68.0 [43.0 – 115.0] 0.13 GGT (IU/L) 568 82.5 [46.0 – 150.5] 81.0 [45.0 – 143.0] 91.0 [53.0 – 157.0] 0.16 Anti-HBc antibodies 581 0.35 Negative 382 (65.8) 274 (64.6) 108 (68.8) Positive 199 (34.2) 150 (35.4) 49 (31.2) Liver decompensation between

inclusion and the initiation of

antiviral therapy

585 5 (0.9) 0 5 (3.2) 0.001

Past history of extrahepatic

cancer 585 35 (6.0) 23 (5.4) 12 (7.6) 0.32

Past history of cardiovascular

events 585 64 (10.9) 50 (11.7) 14 (8.9) 0.33

GFR, glomerular filtration rate; MDRD, modification of diet in renal disease †P value obtained by the following merging of modalities of variable alcohol consumption (1, 0 or<10; 2, 10–50; and 3,>50).

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Suppl Table 2. Crude HCC incidence in patients with HCV genotype 1, according to first or second generation DAAs intake and virological response in DAAs.

Incidence at Without BOC / TVR BOC / TVR DAAs SVR DAAs Non-SVR DAAs MD

6 months 0.1% 0.8% 0% 11.1% 4.0% 12 months 1.6% 2.1% 1.7% 33.3% 4.0% 18 months 3.4% 6.0% 1.7% 33.3% 4.0% 24 months 5.8% 7.0% 3.7% - 4.0% 36 months 11.4% 9.3% 3.7% - 4.0% 42 months 12.9% 10.3% 3.7% - 4.0% 48 months 16.4% 10.3% 3.7% - 4.0% 54 months 18.7% 12.7% 3.7% - 4.0% 60 months 19.8% 12.7% 3.7% - 4.0%

BOC: Boceprevir; TVR: Telaprevir

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Suppl Table 3. Factors associated with HCC occurrence in patients with HCV genotype 1

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Whole cohort

Cox univariate analysis

Cox multivariate analysis

HR (95% CI)

P

HR (95% CI)

P

Age > 50 yrs 1.38 (0.91;2.09) 0.131

Past excessive alcohol consumption 1.51 (1.07;2.13) 0.018

Past history of malignancy 1.87 (1.08;3.25) 0.027

Dyslipidemia 0.61 (0.27;1.37) 0.230

Ongoing alcohol consumption 0.579

0 or <10 Ref

10-50 1.37 (0.74;2.54) 0.323

> 50 1.31 (0.32;5.32) 0.704

Platelet count (103/mm

3) <0.0001 0.026

<100 2.64 (1.73;4.02) <0.0001 1.87 (1.19;2.95) 0.007

[100 ; 150] 1.84 (1.20;2.83) 0.005 1.44 (0.92;2.27) 0.112

> 150 Ref Ref

AST (IU/L) 0.001

≤N Ref

]N ; 2N] 2.01 (1.17;3.45) 0.011

> 2N 2.70 (1.61;4.54) <0.0001

ALT (IU/L) 0.208

≤N Ref

]N ; 2N] 1.22 (0.77;1.94) 0.390

> 2N 1.46 (0.96;2.23) 0.080

Serum AFP level >7 ng/mL 2.29 (1.62;3.24) <0.0001 1.72 (1.18;2.52) 0.005

Prothrombin time ≤ 80% 0.69 (0.48;0.98) 0.039

Serum albumin ≤ 35 g/L 0.42 (0.27;0.63) <0.0001 0.55 (0.35;0.86) 0.008

Total bilirubin > 17 µmol/L 1.29 (0.89;1.87) 0.173

Oesophageal varices 2.18 (1.49;3.19) <0.0001

Past history of liver decompensation 2.76 (0.98;7.82) 0.056

GGT levels <0.0001 0.015

≤N Ref Ref

]N ; 2N] 1.65 (0.93;2.93) 0.089 1.41 (0.77;2.56) 0.264

> 2N 2.68 (1.61;4.45) <0.0001 2.08 (1.21;3.58) 0.008

BMI (kg/m²) 1.00 (0.96;1.03) 0.849

Diabetes 1.25 (0.85;1.83) 0.261

Past history of CV events 1.10 (0.64;1.88) 0.731

Antiviral regimen 0.082 0.066

Without BOC / TVR Ref Ref

With BOC / TVR 0.70 (0.44;1.11) 0.130 0.62 (0.33;1.16) 0.137

DAAs 0.51 (0.25;1.04) 0.066 0.36 (0.13;1.02) 0.054

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Suppl Table 4. Baseline characteristics of patients in DAAs group according to SVR status.

