Natale Guzzo
email: natale.guzzo@inria.fr

Nathalie Mitton

Pascal Daragon

Arulnambi Nandagoban

A Cluster-based and On-demand routing algorithm for Large-Scale Multi-hop Wireless Sensor Networks

Keywords: Wireless Sensor Networks (WSN), distributed clustering, multihop routing protocol, on-demand scheme, Base Station (BS) connectivity, energyeciency

Reducing the energy consumption and improving the robustness of a Wireless Sensor Network (WSN) are the main requirements for many industrial and research applications. The sensors usually use a routing protocol in order to deliver the sensing data to a Base Station (BS) which may be far away from the monitoring area. Many algorithms proposed in the literature compute the routing process by clustering the network and by designing new election mechanisms in which the clusterheads are chosen taking account of the remaining energy, the communication cost and the density of nodes. However, they do not consider the connectivity to the BS, and assume that all the nodes or only few prexed nodes are able to directly communicate with it. We believe that this assumption is not suitable for many applications of WSN and to tackle this problem we propose CESAR, a multi-hop and energy-ecient routing protocol for large-scale WSN which includes a new cluster-head selection mechanism aware of the battery level and the connectivity to the BS. Furthermore, our solution employs an innovative hybrid approach to combine both clustering and on-demand techniques in order to provide an adaptive behavior for dierent dynamic topologies. Simulation results show that our solution outperforms in terms of energy consumption and data delivery other known routing algorithms in the literature.

Introduction

The Wireless Sensor Networks (WSN) are often composed of a large number of sensors that collaborate in order to transmit the sensing data to the Base Station (BS) by satisfying some requirements such as coverage, robustness, scalability and lifetime. Several solutions concerning the physical, MAC and network layers have been proposed in the literature. Regarding the routing protocols, the clustering techniques are employed to reduce the message overhead, the overhearing and the interferences between the nodes in the network. The benets introduced by this approach lead to a high scalability, simple routing decisions, and low energy dissipation by reducing the data trac and the overhead caused by the ow of routing information.

In this paper we present the Cluster-based Energy Saving Aliation Routing protocol (CESAR) which is a new multi-hop and energy-ecient algorithm that aims to reduce the energy consumption in WSN by introducing a scheme with innovative features. The main aspects considered in the design of the routing scheme are the energy consumed by the nodes and the data delivery, since our objectives are to create a robust and scalable network and extend its lifetime as long as possible, while fullling application requirements. We will show in the next sections that our clustering scheme outperforms the other simulated algorithms.

We survey the related work in Section II. The main features of CESAR are presented in Section III. In Section IV CESAR is employed in dierent simulated scenarios inspired by industrial use case applications and we analyze the results in comparison with other routing algorithms. Finally, Section V gives the concluding remarks and reports the direction for future works.

Background and related work

Several cluster-based protocols have been proposed in the literature in the last few years to reduce the energy consumption and prolong the network lifetime in WSNs. They can be classied according to the goals and the approaches employed for cluster formation and cluster-head selection. The main distinction is related to the cluster formation mechanism. In this sense, we can distinguish centralized algorithms such as PEGASIS [START_REF] Lindsey | Pegasis: Power-ecient gathering in sensor information systems[END_REF] and CDC [START_REF] Bajaber | Centralized dynamic clustering for wireless sensor network[END_REF], and distributed algorithms like LEACH [START_REF] Heinzelman | An application-specic protocol architecture for wireless microsensor networks[END_REF], HEED [START_REF] Younis | Distributed clustering in ad-hoc sensor networks: a hybrid, energy-ecient approach[END_REF], and DSBCV [START_REF] Liao | Load-balanced clustering algorithm with distributed self-organization for wireless sensor networks[END_REF]. Other schemes are based on Geographical clustering as RCHR [START_REF] Gao | A regional centralized-clustering routing algorithm for wireless sensor networks[END_REF] and TTDD [START_REF] Luo | Ttdd: two-tier data dissemination in large-scale wireless sensor networks[END_REF], on the concentric clustering such as CCS [START_REF] Jung | The concentric clustering scheme for ecient energy consumption in the pegasis[END_REF], or on the use of specic cluster-head election techniques like BLAC [START_REF] Ducrocq | Energy-based Clustering for Wireless Sensor Network Lifetime Optimization[END_REF]. The algorithm named SECC selects the nodes to add to the clusters according to their energy or distance from the cluster-head [START_REF] Bala Krishna | Self-organized energy conscious clustering protocol for wireless sensor networks[END_REF]. In this section we describe in brief some distributed clustering schemes by listing their features and limitations.

Nevertheless, the most of the algorithms studied in the literature suppose that all the nodes can always directly communicate with the BS. We believe that this assumption is quite restrictive and not suitable for many applications of WSNs in which the sensors may not be able to connect to the BS because of the excessive distance or the bad radio environment. Moreover, some schemes such as LEACH and HEED need the synchronization between the nodes in order to start the clustering process at the same time. If the nodes are not synchronized the performances of the two algorithms in terms of energy consumption and data delivery are signicantly degraded, since the cluster-head selection cannot be well performed. The solution presented in this paper does not adopt such an assumption, since it considers the connectivity to the BS as one parameter to use in the cluster-head selection scheme.

CESAR algorithm

Our solution is addressed to specic applications where the sensors are equipped with a long-range radio module to communicate on the link towards the BS (BSlink) and a short-range radio module for the communication peer-to-peer with the other sensor nodes (P2P-link). The nodes do not know the position of the BS and they are supposed to communicate directly with it only whether the received signal strength on the BS-link is high enough. Moreover, depending on the radio environment and the distance from the BS, the nodes do not detect the same quality on the BS-link. As a result, only some of them may be able to connect to the BS and they may need to use dierent transmission powers in order to deliver their data. Such nodes may also change over time depending on the variations of the BS-link quality. In terms of energy consumption, the transmission of data on the BS-link is much more expensive than the transmission of the same amount of data on the P2P-link. In fact, we suppose that the communication on the BSlink requires a transmission power 10 to 20 times higher than the communication on the P2P-link and introduces a connection delay lasting approximately one minute.

We focus on sensor networks where the nodes are positioned at the edges of a 3-dimensional grid. We believe that this model well describes dierent kinds of scenarios such as the monitoring of goods in storage areas. We believe that CESAR is also suitable in applications where the nodes move within the sensing area. Vehicle tracking in a town, surveillance in an airport, and fauna monitoring are some examples in which CESAR can be employed. The most signicant features of CESAR are the following: CESAR is a hybrid algorithm that combines clustering and on-demand approaches in order to dynamically adapt the behavior of the nodes to the topology changes. For this purpose, it does not involve every node in a cluster without preventing it to send data to the BS. The proposed cluster-head selection mechanism is aware of the connectivity to the BS and the battery level: only the nodes that have the signal strength on the BS-link and the battery level greater than prexed thresholds can become cluster-heads.

A recovery scheme is employed to keep alive the routes between the nodes and the cluster-heads with low cost operations. A data aggregation scheme can be employed by the members of the clusters before to send data packet to the cluster-head

In the next paragraphs we explain in more details the cluster-head selection mechanism and the cluster formation scheme. Before that, we need to introduce the types of nodes and routing messages used in dierent processes. We dened four types of nodes: HEAD: nodes which are able to communicate with the BS and are in charge of creating and managing a cluster by sending announcement messages. MEMBER: nodes which have joined a cluster after receiving an announcement transmitted by a HEAD node. LOOSE: nodes which have not joined any cluster and are not able to transmit data to the BS.

The routing messages were dened as follows:

RANN: hop-bounded broadcast messages used by HEAD nodes to build their clusters. REQR: hop-bounded broadcast messages used by LOOSE nodes to discover a nearby cluster. REP: unicast messages used to reply to REQR messages. ROFF: broadcast messages used by HEAD nodes to destroy their clusters. DATA: unicast messages used by MEMBER nodes to deliver their data. ACK: unicast messages used by HEAD nodes to acknowledge DATA packets.

