Younossi Z Et Al

Maria Patrizia Carrieri

Camelia Protopopescu
email: camelia.protopopescu@inserm.fr

Zobair Younossi

Antoine Vilotitch

Hélène Fontaine

Ventzislava Petrov-Sanchez

Fabienne Marcellin

Fabrice Carrat

Christophe Hézode

Marc Bourlière

Health-Related Quality of Life in Chronic HCV-Infected Patients Switching to Pegylated-Interferon-Free Regimens (ANRS CO20 CUPIC Cohort Study and SIRIUS Trial)

Objective We aimed to compare health-related quality of life (HRQL) during and after HCV treatment in patients receiving pegylated-interferon (PEG-IFN)-containing therapy (including boceprevir or telaprevir -ANRS CO20 CUPIC cohort) who subsequently switched to PEG-IFNfree regimens (sofosbuvir + ledipasvir with or without ribavirin (RBV) -SIRIUS trial).

Methods Two analyses were performed. The first compared physical (PCS) and mental (MCS) HRQL (MOS SF-12) scores during treatment between CUPIC and SIRIUS. The second compared PCS and MCS scores after treatment end between CUPIC and SIRIUS. The analyses used linear regression mixed models adjusted for pre-treatment HRQL scores, gender and age at each visit.

Results Among patients enrolled successively in both studies, 43 (corresponding to 212 HRQL assessments) and 43 (82 HRQL assessments) were eligible for the "during" and "post" treatment analyses, respectively. In the "during-treatment" analysis, we found both significantly higher PCS and MCS values during PEG-IFN-free treatment than for PEG-IFN-containing treatment. In the "post-treatment" analysis, results showed significantly higher MCS values after PEG-IFN-free treatment than after PEG-IFN-containing treatment. No significant difference was found for PCS in "post-treatment analysis".

Conclusions These results highlight an improvement in both physical and mental HRQL during HCV treatment, but no major improvement in physical HRQL after treatment end, when comparing PEG-IFN-free regimens with PEG-IFN-containing regimens. This suggests that in the PEG-IFN-free regimens era, screening and comprehensive care of comorbidities and residual somatic symptoms during treatment, and especially after HCV clearance, are still needed to improve patient outcomes.

Key Points for Decision Makers

This study examines health-related quality of life (HRQL) in HCV-infected patients switching, after treatment failure, from a pegylated-interferon (PEG-IFN)-based HCV treatment (ANRS CO20 CUPIC cohort) to a PEG-IFN-free treatment (SIRIUS trial).

The results highlight a relative improvement in both physical and mental HRQL during HCV treatment, but no major improvement in physical HRQL after treatment end, when comparing PEG-IFN-free regimens with PEG-IFN-containing regimens. This suggests that in the PEG-IFNfree regimens era, screening and comprehensive care of comorbidities and residual somatic symptoms during treatment, and especially after HCV clearance, are still needed to improve patient outcomes.

Introduction

For several decades HCV chronic infection was regarded as an incurable disease, leading ineluctably to the death of a great many people from liver cirrhosis or liver cancer sequelae. Pegylated-interferon (PEG-IFN) plus ribavirin (RBV) was the first regimen to result in promising HCV clearance rates, although its effectiveness was strongly linked to HCV genotype and continuity of treatment (persistence). In 1999, the European Consensus Conference on Hepatitis C established that the gold standard for treatment of chronic hepatitis C was a combination of PEG-IFN and RBV [START_REF] Palumbo | PEG-interferon in acute and chronic hepatitis C: a review[END_REF]. However, increasing access to treatment and ensuring adherence to the treatment regimen were a challenge with this combination. The burden of anemia and/or influenza-like symptoms, as well as psychiatric side-effects such as depression, fatigue and anger [START_REF] Marcellin | Adding HCV treatment to HIV treatment in HIV-HCV coinfected patients: the impact on the different dimensions of fatigue and self-reported side effects[END_REF][START_REF] Marcellin | Using patientreported outcomes to improve the management of co-infection with HIV and HCV: the ANRS CO13 HEPAVIH cohort[END_REF], represented a major barrier to initiation and continuity of treatment [START_REF] Bonner | Self-efficacy and adherence to antiviral treatment for chronic hepatitis C[END_REF][START_REF] Hauber | Patient preferences and assessment of likely adherence to hepatitis C virus treatment[END_REF][START_REF] Broers | Barriers to interferon-alpha therapy are higher in intravenous drug users than in other patients with acute hepatitis C[END_REF]. HCV-related fatigue and treatment-related side effects negatively affected health-related quality of life (HRQL) and were identified as predictive factors of treatment discontinuation [START_REF] Guadagnino | Does depression symptomatology affect medication compliance during the first weeks of anti-HCV therapy in intravenous drug users? Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the[END_REF].