Baseline features Number of

patients

DAAs group

n=336 DAAs SVR

n=274

DAAs Non-

SVR/MD

n=62

P–value

Male gender 336 212 (63.1) 173 (63.1) 39 (62.9) 0.97 Age (years) 336 59.2 [54.0 – 67.2] 59.2 [53.8 – 67.1] 59.2 [54.7 – 68.1] 0.90 Place of birth 289 0.28

Europe 245 (84.8) 201 (85.2) 44 (83.0) Sub-Saharan Africa 13 (4.5) 9 (3.8) 4 (7.55) North Africa 29 (10.0) 25 (10.6) 4 (7.55) South East Asia 2 (0.7) 1 (0.4) 1 (1.9) HIV co-infection 334 16 (4.8) 14 (5.1) 2 (3.3) 0.75 Past excessive alcohol intake 318 0.94

No 236 (74.2) 192 (74.1) 44 (74.6) Yes 82 (25.8) 67 (25.9) 15 (25.4) Ongoing alcohol consumption 237 1.00 † 0 211 (89.0) 173 (89.2) 38 (88.4) <10 22 (9.3) 17 (8.8) 5 (11.6) 10 – 50 3 (1.3) 3 (1.5) 0 50 – 100 1 (0.4) 1 (0.5) 0 >100 0 0 0 Tobacco consumption 247 0.34 Never 115 (46.6) 101 (48.6) 14 (35.9) Past 88 (35.6) 71 (34.1) 17 (43.6) Ongoing 44 (17.8) 36 (17.3) 8 (20.5) Drug use 320 0.85 Never 213 (66.6) 171 (65.8) 42 (70.0) Past 103 (32.2) 85 (32.7) 18 (30.0) Ongoing 4 (1.2) 4 (1.5) 0 BMI (kg/m²) 193 26.3 [23.3 – 29.7] 26.3 [23.1 – 30.0] 27.2 [23.6 – 29.7] 0.64 BMI (kg/m²) 193 0.50 <25 77 (39.9) 66 (41.5) 11 (32.4) [25 ; 30[ 69 (35.8) 54 (34.0) 15 (44.1) ≥30 47 (24.3) 39 (24.5) 8 (23.5) Diabetes 333 82 (24.6) 61 (22.5) 21 (33.9) 0.061

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Dyslipidaemia 333 26 (7.8) 19 (7.0) 7 (11.3) 0.29 Arterial hypertension 326 119 (36.5) 91 (34.2) 28 (46.7) 0.070 Oesophageal varices 173 61 (35.3) 54 (37.0) 7 (25.9) 0.27

† P-value computed by the following merging of categories of the variable Alcohol Consumption (1 - “0” or “<10; 2 - “10-50; 3 - “> 50”)

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Suppl Table 4. Baseline characteristics of patients in DAAs group according to SVR status. (continued).

Baseline features Number of

patients DAAs group

n=336 DAAs SVR

n=274 DAAs Non-SVR/MD

n=62 P–value

Creatinine (µmol/L) 253 72.0 [62.0 – 82.0] 72.0 [61.9 – 82.0] 72.6 [62.0 – 81.0] 0.90 eGFR (MDRD) 253 95.0 [80.9 – 117.2] 95.1 [81.9 – 116.7] 93.5 [74.7 – 119.4] 0.95 Serum ferritin (µg/L or ng/mL) 95 261.0 [102.0 – 456.0] 264.0 [117.0 – 456.0] 148.0 [71.0 – 442.6] 0.34 Serum albumin (g/L) 223 40.2 [37.0 – 43.0] 40.2 [37.0 – 43.0] 39.9 [35.4 – 42.4] 0.31 Total bilirubin (µmol/L) 260 13.6 [10.0 – 20.0] 13.3 [10.0 – 19.9] 13.9 [9.8 – 21.5] 0.44 Alpha-foetoprotein (ng/mL) 206 8.1 [4.8 – 16.0] 8.1 [4.4 – 15.1] 8.2 [5.5 – 21.0] 0.35 Platelet count (10

3/mm

3) 282 128.0 [91.0 – 170.0] 129.0 [92.0 – 171.0] 124.0 [90.0 – 157.0] 0.42

Prothrombin time (%) 240 87.0 [76.0 – 98.0] 87.0 [76.0 – 98.5] 86.0 [72.5 – 96.0] 0.60 AST (IU/L) 282 75.0 [48.0 – 111.0] 75.5 [47.0 – 110.0] 71.0 [52.0 – 116.0] 0.70 ALT (IU/L) 281 78.0 [49.0 – 125.0] 79.0 [47.0 – 123.0] 69.5 [52.0 – 130.0] 0.86 GGT (IU/L) 262 101.5 [61.0 – 208.0] 96.0 [58.5 – 198.5] 144.5 [98.0 – 245.0] 0.005 HCV Genotype 327 0.065 1 229 (70.0) 195 (73.0) 34 (56.7) 2 10 (3.1) 6 (2.3) 4 (6.7) 3 45 (13.8) 33 (12.4) 12 (20.0) 4 37 (11.3) 28 (10.5) 9 (15.0) 5 6 (1.8) 5 (1.9) 1 (1.6) 6 0 0 0 Anti-HBc antibodies 335 0.68 Negative 225 (67.2) 182 (66.7) 43 (69.4) Positive 110 (32.8) 91 (33.3) 19 (30.6) Liver decompensation between

inclusion and the initiation of

antiviral therapy

336 34 (10.1) 25 (9.1) 9 (14.5) 0.20

Past history of extrahepatic

cancer 336 24 (7.1) 20 (7.3) 4 (6.5) 1.00

Past history of cardiovascular

events 334 36 (10.8) 29 (10.6) 7 (11.5) 0.85

GFR, glomerular filtration rate; MDRD, modification of diet in renal disease †P value obtained by the following merging of modalities of variable alcohol consumption (1, 0 or<10; 2, 10–50; and 3,>50).