The cluster-head selection mechanism

Every node in the network periodically executes the cluster-head selection process to check whether they have the requirements to become HEAD nodes. As already explained, a node can become a cluster-head only if both the battery level and the signal strength on the BS-link are greater than a prexed threshold. However, these are not the only conditions to become HEAD. There may be other cluster-heads nearby that have better conditions than the considered node. In this case, the latter should become member of one of such clusters, rather than becoming HEAD itself. This decision process is made by calculating the HEAD metric dened as cost and it takes account of the battery level and the quality of the BS-link. Therefore, the higher the metric, the less likely a node to be elected as cluster-head. As we can see from Algorithm 1, if node u is MEMBER and has the requirements to become HEAD, it checks whether the metric of its cluster-head is 1.5 times greater than its own metric, as shown at line 5. In that case, u becomes HEAD, otherwise it remains a MEMBER. Such an approach is introduced in order to avoid the election of several HEAD nodes close to each other, and reduce the overall number of connections to the BS and, thus the global energy consumption. We dened a second threshold for the signal strength on the BS-link to avoid frequent cluster-head elections and resignations when such a parameter continuously varies around the main threshold. Regarding the resignation of a HEAD node, it may occur in two cases. In the rst case, the node has no longer the requirements to be a cluster-head, since it has not enough energy or it is no longer able to directly communicate with the BS. The second case occurs when the considered node receives an announcement from a new HEAD in the neighborhood that has a metric lower than its, as we explain in the next paragraph. When a node resigns as HEAD, it destroys its cluster and, in the second case, it becomes MEMBER of another cluster.

Cluster formation and destruction

The cluster-heads form the clusters in the network and periodically connect to the BS to deliver the sensing data received from other nodes. The clusters are built by broadcasting a bounded-hop RANN in which the header eld named Time To Live (TTL) is set to the number of hops that can be traversed by the message before to be discarded. In this way, only the nodes that are at a limited hop-distance from the considered HEAD are recruited into the cluster.

The RANN messages are periodically broadcast by the HEAD nodes in their cluster in order to keep the MEMBER nodes up-to-date about their metric.

If a non-clustered node receives a RANN message from a HEAD node, it immediately becomes MEMBER of the announced cluster. However, if the considered node receives multiple RANN messages from dierent cluster-heads, it then compares their metrics and joins the cluster with the lowest one. In the case a HEAD node receives a RANN message, it checks whether its metric is 1.5 times lower than the metric of the announced HEAD. If the latter condition holds, the considered node resigns as HEAD, destroys its cluster and joins the cluster of the HEAD announced in the RANN message. Such a condition has been dened in order to avoid frequent cluster destruction when the HEAD nodes are close to each other. After joining a cluster, the MEMBER nodes store in the routing table the last hop traversed by the received RANN in order to have a route to the HEAD. As a result, a routing tree is formed into the clusters between the MEMBER nodes and the cluster-head.

The size of the clusters is decided by the HEAD nodes according to their operating parameters. In this way, CESAR aims to concentrate the collection of the sensing data in the HEAD nodes with better conditions in order to smartly balance the energy consumption between them.

When a HEAD node resigns, it destroys its cluster by sending a ROFF message to all the members that leave the cluster and become LOOSE nodes upon the message reception.

The on-demand scheme

As already explained, the LOOSE nodes do not have any routes to any clusterhead, so they are not able to transmit data to the BS. Thus, when one of them has some data to deliver to the server, it starts a special procedure that aims to discover a cluster nearby.The discovering procedure consists of broadcasting a hop-bounded REQR message that will be received by the nodes in the neighborhood. When a MEMBER node receives such a message, it replies with a REP message containing information about the status of the HEAD of its cluster. The discovery process continues until a cluster is found or the max hop distance is reached. In the latter case, the process is reinitialized and restarted after a certain time interval.

For instance, let's assume that the node e 2 in Figure 2 needs to send the sensing data to the BS. It broadcasts a REQR message in which the TTL is set to TTL_MAX. The nodes d 1 , d 2 , d 3 , e 1 and e 3 are not MEMBER nodes, so they do not reply to the request. Nodes c 1 , c 2 , c 3 , members of the cluster created by the node b 3 receive the REQR and reply with a REP message that reports the metric of their cluster-head. Such a message passes through the nodes traversed by the latest REQR message. In the gure, we suppose that the REP messages are received by the node d 3 and forwards the message to the requesting node e 2 . The latter stores in the routing table the next hop on the path towards to the reported cluster and records the metric of its HEAD. After that, it can deliver the collected data to the HEAD node b 3 by passing through the nodes d 3 and c 3 .

If there are more than one cluster in the nearby, the considered node may receive more than one REP message, and then it should evaluate to which cluster to deliver its data by comparing the metrics of the respective cluster-heads.

Data aggregation

The aggregation of the sensing data allows the reduction of the time needed for transmissions and receptions decrease, and thus, the energy consumption and the risks of collisions decrease as well. The data aggregation in CESAR can be performed in three dierent ways. The least strong approach is the aggregation of data only at the cluster-heads before deliver it to the BS. A stronger approach is to aggregate data also at the member nodes at the borders of the clusters. In this case, such nodes collect the data coming from the LOOSE nodes and aggregate it before transmitting to the cluster-head. Finally, the strongest way is to perform the data aggregation at the cluster-heads and at every member of the clusters. However, in this paper we evaluate CESAR without performing any aggregation of data.

Routing maintenance and recovery

The CESAR algorithm uses ACK messages to acknowledge every data packet. Thus, all the nodes expect to receive an ACK message as conrmation that the transmission succeeded and the data was received by the cluster-head. If no ACK messages are received after a prexed timeout, then the sender node considers the packet lost and transmits it again to the same HEAD. If the transmission fails 3 times, then the considered node becomes LOOSE and restarts the ondemand scheme to nd another route to the same HEAD or to another cluster. Thus, we set a specic timeout in the MEMBER nodes to check if the RANN messages are periodically received. Such a timer is restarted at every reception of RANN messages from the cluster-head and if the timeout occurs, then the node leaves the cluster and becomes LOOSE.

Performance evaluation

In this section we simulate the CESAR algorithm in WSNET [11] and we analyze the obtained results in order to compare its performances with two of the most popular clustering protocols studied in the literature: LEACH [START_REF] Heinzelman | An application-specic protocol architecture for wireless microsensor networks[END_REF] and HEED [START_REF] Younis | Distributed clustering in ad-hoc sensor networks: a hybrid, energy-ecient approach[END_REF]. We consider a network in which the nodes are positioned in a 3d grid with dimensions 160x160x110 m 3 and for each experiment we vary the number of sensors in the same area. Thus, the density and the distance between the nodes change at each scenario. In such a way, we analyze the behavior of the algorithm in low-density and high-density networks.

Since we want to use a realistic model for the energy consumption, we consider the transmission and the reception powers reported in the datasheets of XBee and XBee-PRO DigiMesh 2.4 provided by Digi International [12]. We considered two dierent devices since CESAR uses a multi-hop approach and, therefore it needs a lower transmission power than LEACH and HEED which are single-hop routing protocols.

CESAR has some critical parameters that should be congured in order to evaluate its performances. Such parameters are set to optimized values obtained from long series of simulation as reported in Table 1. Regarding the other simulation parameters we set to 6 hours the virtual duration for each experiment and we suppose to receive from the application layer 4096 Bytes of sensing data every 10 minutes. The energy available at each sensor at the beginning of the simulations is 100 Joules. We believe that the latter values are fair enough to simulate a generic application running on sensors with a generic hardware.

Data delivery

In many applications in which the sensor networks are employed, the robustness is a primary requirement to ensure the delivery of the sensing data to the BS. In this section, we measure the percentage of data generated by the sensors that is successfully delivered to the BS, with dierent experiments in which we change the number of nodes in the sensing area.

As we can observe in Figure 3, the LEACH and HEED algorithms are less robust than CESAR, which uses dedicated mechanisms to recover and maintain the routes between the nodes as explained in Section III. The losses experienced by the rst two algorithms are mainly caused by the interferences between the cluster-heads in the set-up phase, in which some messages related to the cluster formation may be lost and ,thus, some nodes are not able to join any cluster. Moreover the LEACH algorithm experiences more data losses because of its cluster-head selection mechanism which, unlike HEED and CESAR, does not take account of the distribution of the cluster-heads into the network.