The arrival of the first protease inhibitors -boceprevir and telaprevir -in 2012, which were administered in combination with PEG-IFN and RBV, improved rates of sustained virological response (SVR) in genotype 1 subjects [START_REF] Hezode | 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], but increased toxicity (cytopenia, anemia, asthenia, myalgia, skin rash) [START_REF] Chopra | How to optimize HCV therapy in genotype 1 patients: management of side-effects[END_REF] resulting in treatment discontinuation. This highlighted the need for appropriate somatic and psychiatric clinical management. These regimens were also associated with significant impairment of HRQL [10,[START_REF] Vera-Llonch | Health-related quality of life in genotype 1 treatment-naive chronic hepatitis C patients receiving telaprevir combination treatment in the ADVANCE study[END_REF].

One of the new Direct-Acting Antiviral Agents (DAA) against HCV is sofosbuvir (SOF), a nucleotide analog inhibitor of the NS5B polymerase enzyme, approved in June 2013 by the US Food & Drug Administration (FDA) [START_REF]Food and Drug Administration Approves Gilead's Sovaldi™ (Sofosbuvir) for the Treatment of Chronic Hepatitis C[END_REF] and in January 2014 by the European MEdicines Agency (EMEA) [START_REF]European Commission Grants Marketing Authorization for Gilead's Sovaldi® (Sofosbuvir) for the Treatment of Chronic Hepatitis C Infection[END_REF] for different treatment combinations. It may be used with PEG-IFN and RBV for 12 weeks or with RBV only for 12 or 24 weeks, according to the HCV genotype. SOF + RBV was the first interferon-free HCV treatment regimen available, and is also recommended for patients with severe fibrosis. Carrieri MP., Protopopescu C., Younossi Z. et al SOF is characterized by high efficacy and tolerance, which result in high response rates (depending on HCV genotype, extent of liver damage and previous treatment history) and few side-effects, especially when not combined with PEG-IFN. HRQL data for SOF regimens with and without PEG-IFN and/or RBV have recently been published. These data show that PEG-IFNcontaining SOF regimens significantly impaired patients' HRQL (as captured by the Medical Outcomes Study 36-item Short-Form questionnaire (MOS SF-36)) [START_REF] Younossi | Minimal impact of sofosbuvir and ribavirin on health related quality of life in chronic hepatitis C (CH-C)[END_REF]. Moreover, the addition of SOF to the treatment regimen did not add to the HRQL burden of PEG-IFN + RBV. In contrast, PEG-IFN-free regimens with SOF + RBV resulted in a slight impairment of HRQL, which was not related to treatment duration [START_REF] Younossi | Minimal impact of sofosbuvir and ribavirin on health related quality of life in chronic hepatitis C (CH-C)[END_REF]. It has also been shown that other patient-reported outcomes, including work productivity, were more negatively affected in patients receiving SOF with PEG-IFN than in those on SOF regimens without PEG-IFN [START_REF] Younossi | Effects of sofosbuvir-based treatment, with and without interferon, on outcome and productivity of patients with chronic hepatitis C. Clinical gastroenterology and hepatology : the official clinical practice[END_REF].