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Suppl Table 5. Characteristics of hepatocellular carcinoma in patients of DAAs group, according to SVR status.

Characteristics

DAAs group

n=336 DAAs SVR

n=274

DAAs Non-

SVR/MD

n=62

P–

value

Number (%) of HCC patients 15 (4.5) 7 (2.6) 8 (12.9) <0.001

Tumour type 0.67

Uninodular 6 (40.0) 2 (28.6) 4 (50.0)

2 or 3 nodules 7 (46.6) 4 (57.1) 3 (37.5)

> 3 nodules 1 (6.7) 0 1 (12.5)

Infiltrating 1 (6.7) 1 (14.3) 0

MD 0 0 0

Diameter of largest nodule (mm) 0.27

≤ 20 6 (46.1) 4 (66.7) 2 (28.6)

21-30 3 (23.1) 2 (33.3) 1 (14.3)

31-50 3 (23.1) 0 3 (42.9)

> 50 1 (7.7) 0 1 (14.3)

MD 2 1 1

Portal invasion 2 (14.3) 1 (14.3) 1 (14.3) 1.00

MD 1 0 1

Within Milan criteria 10 (71.4) 6 (85.7) 4 (57.1) 0.56

1 nodule ≤ 50 mm 5 2 3

2 or 3 nodules ≤ 30 mm 5 4 1

Outside Milan criteria 4 (28.6) 1 (14.3) 3 (42.9)

MD 1 0 1

AFP level at HCC diagnosis (ng/mL)

Median [Q1-Q3] 9.0 [4.4 – 35.1] 7.8 [6.2 – 31.0] 13.5 [4.4 – 110.0] 0.58

> 200 ng/mL 1 (9.1) 0 1 (20.0)

MD 4 1 3

Time of last imaging examination

before HCC diagnosis (months) 6.1 [3.0 – 8.6] 7.5 [2.8 – 8.6] 5.9 [3.4 – 12.9]

1.00

Imaging examinations

performed/theoretical number

during follow-up in HCC patients (%)

(between inclusion and HCC

diagnosis)

78.6 [42.9 – 92.3] 87.5 [75.0 – 100.0] 70.8 [41.4 – 85.9]

0.22

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HCC treatment* 0.57

- Curative intent

6 (50.0) 2 (33.3) 4 (66.7)

Transplantation 0 0 0

Resection 4 (33.3) 1 (16.7) 3 (50.0)

Ablation 3 (25.0) 2 (33.3) 1 (16.7)

- Palliative intent or no

treatment

6 (50.0) 4 (66.7) 2 (33.3)

TACE 2 (16.7) 0 0

Other palliative approach 2 (16.7) 0 2 (33.3)

Biotherapy 1 (8.3) 0 1 (16.7)

Best supportive care 2 (16.7) 1 (16.7) 1 (16.7)

No treatment 0 0 0

- MD 3 1 2

* Included one or several associated therapeutic procedures

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Suppl Table 6. HCC crude incidence according to treatment allocation and SVR status.

Incidence at DAA SVR DAA Non-SVR DAA MD SVR-IFN Non-SVR

6 months 0.4% 17.1% 2.6% 0.2% 0.2%

12 months 2.0% 23.5% 11.8% 0.4% 2.0%

18 months 2.0% 23.5% 11.8% 1.5% 4.4%

24 months 3.5% - 11.8% 2.4% 6.3%

36 months 3.5% - 11.8% 3.1% 12.7%

42 months 3.5% - 11.8% 4.7% 14.3%

48 months 3.5% - 11.8% 4.5% 16.8%

54 months 3.5% - 11.8% 5.5% 19.5%

60 months 3.5% - 11.8% 5.5% 21.0%

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Suppl Table 7. Influence of treatment allocation and SVR status on HCC risk.

Whole cohort

Cox univariate analysis

Cox multivariate analysis

HR [95% CI]

P

HR [95% CI]