Energy consumption

The energy consumed by each node is measured by performing dierent tests in which we increase the number of the nodes in the sensing area. As we can see from the results shown in Figure 4, CESAR is less expensive in terms of energy and more scalable than LEACH and HEED, thanks to the mechanisms described in Section III.

The graphs show that CESAR is also more scalable than LEACH and HEED which suer of interferences and high overhead for the assignation of the timeslots by the cluster-heads to the members of the cluster.

Conclusions

The algorithm described in this paper combines the clustering and the ondemand approaches in order to reduce the energy consumption in the whole network. A new cluster-head selection mechanism is proposed in order to consider the situations in which the nodes have limited battery capacity and not all of them are capable to communicate with the BS to which deliver the own sensing data. The further mechanisms employed for the reduction of the energy consumption and improvement of the robustness make CESAR suitable for many low data rate applications of WSNs. The simulations described in Section IV show that CESAR performs better than some popular algorithms such as LEACH and HEED, and the experiments performed on the FIT-IoT-lab [START_REF] Burin Des Roziers | Using senslab as a rst class scientic tool for large scale wireless sensor network experiments[END_REF] platform show that our solution well perform also in real sensor networks. Thanks to the on-demand mechanism and the adaptability of the cluster size, we believe that CESAR is also suitable for networks composed of mobile sensors. A new metric can be investigated to take account of the mobility of the nodes and adapt the above-mentioned features to the dynamic of the network topology. Regarding future developments, CESAR will be tested in combination with some Low Power Listening (LPL) protocols , such as X-MAC [START_REF] Buettner | X-mac: A short preamble mac protocol for duty-cycled wireless sensor networks[END_REF] and LA-MAC [START_REF] Corbellini | La-mac: Low-latency asynchronous mac for wireless sensor networks[END_REF], in order to gure out which one is the best choice to minimize the energy consumption and ensure the robustness of the network.

Fig. 1 .

 1 Fig. 1. Cluster formation. The RANN are broadcast by the HEAD nodes to form clusters of dierent sizes.

Fig. 2 .

 2 Fig. 2. On-demand scheme. The non-clustered nodes employ REQR messages to discover a cluster in the neighborhood and nd a route a HEAD node.

Fig. 3 .

 3 Fig. 3. Data delivery.

Fig. 4 .

 4 Fig. 4. Energy consumption at each node.

  Algorithm 1 CESAR (Cluster-head selection algorithm run on node u)

	Parameters:
	connectivity: signal strength measured on the BS-link
	battery: remaining energy
	conn_thr1, conn_thr2: thresholds for the connectivity parameter
	batt_thr: threshold for the battery parameter
	1: if ( connectivity(u) > conn_thr1 AND battery(u) > batt_thr ) then
	2:	if (u is HEAD) then
	3:	Send RANN;
	4:	else if (u is MEMBER) then
	5:	if (metric(head of u) > 1.5 * metric(u) then
	6:	Become HEAD;
	7:	Send RANN;
	8:	end if
	9:	else if (u is LOOSE) then
	10:	Become HEAD;
	11:	Send RANN;
	12:	end if
	13: else if ( connectivity(u) > conn_thr2 AND battery(u) > batt_thr ) then
	14:	if (u is HEAD) then
	15:	Send RANN;
	16:	end if
	17: else if ( connectivity(u) < conn_thr2 OR battery(u) < batt_thr ) then
	18:	if (u is HEAD) then
	19:	Become LOOSE;
	20:	Send ROFF to destroy the cluster;
	21:	end if
	22: end if

Table 1 .

 1 Critical parameters of CESAR

	Connectivity threshold 1 40%
	Connectivity threshold 2 30%
	Battery threshold	20%
	Status update frequency every 2 min
	RANN frequency	every 1 min
	Maximum cluster size	5 hops
	Data delivery frequency every 10 min

Acknowledgements

This work was partially supported by a grant from CPER Nord-Pas-de-Calais /FEDER Campus Intelligence Ambiante.


Christophe Hézode

Hélène Fontaine

Céline Dorival

Fabien Zoulim

Dominique Larrey

Valérie Canva

Victor De Ledinghen

Thierry Poynard

Didier Samuel

Marc Bourlière

Christophe Hezode

Helene Fontaine

Celine Dorival

Valerie Canva

Marc Bourliere

Laurent Alric

Jean-Jacques Raabe

Jean-Pierre Zarski

Patrick Marcellin

Ghassan Riachi

Pierre-Henri Bernard

Veronique Loustaud- Ratti

Olivier Chazouilleres

Armand Abergel

Dominique Guyader

Sophie Metivier

Albert Tran

Vincent Di Martino

Xavier Causse

THONG DAO 25 Damien Lucidarme

Isabelle Portal

Patrice Cacoub

Jerome Gournay

Veronique Grando-Lemaire

Patrick Hillon

Pierre Attali

Thierry Fontanges

Isabelle Rosa

Ventzislava Petrov-Sanchez

Yoann Barthe

Jean-Michel Pawlotsky

Stanislas Pol

Fabrice Carrat

Jean-Pierre Bronowicki

Hélène Fontaine

Céline Dorival

Jean-Pierre Bronowicki

Hélène Fontaine

Jean- Pierre Bronowicki

Valérie Canva

Jean- Jacques Raabe

Véronique Loustaud-Ratti

Sophie Métivier

Vincent Di Martino

Véronique Grando-Lemaire

Jérome Gournay

Thong Dao

Effectiveness of telaprevir or boceprevir in treatment-experienced patients with HCV genotype 1 infection and cirrhosis

Keywords: chronic hepatitis C, cirrhosis, boceprevir, telaprevir

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

-Laurent Alric has been a clinical investigator, speaker and/or consultant for Bristol-Myers Squibb, Janssen Pharmaceuticals, Merck Sharp & Dohme, and Roche.

-Jean-Jacques Raabe has nothing to disclose.

-Jean-Pierre Zarski has been speaker and/or consultant for Boehringer Ingelheim, Bristol-Myers Squibb, Gilead Sciences, Janssen Pharmaceuticals, Merck Sharp & Dohme, Roche, and Siemens.

-Patrick Marcellin has been clinical investigator, speaker and/or consultant for Abbvie, Alios BioPharm, Boehringer Ingelheim, Bristol-Myers Squibb, Gilead Sciences, Janssen Pharmaceuticals, Merck Sharp & Dohme, Novartis, Pfizer, Roche, and Vertex pharmaceuticals.

-Ghassan Riachi has nothing to disclose.

-Pierre-Henri Bernard has nothing to disclose.

-Véronique Loustaud-Ratti has been clinical investigator, speaker and/or consultant for Bristol-Myers Squibb, Gilead Sciences, Janssen Pharmaceuticals, Merck Sharp & Dohme, and Roche. She received grant/research support from Bristol-Myers Squibb, and Roche.

-Olivier Chazouilleres has been clinical investigator, speaker and/or consultant for Aptalis, Echosens, Gilead Sciences, Mayoly-Spindler and Roche.

-Armand Abergel has been clinical investigator, speaker and/or consultant for Janssen Pharmaceuticals, Merck Sharp & Dohme, and Roche.

-Dominique Guyader has been a clinical investigator, speaker and/or consultant for Boehringer Ingelheim, Bristol-Myers Squibb, Gilead Sciences, Janssen Pharmaceuticals, Merck Sharp & Dohme, and Roche.

-Sophie Métivier has nothing to disclose.

-Albert Tran has been a clinical investigator for Janssen Pharmaceuticals, and Merck Sharp & Dohme.

-Vincent Di Martino has been a clinical investigator, speaker and/or consultant for Bristol-Myers Squibb, Gilead Sciences, Merck Sharp & Dohme, and Roche.

-Xavier Causse has been consultant for Janssen Pharmaceuticals, and Merck Sharp & Dohme.

-Thong Dao has been consultant for Gilead Sciences, and Merck Sharp & Dohme.

-Damien Lucidarme has nothing to disclose.