The objective of this study was to compare, for the first time, HRQL in patients receiving boceprevir or telaprevir triple combination PEG-IFN-containing therapy (ANRS CO20 CUPIC cohort study [START_REF] Hezode | 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]) who subsequently switched to SOF combined with a NS5A inhibitor (ledipasvir (LDV)) PEG-IFN-free therapy with or without RBV (SIRIUS trial [START_REF] Bourliere | Ledipasvir-sofosbuvir with or without ribavirin to treat patients with HCV genotype 1 infection and cirrhosis non-responsive to previous protease-inhibitor therapy: a randomised, doubleblind, phase 2 trial (SIRIUS)[END_REF]). The comparison focuses specifically on patient HRQL during HCV treatment in a first analysis, and after the end of treatment in a second analysis.

Methods

Study Design

Analyses are based on data collected from HCV-chronic patients who consecutively participated for a new drug. The study prospectively followed 674 patients who received triple therapy with PEG-IFN, RBV and either boceprevir or telaprevir for 48 weeks, with approval from the French Health authorities [START_REF] Hezode | 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]. Drug safety profiles and virological response to combined treatment were assessed [START_REF] Hezode | 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]. SIRIUS (ClinicalTrials.gov identifier: GS-US-337-0121) is a phase II multicenter, randomized, double-blind trial [START_REF] Bourliere | Ledipasvir-sofosbuvir with or without ribavirin to treat patients with HCV genotype 1 infection and cirrhosis non-responsive to previous protease-inhibitor therapy: a randomised, doubleblind, phase 2 trial (SIRIUS)[END_REF], which evaluated the efficacy and safety of interferon-free SOF/LDV treatment with or without RBV, in treatment-experienced patients with compensated cirrhosis.

Eligible patients were genotype 1 individuals with prior virological failure after both PEG-IFN + RBV regimen and triple combination therapy (containing either telaprevir or boceprevir). The 154 patients enrolled in SIRIUS were randomized into the following two arms: 24-week treatment with SOF/LDV as a fixed-dose combination (FDC) with placebo RBV (arm 1: "FDC + Placebo RBV", n=78 patients), and 12-week treatment with placebo, followed by 12-week treatment with FDC and RBV (arm 2: "Placebo -> FDC + RBV", n=76 patients).

Among the 154 patients enrolled in SIRIUS between 21st October and 28th November 2013, 47 were identified as having previously participated in the CUPIC cohort (CUPIC enrolment date between March 2011 and April 2012). According to SIRIUS eligibility criteria, none of these 47 patients had achieved sustained virological response (SVR) after treatment from CUPIC, and none had either hepatocellular carcinoma or decompensated hepatic disease. All these patients achieved SVR by the end of the treatment in SIRIUS trial. The analyses of this study will use data from these 47 patients.

Assessment of HRQL

In the CUPIC study, patient HRQL was assessed using the Medical Outcomes Study 12-item Short-Form questionnaire (MOS SF-12), a short version of the MOS SF-36 questionnaire [START_REF] Ware | Interpreting SF-36 summary health measures: a response[END_REF], which has been widely used for studies on HCV-infected patients in France and other European countries [START_REF] Dacosta Dibonaventura | The burden of viral hepatitis C in Europe: a propensity analysis of patient outcomes[END_REF]19]. Patients answered the SF-12 at several time points during follow-up, as Carrieri MP., Protopopescu C., Younossi Z. et al follows: baseline (Week 0), during treatment (Weeks 4, 8, 12, 24, 36, and 48), and after treatment (Week 72, i.e., 24 weeks after treatment end).