P

Age > 50 yrs 1.41 (1.01;1.97) 0.043 1.60 (1.11;2.31) 0.012

Past excessive alcohol consumption 1.50 (1.12;2.00) 0.006 1.67 (1.22;2.27) 0.001

Past history of malignancy 1.69 (1.00;2.86) 0.051

Dyslipidemia 0.70 (0.36;1.36) 0.287

Ongoing alcohol consumption 0.821

0 or <10 Ref

10-50 0.96 (0.53;1.72) 0.885

> 50 0.65 (0.16;2.60) 0.539

Platelet count (103/mm

3) <0.0001 <0.0001

<100 3.00 (2.10;4.28) <0.0001 2.44 (1.67;3.56) <0.0001

[100 ; 150] 2.00 (1.39;2.88) <0.0001 1.64 (1.11;2.41) 0.012

> 150 Ref Ref

AST (IU/L) <0.0001

≤N Ref

]N ; 2N] 2.69 (1.72;4.18) <0.0001

> 2N 3.55 (2.32;5.43) <0.0001

ALT (IU/L) <0.0001

≤N Ref

]N ; 2N] 1.61 (1.09;2.37) 0.017

> 2N 2.05 (1.44;2.93) <0.0001

Serum AFP level >7 ng/mL 2.40 (1.81;3.19) <0.0001

Prothrombin time ≤ 80% 0.52 (0.39;0.70) <0.0001

Serum albumin ≤ 35 g/L 0.47 (0.32;0.69) <0.0001

Total bilirubin > 17 µmol/L 1.40 (1.03;1.91) 0.031

Oesophageal varices 2.18 (1.58;3.00) <0.0001

Past history of liver decompensation 4.47 (1.92;10.45) 0.001

GGT levels <0.0001 0.009

≤N Ref Ref

]N ; 2N] 2.51 (1.54;4.08) <0.0001 1.92 (1.16;3.17) 0.012

> 2N 3.58 (2.29;5.60) <0.0001 2.09 (1.30;3.36) 0.002

BMI (kg/m²) 0.99 (0.96;1.02) 0.486

Diabetes 1.23 (0.89;1.71) 0.211

Past history of CV events 1.21 (0.76;1.95) 0.421

HCV Genotype 1 1.83 (1.30;2.57) 0.001 1.62 (1.13;2.34) 0.009

SVR/Antiviral regimen final status <0.0001 <0.0001

SVR-INF Ref Ref

DAAs SVR 1.04 (0.45;2.41) 0.925 0.70 (0.28;1.74) 0.443

DAAS Non-SVR 20.15 (7.72;52.58) <0.0001 14.44 (5.37;38.81) <0.0001

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DAAs MD 4.72 (1.42;15.64) 0.011 2.69 (0.62;11.62) 0.184

Non-SVR 4.14 (2.76;6.23) <0.0001 2.32 (1.50;3.59) <0.0001

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Supplementary Table 8. DAAs regimen and sustained virological response.

DAA regimen DAAs SVR

n=274 (81.6)

DAAs Non-SVR

n=23 (6.8)

DAA MD

n=39 (11.6)

SOF +/-RBV 19 (6.9) 7 (30.4) 3 (7.7)

SOF +IFN +/-RBV 25 (9.1) 1 (4.4) 1 (2.6)

SOF +DCV +/-RBV 104 (38.0) 10 (43.5) 17 (43.6)

SOF +SMV +/-RBV 52 (19.0) 2 (8.7) 11 (28.2)

SOF +LDV +/-RBV 50 (18.2) - 5 (12.8)

OBV + PTV +Ritonavir +/-RBV 3 (1.1) 1 (4.3) -

OBV + PTV +Ritonavir +DSV +/-RBV 6 (2.2) - -

EBR +GZR +/-RBV 4 (1.5) - -

DCV +/-RBV 1 (0.4) - -

Others 10 (3.6) 2 (8.7) 2 (5.1)

SOF +RBV +/-IFN 1 - -

SOF +SMV +IFN +RBV 1 - -

SOF +VPR +GS 9857 1 - -

2 DAA (missing data) +IFN +RBV - 1 -

ASV +DCV +IFN +RBV 3 - -

DCV +IFN +RBV 1 - -

SMV +IFN +RBV 4 1 2

MD : Missing data

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Suppl Table 9. Baseline characteristics of patients who never experienced a liver decompensation before treatment initiation.

Baseline features

Number

of

patients

Whole

population

n=1234

DAAs group

n=302

SVR-IFN group

n=493

Non-SVR group

n=439 P–value

Male gender 1234 782 (63.4) 190 (62.9) 325 (65.9) 267 (60.8) 0.27

Age (years) 1234 57.2 [50.3 – 65.9] 59.2 [54.2 – 66.6] 55.5 [48.9 – 62.7] 57.6 [49.9 – 68.0] <0.001

Place of birth 1061 0.40

Europe 892 (84.1) 219 (85.2) 352 (82.4) 321 (85.2)

Sub-Saharan Africa 33 (3.1) 12 (4.7) 11 (2.6) 10 (2.6)

North Africa 120 (11.3) 24 (9.3) 56 (13.1) 40 (10.6)

South East Asia 16 (1.5) 2 (0.8) 8 (1.9) 6 (1.6)

HIV co-infection 1220 53 (4.3) 15 (5.0) 18 (3.7) 20 (4.6) 0.64

Past excessive alcohol intake 1180 0.028

No 795 (67.4) 211 (73.5) 313 (66.6) 271 (64.1)

Yes 385 (32.6) 76 (26.5) 157 (33.4) 152 (35.9)

Ongoing alcohol consumption 1061 0.012 †

0 838 (79.0) 188 (88.3) 342 (77.4) 308 (75.9)

<10 149 (14.0) 21 (9.9) 65 (14.7) 63 (15.5)

10 – 50 57 (5.4) 3 (1.4) 27 (6.1) 27 (6.6)

50 – 100 15 (1.4) 1 (0.5) 8 (1.8) 6 (1.5)

>100 2 (0.2) 0 0 2 (0.5)

Tobacco consumption 1075 <0.001

Never 435 (40.5) 101 (45.7) 173 (39.1) 161 (39.2)

Past 288 (26.8) 78 (35.3) 107 (24.1) 103 (25.0)

Ongoing 352 (32.7) 42 (19.0) 163 (36.8) 147 (35.8)

Drug use 1201 0.61

Never 822 (68.4) 188 (65.5) 327 (68.0) 307 (70.9)

Past 366 (30.5) 95 (33.1) 149 (31.0) 122 (28.2)

Ongoing 13 (1.1) 4 (1.4) 5 (1.0) 4 (0.9)