-Isabelle Portal has nothing to disclose.

-Patrice Cacoub has received consulting and lecturing fees from Bristol-Myers Squibb, Gilead, Roche, Merck Sharp, Servier, and Vifor.

-Jérome Gournay has been speaker and/or consultant for Bristol-Myers Squibb, Gilead Sciences, Janssen Pharmaceuticals, Merck Sharp & Dohme, and Roche.

-Véronique Grando-Lemaire has nothing to disclose.

-Patrick Hillon has been a clinical investigator, speaker and/or consultant for Gilead Sciences, Janssen Pharmaceuticals, Merck Sharp & Dohme, and Roche.

-Pierre Attali has been a clinical investigator for Boehringer Ingelheim, Bristol-Myers Squibb, Cytheris, Gilead Sciences, and Novartis.

-Thierry Fontanges has been speaker and/or consultant for Bristol-Myers Squibb, Gilead Sciences, Janssen Pharmaceuticals, and Merck Sharp & Dohme.

-Isabelle Rosa has been speaker and/or consultant for Janssen Pharmaceuticals and Merck Sharp & Dohme.

-Ventzislava Petrov-Sanchez has nothing to disclose.

-Yoann Barthe has nothing to disclose.

Introduction

Two direct-acting antiviral drugs, telaprevir (TVR) and boceprevir (BOC), both hepatitis C virus (HCV) non-structural 3-4A protease inhibitors (PIs), were recently approved in combination with pegylated interferon (Peg-IFN) and ribavirin (RBV) for the treatment of chronic HCV genotype 1 infection (1-4). Phase 3 trials showed significantly improved sustained virological response (SVR) rates compared with Peg-IFN/RBV alone in both treatment-naïve and treatment-experienced patients [START_REF] Poordad | Boceprevir for untreated chronic HCV genotype 1 infection[END_REF][START_REF] Bacon | Boceprevir for previously treated chronic HCV genotype 1 infection[END_REF][START_REF] Jacobson | Telaprevir for previously untreated chronic hepatitis C virus infection[END_REF][START_REF] Zeuzem | Telaprevir for retreatment of HCV infection[END_REF]. However, the gain in efficacy was associated with an increased frequency of side effects, including a 20% incremental anaemia with both PIs, dysgeusia with BOC, and frequent skin and gastrointestinal disorders with TVR (1-4). Patients with cirrhosis have the greatest need for antiviral treatment given the higher survival rates in those who achieve an SVR compared with non-responders, as a result of less frequent liver failure and hepatocellular carcinoma [START_REF] Bruno | Predicting mortality risk in patients with compensated HCV-induced cirrhosis: a long-term prospective study[END_REF][START_REF] Dienstag | A prospective study of the rate of progression in compensated, histologically advanced chronic hepatitis C[END_REF][START_REF] N'kontchou | Risk factors for hepatocellular carcinoma in patients with alcoholic or viral C cirrhosis[END_REF][START_REF] Sangiovanni | The natural history of compensated cirrhosis due to hepatitis C virus: A 17-year cohort study of 214 patients[END_REF][START_REF] Bruno | Sustained virological response to interferonalpha is associated with improved outcome in HCV-related cirrhosis: a retrospective study[END_REF][START_REF] Mallet | Brief communication: the relationship of regression of cirrhosis to outcome in chronic hepatitis C[END_REF][START_REF] Morgan | Outcome of sustained virological responders with histologically advanced chronic hepatitis C[END_REF][START_REF] Van Der Meer | Association between sustained virological response and all-cause mortality among patients with chronic hepatitis C and advanced hepatic fibrosis[END_REF]. These patients are considered difficult-to-treat due to both a lower SVR rate than in non-cirrhotics and an increased risk of therapy. However, the administration of Peg-IFN/RBV in patients with compensated cirrhosis has proven to be feasible [START_REF] Poordad | Boceprevir for untreated chronic HCV genotype 1 infection[END_REF][START_REF] Bacon | Boceprevir for previously treated chronic HCV genotype 1 infection[END_REF][START_REF] Jacobson | Telaprevir for previously untreated chronic hepatitis C virus infection[END_REF][START_REF] Zeuzem | Telaprevir for retreatment of HCV infection[END_REF][START_REF] Bruno | Efficacy and safety of peginterferon alfa-2a (40KD) plus ribavirin in hepatitis C patients with advanced fibrosis and cirrhosis[END_REF][START_REF] Marrache | Safety and efficacy of peginterferon plus ribavirin in patients with chronic hepatitis C and bridging fibrosis or cirrhosis[END_REF][START_REF] Carrion | Antiviral therapy increases the risk of bacterial infections in HCV-infected cirrhotic patients awaiting liver transplantation: A retrospective study[END_REF][START_REF] Pol | Efficacy and safety of telaprevir-based regimens in cirrhotic patients with HCV genotype 1 and prior peginterferon/ribavirin treatment failure: subanalysis of the REALIZE phase III study[END_REF]. This patient population is generally under-represented in registration clinical trials, and the cirrhotics included in these studies are highly selected and do not reflect well the actual population of HCV-infected cirrhotics who are potential candidates for direct-acting antiviral-based regimens.

The French "Autorisation Temporaire d'Utilisation" (temporary authorization for use) is an early access programme that gives patients access to a medicinal product before it is granted a marketing authorization. Patients with compensated cirrhosis who were relapsers or partial responders to a prior course of Peg-IFN/RBV were treated prior to approval of TVR and BOC within the framework of this programme, beginning in January 2011. Null responders were subsequently given access to these therapies when the drugs were approved.

The ANRS CO20 "Compassionate Use of Protease Inhibitors in viral C Cirrhosis" (CUPIC) study is a cohort study sponsored by the French National Agency for Research on AIDS and Viral Hepatitis (ANRS) that enrolled patients benefiting from the temporary authorization for use early access programme in selected centres. The objective of this cohort study was to evaluate the efficacy and safety of triple combination regimens including TVR or BOC in treatment-experienced cirrhotic patients in the real-life setting. This article presents the week 60 efficacy (including SVR12) and safety results of this study.

Patients and methods

Patients

The ANRS CO20-CUPIC cohort is a national multicentre prospective cohort study conducted in 56 French centres (ClinicalTrials.gov number NCT01514890). From February 2011 to April 2012, patients with compensated cirrhosis (Child-Pugh class A) chronically infected with HCV genotype 1 who failed on a prior course of IFN with or without RBV and started triple combination therapy in the French Early Access Programme in the participating centres were included. Initially, only relapsers (or patients with a virological breakthrough) and partial responders were included in the Early Access Programme and recruited in the cohort.

Null responders started to be included in the cohort study after the approval of both PIs in September 2011. (Supplementary materials).

In all instances, the diagnosis of cirrhosis was confirmed by a liver biopsy or a non-invasive test (e.g. Fibrotest ® , Fibroscan ® , Fibrometer ® or Hepascore ® ) at the investigator's discretion, according to the French recommendations [START_REF] Fontaine | Guidelines for the diagnosis of uncomplicated cirrhosis[END_REF]. The non-inclusion criteria were an HIV and/or hepatitis B virus co-infection, renal insufficiency (defined by creatinine clearance <50 mL/min), an organ graft, and contraindication to the use of interferon.

Written informed consent was obtained from each patient before enrolment. The protocol was conducted in accordance with the Declaration of Helsinki and French law for biomedical research and was approved by the "Ile de France IX" Ethics Committee (Créteil, France).

Objectives

The goals of the study were to evaluate the virological response defined as undetectable HCV RNA 12 weeks after treatment discontinuation (SVR12) based on the Food and Drug Administration recommendations and its safety over the full duration of treatment.

Treatments

The choice between a TVR-or BOC-based regimen and the use of a lead-in were was at the investigator's discretion. The patients were not randomized; thus the study did not allow for comparisons between the two treatment regimens. The treatment schedules and recommended stopping rules are described in the Supplementary materials.