A similar self-administered questionnaire including the MOS SF-36 questionnaire [START_REF] Ware | Interpreting SF-36 summary health measures: a response[END_REF] was proposed to participants in the SIRIUS trial during and after the treatment period: at the baseline visit (Week 0), during treatment (Weeks 4, 12, 16, 24), and after the end of treatment (Weeks 28, 36, 48, i.e. respectively 4, 12 and 24 weeks after treatment end) [START_REF] Younossi | The impact of ledipasvir/sofosbuvir on patient-reported outcomes in cirrhotic patients with chronic hepatitis C: the SIRIUS study[END_REF].

Two HRQL aggregate scores -the physical component summary (PCS) for physical HRQL and the mental component summary (MCS) for mental HRQL -were calculated in both studies using the 12 items common to the SF-12 and the SF-36 questionnaires. These summary scores were calculated using the U.S. population norms to the mean of 50 and a standard deviation of 10, over a range of 0 to 100 points, with higher values denoting better HRQL.

Statistical Analyses

Given the repeated-measure design of the study and the presence of two arms in the SIRIUS trial with different treatment durations and follow-up schedules, for the purpose of standardization, analyses were restricted to the data collected at the following selected visits during CUPIC and SIRIUS follow-ups. Accordingly, we performed the following two analyses:

During-treatment analysis: This analysis aimed at comparing PCS and MCS during treatment in SIRIUS (using data at Weeks 4, 12, 16, 24) versus CUPIC (using data at Weeks 4, 8, 12, 24, 36, and 48), after adjustment for gender, age at each visit and pre-treatment HRQL values (baseline data). Patients with available HRQL scores at least once during treatment and at baseline, in at least one of the two studies, were included in this analysis. The baseline time point was set at Week 0. However for SIRIUS-arm 2 patients (who had taken the Placebo during the first 12 weeks), the baseline was set at Week 12 and only subsequent visits (at Weeks 16 and 24) were included in the "during-treatment" analysis. In addition, in order to maximize the sample size, we performed a last observation carried forward imputation for SIRIUS-arm 2 patients, using the score values at Week 0 as baseline values when the values at Week 12 were missing (this was the Carrieri MP., Protopopescu C., Younossi Z. et al case for 2 patients). A linear mixed-effects regression model -adjusted for baseline PCS and MCS values in CUPIC and SIRIUS -was used to verify whether PCS and MCS changed significantly during the PEG-IFN-free regimens (SIRIUS) with respect to the boceprevir/telaprevir PEG-IFNcontaining regimens (CUPIC).

Post-treatment analysis: This second analysis aimed at comparing PCS and MCS after treatment end in SIRIUS (data at Weeks 36 and 48) and CUPIC (data at Week 72), after adjustment for gender, age at each visit and pre-treatment HRQL values (baseline data). To this end, we employed the same method used for the "during-treatment" comparison. Patients with available HRQL scores at least once after end of treatment and at baseline, in at least one of the two studies (CUPIC and SIRIUS), were included in this analysis. Nevertheless, the visit at 28 weeks in SIRIUS (i.e. 4 weeks after treatment end) was not included in this analysis, to keep a reasonable minimum delay of at least 12 weeks after the end of treatment.

In all analyses the computation of p-values and confidence intervals was based on the robust sandwich method.

The descriptive statistics (mean ± standard deviation, median and interquartile range (IQR)) of PCS and MCS scores for each CUPIC and SIRIUS visit are reported in Table 1. The scores' distributions for both studies and for each visit are also described using boxplots in Fig. 1.

Stata software release 12.1 was used for all statistical analyses [START_REF]Stata Statistical Software[END_REF].

Results

Among the 47 patients enrolled in both studies (SIRIUS trial and CUPIC cohort), 42 were present in the CUPIC HRQL database (the remaining 5 patients did not respond to the HRQL questionnaire during the CUPIC follow-up). Overall, 43 patients were eligible for the "duringtreatment" analysis, having available HRQL scores at least once during treatment and at baseline, in at least one of the two studies, for a total of 212 HRQL assessments (109 visits from CUPIC and 103 visits from SIRIUS). Forty-three patients were eligible for "post-treatment" analysis, having HRQL scores available at least once after end of treatment and at baseline, in at least one of the two studies, for a total of 82 HRQL assessments (7 visits from CUPIC and 75 visits from SIRIUS, see flow chart in Fig. 2).