BMI (kg/m²) 975 26.0 [23.1 – 29.1] 26.3 [23.3 – 29.4] 25.9 [23.1 – 29.1] 26.0 [23.1 – 28.7] 0.69

BMI (kg/m²) 975 0.68

<25 395 (40.5) 71 (40.8) 167 (40.1) 157 (40.8)

[25 ; 30[ 386 (39.6) 62 (35.6) 169 (40.6) 155 (40.3)

≥30 194 (19.9) 41 (23.6) 80 (19.2) 73 (18.9)

Diabetes 1230 254 (20.7) 71 (23.7) 80 (16.3) 103 (23.5) 0.009

Dyslipidaemia 1232 78 (6.3) 25 (8.3) 28 (5.7) 25 (5.7) 0.26

Arterial hypertension 1221 376 (30.8) 101 (34.6) 129 (26.3) 146 (33.3) 0.020

Oesophageal varices 765 201 (26.3) 45 (30.6) 54 (17.3) 102 (33.4) <0.001 † P-value computed by the following regroupment of categories of the variable Alcohol Consumption (1 - “0” or “<10; 2 - “10-50; 3 - “> 50”)

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Suppl Table 9. Baseline characteristics of patients who never experienced a liver decompensation before treatment initiation (continued).

Baseline features

Number

of

patients

Whole population

n=1234

DAAs group

n=302

SVR-IFN group

n=493

Non-SVR group

n=439 P–value

Creatinine (µmol/L) 1123 71.0 [61.9 - 81.0] 71.0 [61.9 - 82.0] 71.0 [61.9 - 80.0] 70.7 [61.9 - 80.0] 0.75

eGFR (MDRD) 1123 95.6 [81.7 ; 113.6] 95.1 [81.9 ; 117.8] 96.4 [82.1 ; 113.4] 95.6 [80.8 ; 112.9] 0.80

Serum ferritin (µg/L or

ng/mL)

940 264.5 [127.5 – 556.0] 262.5 [104.0 – 456.0] 200.0 [101.0 – 397.0] 365.0 [163.0 – 707.0] <0.001

Serum albumin (g/L) 1101 41.2 [38.0 – 44.5] 40.6 [37.7 – 43.0] 43.0 [40.0 – 46.0] 39.7 [36.1 – 43.0] <0.001

Total bilirubin (µmol/L) 1144 12.0 [8.0 – 17.0] 13.0 [9.9 – 19.0] 10.0 [7.0 – 14.0] 13.0 [10.0 – 18.0] <0.001

Alpha-foetoprotein

(ng/mL)

1081 6.0 [3.5 – 11.0] 8.0 [4.9 – 15.0] 4.0 [2.6 – 6.0] 8.6 [5.0 – 16.2] <0.001

Platelet count (103/mm

3) 1159 136.0 [95.0 – 181.0] 132.0 [98.0 – 174.0] 158.0 [111.0 – 206.0] 118.0 [83.0 – 155.0] <0.001

Prothrombin time (%) 1193 88.0 [79.0 – 98.0] 89.0 [79.0 – 100.0] 91.0 [81.0 – 100.0] 85.0 [76.0 – 95.0] <0.001

AST (IU/L) 1173 56.0 [35.0 – 92.0] 77.0 [49.0 – 113.0] 37.0 [27.0 – 60.0] 72.5 [50.0 – 105.0] <0.001

ALT (IU/L) 1173 61.0 [34.0 – 107.0] 79.0 [52.0 – 134.0] 39.0 [25.0 – 74.0] 73.5 [50.0 – 115.0] <0.001

GGT (IU/L) 1146 83.5 [46.0 – 158.0] 102.0 [61.0 – 218.0] 54.0 [31.0 – 99.0] 111.0 [67.0 – 199.0] <0.001

HCV Genotype 1161 <0.001

1 789 (68.0) 206 (70.3) 254 (57.9) 329 (76.7)

2 66 (5.7) 8 (2.7) 43 (9.8) 15 (3.5)

3 182 (15.7) 42 (14.3) 99 (22.5) 41 (9.5)

4 104 (8.9) 31 (10.6) 34 (7.7) 39 (9.1)

5 16 (1.4) 6 (2.1) 6 (1.4) 5 (1.2)

6 4 (0.3) 0 3 (0.7) 1 (0.2)

Anti-HBc antibodies 1225 0.42

Negative 789 (64.4) 202 (66.9) 317 (64.8) 270 (62.2)

Positive 436 (35.6) 100 (33.1) 172 (35.2) 164 (37.8)

Liver decompensation

between inclusion and the

initiation of antiviral

therapy

1234 0 0 0 0 -

Past history of extrahepatic

cancer 1234 68 (5.5) 19 (6.3) 20 (4.1) 29 (6.6) 0.19

Past history of

cardiovascular events 1233 118 (9.6) 31 (10.3) 33 (6.7) 54 (12.3) 0.013

GFR, glomerular filtration rate; MDRD, modification of diet in renal disease †P value obtained by the following regroupment of modalities of variable alcohol consumption (1, 0 or<10; 2, 10–50; and 3,>50).

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Suppl Table 10. Characteristics of hepatocellular carcinoma for patients who never experienced a liver decompensation before treatment initiation.