HCV RNA level monitoring

HCV RNA levels were measured at baseline and at weeks 4, 8, 12, 16, 24, 36, and 48 of therapy, and 12 and 24 weeks after its withdrawal, with a real-time PCR-based assay, either COBAS AmpliPrep ® /COBAS TaqMan ® (Roche Molecular Systems, Pleasanton, California) with a lower limit of detection of 15 IU/mL, or m2000 SP /m2000 RT (Abbott Molecular, Des Plaines, Illinois), with a lower limit of detection of 12 IU/mL. Both assays have been validated for their accuracy in patients infected with HCV genotype 1 [START_REF] Chevaliez | Overestimation and underestimation of hepatitis C virus RNA levels in a widely used real-time polymerase chain reaction-based method[END_REF][START_REF] Chevaliez | Performance of the Abbott real-time PCR assay using m2000sp and m2000rt for hepatitis C virus RNA quantification[END_REF].

Safety assessments

The safety profile assessment is described in the Supplementary materials. Data on all adverse events were collected until the 60 th week of follow-up. The definition of clinical and laboratory grade 3 or 4 adverse events, serious adverse event (SAE) and serious cutaneous adverse reaction [START_REF] Cacoub | Dermatological side effects of hepatitis C and its treatment: patient management in the era of direct-acting antivirals[END_REF] are described in the Supplementary materials. The factors associated with severe complications of cirrhosis (infection, hepatic decompensation) or death were explored. In addition, the factors associated with grade 3 or 4 anaemia or blood transfusion were also analyzed. The management of anaemia (RBV dose reductions and/or erythropoietin administration, authorized in France when the haemoglobin level is below 10 g/dL, and/or blood transfusion) was at the investigator's discretion. Use of other hematopoietic growth factors for neutropenia or thrombocytopenia was also recorded.

Statistical analysis

We estimated that 900 patients would be needed for the cohort to have a 3% precision in estimating the SVR. The efficacy and safety interim analysis was not pre-specified in the protocol, but decided by the Scientific Committee in February 2012 based on preliminary reports of safety findings. Therefore, no sample size was pre-defined. All patients who reached week 60 of follow-up by March 1, 2013 were included in the present analysis.

Early virological breakthrough was defined as an undetectable HCV RNA before week 12 of triple therapy with detectable HCV RNA at week 12; late virological breakthrough as an undetectable HCV RNA after week 12 with detectable HCV RNA at week 48; relapse as an undetectable HCV RNA at week 48 with detectable HCV RNA at week 60 (i.e. week 12 posttreatment); non-response as persistently detectable HCV RNA during treatment; and SVR12 as an undetectable HCV RNA at week 60, i.e. 12 weeks after the end of therapy. Patients with detectable HCV RNA at week 12 had to stop therapy, according to the pre-defined stopping rules. Efficacy and safety analyses were performed on an intent-to-treat basis. Missing HCV RNA values at week 12 post-therapy were considered as treatment failures. Missing intermediate HCV RNA values were considered as undetectable when the preceding and subsequent HCV RNA levels were undetectable, and detectable otherwise. Blood parameters were categorized according to thresholds used to define eligibility in a recently published randomized trial of PI-based triple therapy [START_REF] Bacon | Boceprevir for previously treated chronic HCV genotype 1 infection[END_REF].

Comparisons between independent groups used the Mann-Whitney test for continuous variables or Fisher's exact test for categorical variables; and within-group comparisons were made using the Wilcoxon signed-rank test for continuous variables or McNemar's

Chi square tests for categorical variables. Logistic regression models were used to identify predictors of SVR12, severe complications and grade 3/4 anaemia or blood transfusion. For

Results

Baseline demographics and disease characteristics

Six hundred and sixty patients over 18 years of age were enrolled in 56 centres; 511 patients reached week 60 of follow-up and were thus included in this analysis, including 299 treated with TVR and 212 with BOC. The baseline demographics and disease characteristics are shown in Table 1. Of the 511 patients, 346 (67.7%) were men, and their mean age was 57.0±9.7 years. The prior treatment response was a relapse or a virological breakthrough in 226 cases (44.3%, including 17 patients with a virological breakthrough), a partial response in 229 cases (44.8%), a null response in 41 cases (8.0%) and undetermined in the remaining 15 cases (2.9%). At baseline, cirrhosis was compensated and classified as Child-Pugh A in 483 patients (94.5%), and the MELD score, available in 460 patients (90.0%), was <13 in 433 of them (94.1%). The mean albumin level was 40.2±4.9 g/dL and the mean platelet count was 148,000±67,000/mm 3 . When considering age and laboratory parameters, at least one exclusion criterion from the phase III studies in treatment-experienced patients (e.g. REALIZE and RESPOND-2) (2,4) was reported in 164 (32.1%) and 227 (44.4%) patients treated with TVR and BOC, respectively. The patients were infected with HCV subtype 1b in 52.8% of cases and 62.6% of them had a baseline HCV RNA level ≥800,000 IU/mL. The mean treatment duration was 49.0±26.4 weeks with TVR and 46.4±26.8 weeks with BOC.

The mean duration of PI use was 11.0±2.5 weeks with TVR and 32.4±15.1 weeks with BOC.

Efficacy of triple therapy including TVR

The intent-to-treat (ITT) efficacy analysis in the 299 patients who received TVR is shown in Figure 1A. The primary endpoint, ie, SVR12, was achieved in 92/124 (74.2%) patients with a relapse or a virological breakthrough (89/117, 76.1% and 3/7, 42.9%, respectively), 54/135 partial responders (40.0%), 6/31 null responders (19.4%) and 3/9 undetermined patients, p<0.0001.

Among the 155 patients who achieved an SVR (all groups together), 33 (21.3%) had to discontinue treatment prematurely, including 8 before and 25 after week 12. The use of a lead-in was at the investigator's discretion. Forty-five patients receiving TVR were treated with a lead-in phase: their SVR12 rate was lower than in those treated without a lead-in phase (15/45, 33.3% versus 140/254, 55.1%; p=0.0092). Patients treated with a lead-in were older (59.5 vs 56.7 years, p=0.036) and experienced more adverse events leading to premature treatment discontinuation: 35.6% (16/45) versus 23.8% (55/254) in the patients without leadin (p=0.0564). The SVR12 rate was significantly higher in patients infected with HCV subtype 1b than 1a: 61.4% (102/166) versus 34.3% (35/102); p<0.0001) (Figure 1B). The difference was not significant between patients with more or less than 800,000 IU/mL of HCV RNA at baseline: 48.7% (90/185) versus 57.5% (65/113); p=0.1219. The patients who achieved a rapid virological response (undetectable HCV RNA at treatment week 4 or at treatment week 8 in case of lead-in) were more likely to achieve an SVR: 63.1% (125/198) versus 29.7% (30/101); p<0.0001 (Figure 1C). Among the 144 patients who failed on triple combination therapy, 37 met the stopping rule criteria, including 6 (2.0% of the 299 treated patients) who experienced an early virological breakthrough and 31 (10.4%) who did not respond. A late virological breakthrough was observed after discontinuing TVR in 49 patients (16.4%), a relapse in 44 patients (14.7%) and 14 patients (4.7%) failed due to other reasons, including loss to follow-up [START_REF] N'kontchou | Risk factors for hepatocellular carcinoma in patients with alcoholic or viral C cirrhosis[END_REF], death (4), or missing HCV RNA level measurements (3).

Efficacy of triple therapy including BOC

The intent-to-treat (ITT) efficacy analysis in the 212 patients who received BOC is shown in Figure 2A. The primary endpoint, ie, SVR12, was achieved in 55/102 (53.9%) patients with a relapse or a virological breakthrough (50/92, 54.3% and 5/10, 50%, respectively), 36/94 partial responders (38.3%), 0/10 (0%) null responders, and none of the undetermined patients, p=0.0004.

Among the 91 patients who achieved an SVR (all groups together), 12 (13.2%) had to discontinue treatment prematurely, including 2 before and 10 after week 16, i.e. lead-in plus 12 weeks of BOC.