The "during-treatment" study group of 43 patients mainly included men (n=35 (81.4%)), median

[IQR] age at baseline in CUPIC was 56 [50-63] years. Among these 43 patients, 33 had HRQL data treatment and at baseline in CUPIC, and 41 had HRQL data during treatment and at baseline in Sirius (18 in "FDC + Placebo RBV" arm and 23 in "Placebo -> FDC + RBV" arm) (see Fig. 2).

The "post-treatment" study group of 43 patients had similar characteristics (in fact, 41 patients were common to both the "during-treatment" and "post-treatment" study groups). It included 36 men (83.7%), with a median [IQR] age at baseline in CUPIC of 56 [51-64] years.

In the "during-treatment" analysis (Table 2, In the "post-treatment" analysis (Table 2, model B), significantly higher MCS values were found after PEG-IFN-free treatment (SIRIUS), with an average increase of 3.95 points (95% CI: [0.38; This study has two main results. First, compared with PEG-IFN-containing regimens, we observed a significant improvement in both the physical and mental dimensions of HRQL during PEG-IFN-free treatment. Second, in the post-treatment analysis, a significant improvement was observed in the mental dimension of HRQL after completing PEG-IFN-free treatments compared with PEG-IFN-containing treatments. By contrast, no significant improvement was found for post-treatment values of physical HRQL.

The improvement observed during treatment in both physical and mental HRQL when moving from telaprevir/boceprevir-based triple combination therapy to the PEG-IFN-free SOF-based treatment is consistent with previous results [START_REF] Younossi | The impact of ledipasvir/sofosbuvir on patient-reported outcomes in cirrhotic patients with chronic hepatitis C: the SIRIUS study[END_REF] and may be due to the benefits of PEG-IFN-free treatment in terms of increased efficacy and fewer treatment-related side-effects. Moreover, the former can be considered the "worst case scenario" in terms of toxicity burden, while the latter has already proven itself to be quite well tolerated for most patients.

Results from the "post-treatment" analysis showed there was no significant difference between physical HRQL values after PEG-IFN-containing and PEG-IFN-free treatment completion. This may be attributable to fatigue, which is known to persist after completing PEG-IFN-containing regimens [START_REF] Younossi | The effects of HCV infection and management on healthrelated quality of life[END_REF], and which may also continue for a substantial period (in our case 12 to 24 weeks) after completing PEG-IFN-free regimens, despite HCV clearance. In fact, recent data show that fatigue may decrease over time after post HCV clearance [START_REF] Gerber | Effects of Viral Eradication With Ledipasvir and Sofosbuvir, With or Without Ribavirin, on Measures of Fatigue in Patients With Chronic Hepatitis C Virus Infection[END_REF], which would suggest that even Carrieri MP., Protopopescu C., Younossi Z. et al with the advent of novel powerful and less toxic regimens, the management of physical health disturbances cannot be neglected, and needs to be incorporated into standard HCV care.

The significant improvement found in the mental HRQL dimension after the end of PEG-IFNfree regimens suggests that HCV clearance may have important benefits for patients including decreased anxiety and a reduced impact of HCV-related psychiatric symptoms on daily life. This improvement found here is consistent with previous research in HIV-HCV co-infected patients which highlighted that the low rates of suicide ideation exhibited by HCV-clearers were similar to those in people who had never been HCV co-infected [START_REF] Fressard | Suicide risk in people living with HIV: the possible role of HCV co-infection and experience of discrimination[END_REF]. This is an additional argument for promoting access to better tolerated treatment regimens for HCV-infected patients.