Characteristics

Whole

population

n=1234

DAAs group

n=302

SVR-IFN group

n=493

Non-SVR group

n=439 P-value

Number (%) of HCC patients

194 (15.7) 9 (3.0) 31 (6.3) 154 (35.1) <0.001**

Tumour type

Uninodular 115 (65.7) 6 (66.7) 17 (63.0) 92 (66.2)

2 or 3 nodules 45 (25.7) 3 (33.3) 9 (33.3) 33 (23.7) 0.70

> 3 nodules 10 (5.7) 0 0 10 (7.2)

Infiltrating 5 (2.9) 0 1 (3.7) 4 (2.9)

MD 19 0 4 15

Diameter of largest nodule (mm)

≤ 20 91 (56.2) 3 (37.5) 17 (65.4) 71 (55.5)

21-30 39 (24.1) 3 (37.5) 6 (23.1) 30 (23.4)

31-50 17 (10.5) 1 (12.5) 1 (3.8) 15 (11.7) 0.72

> 50 15 (9.2) 1 (12.5) 2 (7.7) 12 (9.4)

MD 32 1 5 26

Portal invasion 14 (8.3) 1 (11.1) 2 (7.4) 11 (8.3) 0.87

MD 26 0 4 22

Within Milan criteria 141 (82.0) 7 (87.5) 24 (88.9) 110 (80.3) 0.67

1 nodule ≤ 50 mm 106 5 16 85

2 or 3 nodules ≤ 30 mm 35 2 8 25

Outside Milan criteria 31 (18.0) 1 (12.5) 3 (11.1) 27 (19.7)

MD 22 1 4 17

AFP level at HCC diagnosis

(ng/mL)

Median [Q1-Q3] 14.1 [6.1 – 94.6] 9.0 [6.2 – 13.5] 4.8 [3.0 – 12.0] 19.6 [8.2 – 102.0] 0.001

> 200 ng/mL 19 (14.0) 1 (20.0) 1 (5.0) 17 (15.3) 0.34

MD 58 4 11 43

Time of last imaging examination

before HCC diagnosis (months) 6.6 [5.6 – 9.2] 5.8 [3.8 – 6.7] 6.3 [5.7 – 11.4] 6.8 [5.6 – 9.4] 0.30

Imaging examinations

performed/theoretical number

during follow-up in HCC patients

(%) (between inclusion and HCC

diagnosis)

100 [80.0 – 100] 78.6 [42.9 – 87.5] 91.7 [75.0 – 100] 100 [80 – 100] 0.012

HCC treatmenta 0.45*

- Curative intent

121 (68.8) 6 (75.0) 22 (78.6) 93 (66.4)

Transplantation 14 (8.0) 0 1 (3.6) 13 (9.3)

Resection 30 (17.0) 4 (50.0) 6 (21.4) 20 (14.3)

Ablation 88 (50.0) 2 (25.0) 15 (53.6) 71 (50.7)

- Palliative intent or no

treatment

55 (31.2) 2 (25.0) 6 (21.4) 47 (33.6)

TACE 37 (21.0) 1 (12.5) 4 (14.3) 32 (22.9)

Other palliative approach 7 (4.0) 1 (12.5) 1 (3.6) 5 (3.6)

Biotherapy 9 (5.1) 0 1 (3.6) 8 (5.7)

Best supportive care 11 (6.3) 1 (12.5) 0 10 (7.1)

No treatment 4 (2.3) 0 0 4 (2.9)

- MD 18 1 3 14

a Included one or several associated therapeutic procedures

*Curative intent versus palliative intent or no treatment

** Test from univariate Cox regression model

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Suppl Table 11. Features associated with the occurrence of HCC among patients who never experienced a liver decompensation before treatment initiation.

Whole cohort

Cox univariate analysis

Cox multivariate analysis

HR [95% CI]

P

HR [95% CI]