The SVR rate was significantly higher in patients infected with HCV subtype 1b than 1a: 52.9% (55/104) versus 33.3% (29/87); p=0.0084 (Figure 2B). The difference was not significant between patients with more or less than 800,000 IU/mL of HCV RNA at baseline: 43.7% (59/135) versus 41.7% (30/72); p=0.8829. Higher SVR rates were observed in patients who exhibited a ≥1 log 10 decline of HCV RNA level from baseline at treatment week 4 (end of lead-in) than in those who did not: 62.6% (62/99) versus 25.7% (29/113); p<0.0001 (Figure 2C). The SVR12 was also significantly more frequent in patients with undetectable HCV RNA at treatment week 8 (week 4 of BOC administration): 71.6% (58/81) versus 25.2% (33/131); p<0.0001 (Figure 2C), and in patients who exhibited a ≥3 log 10 decline of HCV RNA level from baseline or had undetectable HCV RNA at treatment week 8: 58.4% (87/149) versus 6.3% (4/63); p<0.0001.

Among the 121 patients who failed on triple combination therapy, 62 (29.2% of the 212 treated patients) did not respond. A virological breakthrough was observed after discontinuing BOC in 19 patients (9.0%), a relapse in 36 patients (17.0%) and 4 patients (1.9%) failed due to other reasons, including death (2), or missing HCV RNA level measurements [START_REF] Bacon | Boceprevir for previously treated chronic HCV genotype 1 infection[END_REF].

Independent predictors of SVR12

Patients from the TVR and BOC groups were pooled to identify factors related to the SVR12.

The results of the univariate analysis are shown in Table 2. Four independent factors predicting the SVR12 were identified: the prior treatment response, including relapse or breakthrough (odds ratio [OR]=2.96, 95% CI: 1.97-4.44, p<0.0001) and null response (OR=0.28, 95% CI: 0.11-0.73, p=0.0086) versus partial response; no lead-in phase (OR=1.78, 95% CI: 1.20-2.66, p=0.0044); a platelet count >100,000/mm 3 (OR=2.15, 95% CI: 1.34-3.45, p=0.0015); and an HCV subtype 1b (OR=2.50, 95% CI: 1.62-3.85, p<0.0001) versus subtype 1a. A nearly significant trend was noted with serum albumin ≥35g/L (OR=1.86, 95% CI: 0.97-3.56, p=0.0614).

Safety

Tables 3 and4 show the safety profiles of the triple therapies including TVR or BOC, respectively. A high incidence of SAEs (n=850) was observed during the 60 weeks of followup. SAEs occurred in 255 patients (49.9%), leading to early discontinuation of all drugs in 108 (21.1%). The probability of remaining free of any serious adverse event is represented in the supplementary materials (Figures 1 and2).

Deaths occurred in 11 patients (2.2%) during the course of therapy, mainly related to severe infections: septicaemia (n=4), pneumonia (n=3), endocarditis (n=1). Other causes of death were hepatic decompensation related to variceal bleeding (n=2) and massive bleeding due to an aortic aneurysm (n=1). Death occurred after a median time of 20 weeks and two deaths occurred during the lead-in phase, i.e. without PI.

Apart from death, severe complications, including severe infections and hepatic decompensation, occurred in 43 patients (8.4%). Severe infections were reported in 28 patients (5.5%), including pneumonia (n=5), septicaemia (n=5), acute pyelonephritis (n=3), cutaneous infection (n=4), acute cholecystitis (n=2), infectious diarrhoea (n=2), endocarditis (n=1), ascites infection (n=1), and others (n=5). These infectious complications occurred after a median duration of antiviral treatment of 13.9 weeks (range: 2.3 to 47.3 weeks) and during the lead-in phase in one patient. The peg-IFN dose was reduced or discontinued in 10 patients (35.7%) before the occurrence of severe infection, and in an additional 16 patients (57.1%) after the onset of severe infection. In addition, episodes of hepatic decompensation (without death or infection) were observed in 15 patients (3.1%): ascites in 14 (93.3%), encephalopathy in 1 (6.7%). 3 and4).

The incidence of grade 2 anaemia (8.0 to ≤ 9.0 g/dL) was 22.9% (117/511). Grade 3-4 anaemia (haemoglobin ≤8.0 g/dL) occurred in 11.2% of cases (57/511). Out of 174 patients with anaemia, 168 (96.0%) received erythropoietin, the RBV dose was reduced or discontinued in 133 (76.4%), and blood transfusions were administered to 78 (44.8%) (Tables 3 and4). Ninety-four patients (18.4%) experienced grade 3 or 4 anaemia and/or blood transfusion. In multivariate analysis, the predictors of severe anaemia or blood transfusion were as follows: age per 10-year increase (OR = 2.08, 95% CI 1.56-2.77, p < 0.0001), baseline Hb ≤ 12 g/dL for females and ≤13 g/dL for males (OR = 4.30, 95% CI 2.21-8.37, p < 0.0001) and albumin <35 g/L (OR=1.95, 95% CI: 1.02-3.73, p=0.0448).

An increased creatinine level, defined as >80 µmol/L in women and >110 µmol/L in men, was observed during the treatment in the following percentages of patients: 1.04% at baseline, 4.6% after the first month of TVR (W4 or W8 in the case of lead-in), 6.6% at the end of TVR (W12 or W16 in the case of lead-in), 0% at W24 and 1% at the end of treatment (EOT) in the TVR cohort and 1.16% at baseline, 3.9% at W8, 5.8% at W16, 5.3% at W24 and 2.77 at EOT in the BOC cohort.

Risk/benefit ratio of triple therapy

Table 5 shows the SVR12 rates and the rates of death and severe complications according to the two baseline predictors of severe complications and death identified in the week 16 interim analysis, i.e. albumin level and platelet count [START_REF] Hézode | Triple therapy in treatment-experienced patients with HCV-cirrhosis in a multicentre cohort of the French Early Access Programme (ANRS CO20-CUPIC)-NCT01514890[END_REF].

Discussion

The CUPIC cohort is a large cohort of treatment-experienced cirrhotic patients infected with HCV genotype 1 treated with BOC or TVR in combination with peg-IFN and RBV in the real-life setting. Because the choice of TVR or BOC was made by the treating physicians and the patients were not randomized, no comparison can be made between the two PIs. However, our results provide, for each drug regimen, an accurate reflection of what can be expected in terms of antiviral efficacy and safety in this particular population with a clear indication for antiviral therapy, which was poorly documented in phase II and phase III trials. Altogether, our results demonstrate a substantial benefit of adding BOC or TVR to Peg-IFN and RBV in these patients, compared with the 0% to 10% global SVR rates in treatment-experienced cirrhotic patients retreated with Peg-IFN and RBV alone in phase III trials [START_REF] Bacon | Boceprevir for previously treated chronic HCV genotype 1 infection[END_REF][START_REF] Zeuzem | Telaprevir for retreatment of HCV infection[END_REF].

The present study identifies baseline predictors of SVR12, including the prior treatment response, the absence of a lead-in phase, HCV subtype 1b, and a platelet count >100,000/mm 3 , while a nearly significant trend was observed for serum albumin ≥35 g/L.

These parameters can now be used in this population to guide treatment decisions and eventually to target therapy to those patients more likely to achieve high SVR rates.

Not surprisingly, the relapsers were the best candidates for triple therapy with BOC or TVR, with an SVR12 rate of 74.2% with TVR, a number in keeping with those reported in phase III trials. In contrast, the SVR12 rate was 53.9% with BOC, versus 83% in relapsers from the RESPOND-2 trial who received 48 weeks of treatment including 44 weeks of triple therapy.

The difference could be explained by the small number of patients included in this trial compared with our cohort (18 versus 92 patients, respectively), and by the fact that patients with advanced fibrosis were pooled with cirrhotics in RESPOND-2 [START_REF] Bruno | Efficacy and safety of boceprevir plus peginterferon-ribavirin in patients with HCV G1 infection and advanced fibrosis/cirrhosis[END_REF].

In the present study, the SVR12 rates in prior partial responders were of the order of 40%, in keeping with those reported in clinical trials in the same population [START_REF] Bacon | Boceprevir for previously treated chronic HCV genotype 1 infection[END_REF][START_REF] Zeuzem | Telaprevir for retreatment of HCV infection[END_REF]. In contrast, prior null responders rarely achieved an SVR12 (0% and 19.4% for BOC and TVR, respectively), suggesting that the approved triple therapy is not an appropriate therapeutic option in prior null responders with cirrhosis in the real-life setting. However, it is noteworthy that a small number of such patients were included. For BOC, data in prior null responders with cirrhosis are available in 3 patients in trials [START_REF] Vierling | Boceprevir for chronic HCV genotype 1 infection in patients with prior treatment failure to peginterferon/ribavirin, including prior null response[END_REF], and only 10 patients were included in our study. More patients (i.e. 31) were treated with TVR, and the observed SVR rate was of the same order as that reported in pooled non-cirrhotics and cirrhotics included in the REALIZE trial (14%) [START_REF] Pol | Efficacy and safety of telaprevir-based regimens in cirrhotic patients with HCV genotype 1 and prior peginterferon/ribavirin treatment failure: subanalysis of the REALIZE phase III study[END_REF].

In the TVR cohort, the SVR12 rate was lower in patients who received a lead-in phase. This result was unexpected. In the REALIZE trial, which included a large number of patients in both groups, no significant SVR difference was observed between the patients randomized to have or not to have a lead-in phase, including the same three subgroups of prior response as those in the present study [START_REF] Zeuzem | Telaprevir for retreatment of HCV infection[END_REF]. The baseline characteristics of our patients were similar in the two groups, except that patients with a lead-in phase were older. Moreover, we observed more treatment discontinuation due to adverse events in patients who received a lead-in. This result might have been biased by the fact that physicians decided to start with a lead-in phase in patients who were less likely to respond and/or more likely to develop severe complications of therapy.

As already partly reported in our week 16 interim analysis [START_REF] Hézode | Triple therapy in treatment-experienced patients with HCV-cirrhosis in a multicentre cohort of the French Early Access Programme (ANRS CO20-CUPIC)-NCT01514890[END_REF], the safety profile over 60 weeks of follow-up was poor for both treatment regimens, and was characterized by a large number of SAEs and the occurrence of severe complications, such as severe infection or hepatic decompensation, and death in 10.6% of patients. This may be explained in part by a greater mean age in our population compared with the phase III studies, and more severe liver disease with a relatively high rate of portal hypertension. The management of anaemia was at the investigator's discretion and involved erythropoietin prescription in most cases and RBV dose reduction more rarely. At the time of the study, clinicians were not convinced that anaemia could be managed first by RBV dose reduction without any impact on SVR. More recently, a prospective controlled trial has shown that RBV dose reduction can be the first strategy for anaemia management in treatment-naïve patients [START_REF] Poordad | Effects of ribavirin dose reduction vs erythropoietin for boceprevir-related anemia in patients with chronic hepatitis C virus genotype 1 infection-a randomized trial[END_REF]. However, it is worth noting that very few cirrhotic patients were included in this trial and that the SVR rate in cirrhotics was 57% in the "RBV dose reduction" arm versus 64% in the "erythropoietin" arm. So the validity of this strategy remains to be confirmed in treatment-experienced cirrhotic patients. As previously reported with Peg-IFN and RBV without PIs, one of the most frequent causes of severe infection was pneumonia [START_REF] Roomer | Risk factors for infection during treatment with peginterferon alfa and ribavirin for chronic hepatitis C[END_REF]. We did not investigate the effect of neutropenia and Peg-IFN dose reductions on the occurrence of these infections. However, vaccination against pneumococcus could be proposed before antiviral treatment. The number of patients was too small to evaluate the effect of this intervention. The other frequent cause of severe infection was septicaemia, raising the question of prophylactic antibiotic therapy during triple therapy in cirrhotic patients.

In five recent studies (including a meta-analysis) evaluating the natural history of cirrhotic patients with characteristics comparable to those from the CUPIC cohort, the annual incidence of deaths and/or liver decompensation varied from 6.2 to 11%, challenging the indication for triple therapy in this subgroup of patients [START_REF] Gomez | The natural history of compensated HCVrelated cirrhosis: a prospective long-term study[END_REF][START_REF] Alazawi | Systematic review: outcome of compensated cirrhosis due to chronic hepatitis C infection[END_REF][START_REF] Sangiovanni | The natural history of compensated cirrhosis due to hepatitis C virus: A 17-year cohort study of 214 patients[END_REF][START_REF] Bruno | Predicting mortality risk in patients with compensated HCV-induced cirrhosis: a long-term prospective study[END_REF][START_REF] Bisceglie | Prolonged therapy of advanced chronic hepatitis C with low-dose peginterferon[END_REF]. In the present analysis, two baseline parameters, the serum albumin level and platelet count, were found to be independent predictors of severe complications or death. Interestingly, these two parameters were also identified as strong predictors of SVR12 in our univariate analysis, although the association did not reach significance for albumin in the multivariate analysis when adjusted for other factors. In order to assess the risk/benefit ratio of triple therapy better in the difficultto-treat population of patients with compensated cirrhosis, we analyzed the SVR12 results with the two PIs according to baseline albumin level and platelet count. The subgroup of patients with both a low albumin level (<35 g/L) and a low platelet count (≤100,000/mm 3 ) at baseline represented 8.3% (37/448 patients) of the population with both predictors available.

These patients had a high risk (51.4%) of severe complications and a low SVR12 rate (27%), raising the question as to whether these patients, who are the most in need of therapy, should be treated with interferon-based triple therapy. By contrast, we identified the subgroup of patients with albumin ≥35 g/L and platelet count >100,000/mm 3 as representing the majority of our population (68.3%), with a low risk of severe complications (6.2%) and a high SVR12 rate (54.9%). This result shows that triple therapy can be used confidently in this subgroup of patients. The remaining patients had an incidence of severe complications between 12.2% and 16.1% and a modest efficacy of triple therapy (29.0% to 36.5%). These patients could benefit from prophylaxis of treatment complications and should undergo careful monitoring while on therapy. Alternatively, most of them can wait for all-oral, IFN-free regimens. The lack of a control group does not allow us to distinguish between severe events caused by treatment from those caused by the cirrhosis itself. However, the rate of observed severe events was much higher in this particular group of patient with advanced cirrhosis, low platelet count and low albumin level. Moreover, severe infection is a relatively rare event in non-treated compensated viral cirrhosis. Therefore, it's likely that the treatment contributed to these events.

Recently, a new stopping rule has been proposed based on the on-treatment response at week 8, as a result of post-hoc analysis of the databases of 5 clinical trials including patients with advanced fibrosis or cirrhosis treated with BOC. In this analysis, none of the 22 patients with a less than 3 log 10 HCV RNA decline from baseline achieved an SVR [START_REF] Vierling | Safety and efficacy of boceprevir/peginterferon/ribavirin (BOC/P/R) combination therapy for chronic HCV G1 patients with compensated cirhrhosis: a meta-analysis of five phase 3 clinical trials[END_REF]. Among our 63 patients with a less than 3 log 10 decline in HCV RNA level at week 8, only 6.3% achieved an SVR12. This result suggests that discontinuing triple therapy should be considered at week 12 in these difficult-to-cure patients, especially if they tolerate treatment poorly.