P

Age > 50 yrs 1.48 (1.04;2.11) 0.029 1.69 (1.15;2.49) 0.007

Past excessive alcohol consumption 1.43 (1.05;1.93) 0.022 1.60 (1.16;2.21) 0.005

Past history of malignancy 1.56 (0.89;2.75) 0.121

Dyslipidemia 0.66 (0.33;1.35) 0.259

Ongoing alcohol consumption 0.528

0 or <10 Ref

10-50 0.94 (0.51;1.73) 0.833

> 50 0.33 (0.05;2.34) 0.265

Platelet count (103/mm

3) <0.0001 <0.0001

<100 3.00 (2.08;4.33) <0.0001 2.47 (1.68;3.61) <0.0001

[100 ; 150] 1.91 (1.31;2.78) 0.001 1.49 (1.01;2.21) 0.046

> 150 Ref Ref

AST (IU/L) <0.0001

≤N Ref

]N ; 2N] 2.59 (1.65;4.09) <0.0001

> 2N 3.61 (2.33;5.58) <0.0001

ALT (IU/L) <0.0001

≤N Ref

]N ; 2N] 1.71 (1.15;2.57) 0.009

> 2N 2.18 (1.50;3.16) <0.0001

Serum AFP level >7 ng/mL 2.47 (1.84;3.30) <0.0001

Prothrombin time ≤ 80% 0.52 (0.38;0.70) <0.0001

Serum albumin ≤ 35 g/L 0.45 (0.30;0.66) <0.0001

Total bilirubin > 17 µmol/L 1.44 (1.04;1.98) 0.027

Oesophageal varices 2.36 (1.69;3.30) <0.0001

GGT levels <0.0001 0.007

≤N Ref Ref

]N ; 2N] 2.57 (1.56;4.23) <0.0001 1.89 (1.14;3.14) 0.014

> 2N 3.58 (2.26;5.67) <0.0001 2.15 (1.34;3.47) 0.002

BMI (kg/m²) 0.99 (0.96;1.03) 0.740

Diabetes 1.31 (0.93;1.83) 0.119

Past history of CV events 1.25 (0.77;2.03) 0.367

HCV Genotype 1 1.79 (1.26;2.54) 0.001 1.57 (1.08;2.28) 0.018

SVR/Antiviral regimen <0.0001 0.001

No DAA - No SVR Ref Ref

No DAA - SVR 0.25 (0.17;0.38) <0.0001 0.44 (0.28;0.68) <0.0001

DAA - No SVR 0.60 (0.27;1.31) 0.199 0.74 (0.32;1.73) 0.489

DAA - SVR 0.14 (0.03;0.57) 0.006 0.20 (0.05;0.83) 0.027

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Suppl Table 12. Factors associated with HCC occurrence in the study population, after exclusion of patients achieving SVR by IFN-based treatment started before inclusion.

Whole cohort

Cox univariate analysis

Cox multivariate analysis

HR [95% CI]

P

HR [95% CI]

P

Age > 50 yrs 1.41 (1.00;2.00) 0.050 1.62 (1.11;2.35) 0.012

Past excessive alcohol consumption 1.57 (1.16;2.12) 0.003 1.81 (1.32;2.49) <0.0001

Past history of malignancy 1.48 (0.86;2.56) 0.157

Dyslipidemia 0.71 (0.36;1.38) 0.311

Ongoing alcohol consumption 0.984

0 or <10 Ref

10-50 0.99 (0.55;1.78) 0.965

> 50 0.88 (0.22;3.56) 0.862

Platelet count (103/mm

3) <0.0001 0.001

<100 2.47 (1.70;3.60) <0.0001 2.08 (1.40;3.09) <0.0001

[100 ; 150] 1.61 (1.10;2.36) 0.015 1.44 (0.97;2.15) 0.071

> 150 Ref Ref

AST (IU/L) 0.006

≤N Ref

]N ; 2N] 1.57 (0.96;2.56) 0.074

> 2N 2.08 (1.30;3.33) 0.002

ALT (IU/L) 0.310

≤N Ref

]N ; 2N] 1.14 (0.75;1.74) 0.546

> 2N 1.34 (0.90;1.98) 0.149

Serum AFP level >7 ng/mL 1.94 (1.44;2.61) <0.0001 1.58 (1.16;2.17) 0.004

Prothrombin time ≤ 80% 0.55 (0.41;0.75) <0.0001

Serum albumin ≤ 35 g/L 0.57 (0.38;0.83) 0.004

Total bilirubin > 17 µmol/L 1.20 (0.87;1.66) 0.255

Oesophageal varices 2.12 (1.52;2.94) <0.0001

Past history of liver decompensation 3.51 (1.49;8.25) 0.004 6.44 (1.86;22.30) 0.003

GGT levels 0.002

≤N Ref

]N ; 2N] 1.59 (0.95;2.69) 0.080

> 2N 2.21 (1.37;3.56) 0.001

BMI (kg/m²) 0.98 (0.95;1.02) 0.322

Diabetes 1.11 (0.79;1.56) 0.554

Past history of CV events 1.14 (0.70;1.85) 0.603

HCV Genotype 1 1.52 (1.06;2.17) 0.024 1.49 (1.02;2.18) 0.040

SVR/Antiviral regimen <0.0001 0.002

No DAA - No SVR Ref Ref

No DAA - SVR 0.34 (0.20;0.58) <0.0001 0.40 (0.23;0.69) 0.001

DAA - No SVR 0.77 (0.40;1.48) 0.436 0.74 (0.33;1.68) 0.472

DAA - SVR 0.22 (0.08;0.64) 0.005 0.19 (0.05;0.72) 0.015

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Suppl Table 13. HCC risk factors in patients with no history of liver decompensation within 3 months and screened within 6 months before treatment initiation.

Whole cohort

Cox univariate analysis

Cox multivariate analysis

HR [95% CI]

P

HR [95% CI]