In conclusion, the CUPIC cohort study, performed in the real-life setting of patients with compensated cirrhosis associated with HCV genotype 1 infection, provides useful clinical information for the management of triple therapy in this difficult-to-treat population. It demonstrates the potential benefits, but also emphasizes the risks, of treating such patients with these therapies. In practice, the risk of developing SAEs, including severe complications or death, should be carefully balanced against the likelihood of a virological response and subsequent improvement of survival. Based on our results, three baseline parameters should be considered to guide treatment decisions at the individual level. They include the prior treatment response (triple therapy is not an optimal option for prior null responders with cirrhosis), the serum albumin level and the platelet count (treatment-experienced patients with compensated cirrhosis with a platelet count ≤100,000 /mm 3 and serum albumin <35 g/L should not be treated with a triple combination). Relapsers and partial responders to a prior course of Peg-IFN/RBV and/or patients with a favourable baseline laboratory parameter profile can be treated, because they may benefit from therapy, but they must be carefully

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  Overall, 54 patients (10.6%) experienced severe complications or death. Nearly one half of these severe complications occurred during the first 12 or 16 (in the case of lead-in) weeks, independently of treatment regimens (18/38 in the TVR cohort and 8/16 in the BOC cohort). Age per 10-year increase (OR= 1.61, 95% CI 1.13-2.30, p=0.0087), baseline serum albumin <35 g/L (OR=5.43, 95% CI: 2.72-10.83, p<0.0001) and baseline platelet count ≤100,000/mm 3 (OR=3.57, 95% CI: 1.81-7.02, p=0.0002) were independently associated with death or severe infection or hepatic decompensation and a non-significant trend was noted with baseline haemoglobin level ≤12 g/dL for women, ≤13 g/dL for men (OR=2.11, 95% CI: 0.96-4.63, p=0.0624). The probability of remaining free of severe complication or death is shown in the supplementary materials (Figures

  monitored. Recently, interferon-free regimens combining sofosbuvir, a nucleotide polymerase inhibitor + daclatasvir (NS5a inhibitor) ± RBV (32) or sofosbuvir + simeprevir, a second-wave protease inhibitor ± RBV (33) have yielded very promising results in genotype 1 naive or null responders without cirrhosis. These IFN-free regimens need to be evaluated in cirrhotic patients. Some patients from the CUPIC cohort who failed to respond to interferon-based triple therapy are currently being retreated with sofosbuvir + ledipasvir (NS5a inhibitor) ± ribavirin in a prospective randomized trial (NCT01965535).

Figure legends Figure 1A :

 legends1A Figure legends

Figure 1B :

 1B Figure 1B: SVR12 with TVR according to the HCV subtype and prior response to IFN/RBV

  in 64 patients, **313 SAEs in 94 patients

Table 1 : Baseline demographics and disease characteristics

 1

	Characteristics	TVR (n = 299)	BOC (n = 212)
	Mean age (range), years	57.1 (27-83)	56.8 (34-81)
	Male gender, n (%)	202 (67.6)	144 (67.9)
	Mean body mass index (standard deviation) kg/m 2	26.5 (4.2)	26.3 (4.3)
	Diabetes, n (%)	33 (11.0)	18 (8.5)
	History of ascites or variceal bleeding, n (%)	5 (1.7)	6 (2.8)
	Treatment history, n (%)
	-Prior relapse	117 (39.1)	92 (43.4)
	-Prior partial response	135 (45.1)	94 (44.3)
	-Prior null response	31 (10.4)	10 (4.7)
	-Breakthrough	7 (2.3)	10 (4.7)
	-Undetermined	9 (3.0)	6 (2.8)
	Mean haemoglobin level (range), g/dL	14.5 (9.0-19.7)	14.8 (9.1-18.4)
	Mean neutrophil count (range), 10 9 /mm 3	3.3 (0.8-8.5)	3.2 (0.5-8.5)
	Mean platelet count (range), /mm 3	151,000	144,000
		(18,000-604,000)	(33,900-346,000)
	Mean alanine aminotransferase (range), IU/L	101 (0.2 -456)	108 (5.0 -474)
	Mean prothrombin time ratio (range), (%)	86.5 (27-100)	87.1 (23-100)
	Mean total bilirubin (range), µmol/L	15.4 (4.0-73.5)	15.1 (3.4-78.0)
	Mean serum albumin (range), g/dL	40.0 (20.7-53.2)	40.4 (27.0-50.3)
	Child-Pugh score, n (%)
	-A	285 (95.3)	198 (93.4)
	-B	6 (2.0)	2 (0.9)
	-C	0	0

Creatinine clearance estimated using the Cockcroft-Gault formula, n (%)*** <60 mL/min 60-90 mL/min 90 mL/min 12 (4.2) 70 (24.4) 204 (71.4) 5 (2.7) 48 (25.7) 134 (71.6)

	* available in 276 patients for TVR and 184 patients for BOC
	** available in 298 patients for TVR and 207 patients for BOC
	***

available in 286 patients for TVR and 187 patients for BOCTable 2 : Baseline factors related to SVR12. Univariate and multivariate analysis

 2

			Univariate analysis		Multivariate analysis
		Odds	95% CI	p-value	Odds	95% CI	p-value
		ratio			ratio
	Prior treatment response
	Partial response	1			1
	Null response	0.265	0.107-0.655	0.0040	0.283	0.110-0.725	0.0086
	Relapse or breakthrough	2.874	1.964-4.206	<0.0001	2.956	1.967-4.442	<0.0001
	No lead-in phase	1.701	1.198-2.414	0.0030	1.784	1.198-2.657	0.0044
	TVR	1.431	1.004-2.039	0.0472
	Platelet count >100,000/mm 3	2.207	1.437-3.389	0.0003	2.148	1.339-3.448	0.0015
	Serum albumin ≥35g/L	2.718	1.543-4.791	0.0005
	No REALIZE exclusion criteria	1.661	1.139-2.422	0.0084
	No RESPOND-2 exclusion criteria	1.981	1.389-2.825	0.0002
	HCV subtype
	1a	1
	1b	2.713	1.844-3.993	<0.0001	2.499	1.624-3.846	<0.0001
	Others	1.808	0.971-3.368	0.0619
	Gender, age, body weight, body mass index, diabetes, alcohol intake, cannabis smoking, haemoglobin,

creatinine, alanine aminotransferase, HCV RNA, total bilirubin, prothrombin time, Child-Pugh score (A vs B), MELD score, and presence of oesophageal varices were tested in univariate analysis and were not significant

Table 3 : Safety profile of the triple therapy including TVR (n = 299)

 3

	Events

Table 4 : Safety profile of the triple therapy including BOC (n = 212) Events Week 16 Week 60

 4

	Patients with serious adverse event, n (%)	64 (30.2)*	94 (44.3)**
	Premature treatment discontinuation (any reason), n (%)	33 (15.6)	99 (45.7)
	Premature treatment discontinuation due to SAEs, n (%)	10 (4.7)	36 (17)
	Discontinuation of BOC alone	0 (0)	2 (0.9)
	Discontinuation of RBV alone	0 (0)	3 (1.4)
	RBV dose reduction	11 (5.2)	27 (12.7)
	Peg-IFN dose reduction	3 (1.4)	14 (6.6)
	Death, n (%)	1 (0.5)	3 (1.4)
	Grade 3/4 infection, n (%)	4 (1.9)	8 (3.8)
	Grade 3/4 hepatic decompensation, n (%)	6 (2.8)	9 (4.2)
	Grade 3/4 asthenia, n (%)	10

Table 5 : Risk of death or severe complications and SVR12 according to serum albumin level and platelet count*

 5 Baseline albumin and platelet count were available in 448 patients (missing data in 63 patients for albumin and/or platelet count). 10 deaths were reported and analyzed in these 448 patients.

	Factors	Platelet count	Platelet count
		>100,000 /mm 3	≤100,000 /mm 3
	Serum albumin 35 g/L
	Patients, n (%)	306 (68.3%)	74 (16.5%)
	Patients with severe complications or
	death, n (%)	19 (6.2%)	9 (12.2%)
	Patients with SVR12, n (%)	168 (54.9%)	27 (36.5%)
	Serum albumin <35 g/L
	Patients, n (%)	31 (6.9%)	37 (8.3%)
	Patients with severe complications or
	death, n (%)	5 (16.1%)	19 (51.4%)
	Patients with SVR12, n (%)	9 (29.0%)	10 (27.0%)

*

Acknowledgments

This study was sponsored and funded by The National Agency for Research on AIDS and Viral Hepatitis (ANRS). The ANRS C020 CUPIC cohort study was conducted with the support and participation of the Association Française pour l'Etude du Foie (AFEF).

and Merck/

each tested covariate, a univariate model was estimated. Covariates with p values <.05 in likelihood ratio testing in univariate analysis were included in a multivariate model, and selection of independent covariates was based on a backward elimination procedure, retaining covariates with p values <.05.

All statistical computations were performed using SAS software version 9.3 (SAS Institute Inc, Cary, North Carolina).

All authors had access to the study data and had reviewed and approved the final manuscript.