P

Age > 50 yrs 1.46 (1.04;2.07) 0.030 1.69 (1.15;2.47) 0.007

Past excessive alcohol consumption 1.44 (1.07;1.93) 0.016 1.65 (1.21;2.26) 0.002

Past history of malignancy 1.73 (1.02;2.93) 0.041

Dyslipidemia 0.70 (0.36;1.37) 0.301

Ongoing alcohol consumption 0.875

0 or <10 Ref

10-50 0.99 (0.55;1.78) 0.981

> 50 0.69 (0.17;2.79) 0.605

Platelet count (103/mm

3) <0.0001 <0.0001

<100 3.10 (2.16;4.44) <0.0001 2.51 (1.72;3.66) <0.0001

[100 ; 150] 2.01 (1.39;2.91) <0.0001 1.58 (1.08;2.33) 0.020

> 150 Ref Ref

AST (IU/L) <0.0001

≤N Ref

]N ; 2N] 2.66 (1.70;4.15) <0.0001

> 2N 3.62 (2.36;5.55) <0.0001

ALT (IU/L) <0.0001

≤N Ref

]N ; 2N] 1.63 (1.10;2.42) 0.015

> 2N 2.15 (1.50;3.08) <0.0001

Serum AFP level >7 ng/mL 2.39 (1.79;3.18) <0.0001

Prothrombin time ≤ 80% 0.54 (0.40;0.72) <0.0001

Serum albumin ≤ 35 g/L 0.49 (0.34;0.73) <0.0001

Total bilirubin > 17 µmol/L 1.38 (1.01;1.89) 0.046

Oesophageal varices 2.24 (1.62;3.10) <0.0001

GGT levels <0.0001 0.004

≤N Ref Ref

]N ; 2N] 2.64 (1.62;4.30) <0.0001 1.98 (1.21;3.26) 0.007

> 2N 3.67 (2.34;5.75) <0.0001 2.18 (1.37;3.47) 0.001

BMI (kg/m²) 0.98 (0.95;1.02) 0.313

Diabetes 1.28 (0.92;1.78) 0.143

Past history of CV events 1.26 (0.78;2.02) 0.342

HCV Genotype 1 1.86 (1.32;2.64) <0.0001 1.55 (1.07;2.25) 0.021

SVR/Antiviral regimen <0.0001 <0.0001

No DAA - No SVR Ref Ref

No DAA - SVR 0.22 (0.14;0.33) <0.0001 0.39 (0.25;0.61) <0.0001

DAA - No SVR 0.55 (0.25;1.21) 0.139 0.54 (0.21;1.35) 0.185

DAA - SVR 0.24 (0.09;0.69) 0.008 0.33 (0.11;0.93) 0.037

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Suppl Table 14: Results from screening procedures before treatment initiation in the 15 patients who developed an HCC following DAAs therapy.

Patient number

Time from DAAs initiation to HCC

occurrence (months)

Milan criteria for HCC

Screening within 6 months

before DAAs

Type of imaging technique performed

within 6 months before DAAs

Presence of hepatic focal lesions before DAAs

Details of screening imaging for patients without screening 6-7

months before DAAs

1 0.49 Missing Data Yes US, CT No 2 9.00 In Milan Yes US No 3 5.91 Outside Milan Yes CT No 4 8.97 In Milan Yes US No 5 21.48 Outside Milan Yes US No

6 23.75 In Milan Yes CT Missing data (but 2.4 months and 7.6 months after DAAs initiation: absence of nodule (by US))

7 9.26 In Milan Yes MRI Yes (hypervascular nodule, no more details)

8 11.99 In Milan

No (the last screening (US) occurred 61.1 months before

DAAs)

NA NA

Absence of nodule at the last screening before DAAs. One US screening was performed after DAAs (revealing HCC nodules) but missing data for date and one MRI at HCC diagnosis

9 7.39 Outside Milan Yes US Yes (hypoechogeneous nodule)

10 2.92 In Milan Yes US Yes (doubt about the presence of a 2 cm hypodensity)

11 5.52 In Milan Yes US No 12 11.96 In Milan Yes US No

13 19.25 In Milan

No (the last screening (US)

occurred 8.8 months before

DAAs)

- -

Absence of nodule at the last screening before DAAs. 11.09 months after DAAs initiation: absence of nodule at US screening. Presence of nodules 15.7 months after DAAs by CT.

14 1.18 Outside Milan Yes US Yes (no details about nodules) 15 10.91 In Milan Yes MRI, US, CT Yes (multiple nodules)

MRI: Magnetic resonance imaging; CT: Computerized tomograpgy-scan, US: Doppler ultrasound

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Supplementary Figure 1. Flow-chart of the studied population. Supplementary Figure 2. Incidence of non-HCC hepatic focal lesions according to treatment allocation. Supplementary Figure 3. Crude HCC incidence in patients with HCV genotype 1 according to first or second generation DAAs intake. Supplementary Figure 4. Crude incidence of HCC as a function of SVR status in DAAs patients Supplementary Figure 5. HCC rates in patients ultimately taking DAAs during follow-up. Supplementary Figure 6. Crude incidence of HCC in DAAs patients as a function of treatment regimen Supplementary Figure 7. Extra-hepatic events as a function of antiviral therapy. A- Patients treated with DAAs or who achieved an SVR following interferon-based therapy had lower incidences of cardiovascular events B- Patients treated with DAAs or who achieved an SVR following interferon-based therapy had lower incidences of extrahepatic cancers. C-DAAs patients had the lowest incidence of BI when compared to patients treated with interferon-based therapy (with or without SVR). Supplementary Figure 8. HCC crude incidence in patients who never experienced liver decompensation before treatment initiation. Supplementary Figure 9. Crude HCC incidence in DAAs patients according to the last screening examination before treatment initiation. Among the 336 DAAs patients, 168 (50.0%) had been screened within 6 months before DAAs initiation without any detected nodule (Group 1). Group 2 comprised patients with at least one focal lesion detected before DAAs initiation or who underwent screening procedure more than 7 months before DAAs initiation. Patients who had an inappropriate screening interval or had been detected with a liver focal lesion had a higher HCC incidence.

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