In addition, given that the minimal clinically important difference for the two summary scores (PCS and MCS) is generally in the range of 3 to 5 points [START_REF] Younossi | Systematic review: patient-reported outcomes in chronic hepatitis C-the impact of liver disease and new treatment regimens[END_REF][START_REF] Hays | The RAND-36 measure of health-related quality of life[END_REF][START_REF] Spiegel | Impact of hepatitis C on health related quality of life: a systematic review and quantitative assessment[END_REF], we can conclude that the statistically significant improvements observed in this study can also be interpreted as clinically important, except for the mental HRQL dimension during treatment. For the latter, the slight improvement of 2.49 points, albeit statistically significant, was not clinically significant. We suppose that depressive and anxiety symptoms (not measured in this study but known to be highly correlated with mental HRQL) may persist during any HCV treatment because of patient expectations about treatment outcomes, and also because of the burden of HCV on mental health [START_REF] Fletcher | Hepatitis C virus and the brain[END_REF].

Limitations

The main limitation of this study is the use of a generic scale for the assessment of HRQL, which is perhaps unable to capture specific dimensions of improvement (or absence of improvement) in chronically-infected HCV patients' quality of life. Although the sample size is rather limited and this may hide potential differences, we used robust estimates to compensate for this reduced power. Carrieri MP., Protopopescu C., Younossi Z. et al Moreover, the lack of comparable scales of self-reported symptoms and fatigue in both studies did not enable us to document the residual burden of some symptoms during and after PEG-IFNcontaining and PEG-IFN-free regimens.

Finally, in this study we were not able to compare the specific dimensions (subdomains) of the SF-12 scale which could have captured specific aspects like fatigue or emotional problems. This was due to the fact that the HRQL questionnaire in CUPIC was based on SF-12 version 1, while the HRQL questionnaire in SIRIUS was based on SF-36 version 2. Consequently, although the PCS and MCS summary scores were comparable between versions 1 and 2 of the reduced SF-12 scale, this was not the case for the SF-12 scale's specific dimensions, which had different scoring algorithms in the two versions.

Conclusion

To conclude, our results highlight an improvement in both physical and mental HRQL during HCV treatment, but no major improvement in physical HRQL after treatment end, when comparing PEG-IFN-free regimens with PEG-IFN-containing regimens. Accordingly, these results may have important implications for clinical management of HCV chronically-infected patients. They suggest that in the PEG-IFN-free regimen era, screening and comprehensive care of comorbidities and residual somatic symptoms during and especially after HCV clearance, are still needed in order to improve patient outcomes.

Insert

  Carrieri MP., Protopopescu C., Younossi Z. et al -Yannicq Bacq, MD, Service d'Hépatologie et Gastroentérologie, Centre Hospitalier Universitaire Trousseau, Tours, France -Paul Calès, MD, Service d'Hépatologie et Gastroentérologie, Centre Hospitalier Universitaire, Angers, France -Patrick Delasalle, MD, Service d'Hépatologie et Gastroentérologie, Clinique du Palais, Grasse, France -Denis Ouzan, MD, Service d'Hépatologie et Gastroentérologie, Institut Arnaud Tzanck, Saint-Laurent du Var, France -Jean-Baptiste Nousbaum, MD, Service d'Hépatologie et Gastroentérologie, Centre Hospitalier Universitaire de la Cavale Blanche, Brest, France -Christine Sylvain, MD, Service d'Hépatologie et Gastroentérologie, Centre Hospitalier Universitaire, Poitiers, France -Didier Ribard, MD, Service d'Hépatologie et Gastroentérologie, Centre Hospitalier Universitaire Caremeau, Nîmes, France -Gilles Gatineau-Sailliant, MD, Centre Hospitalier, Meaux, France -Stéphanie de Montigny-Lenhardt, MD, Centre Hospitalier Edmond Garcin, Aubagne, France -Philippe Renard, MD, Centre Hospitalier Victor Dupouy, Argenteuil, France -Christophe Pilette, MD, Centre Hospitalier, Le Mans, France -Jacques Denis, MD, Centre Hospitalier Sud Francilien, Corbeil-Essonnes, France -Caroline Lascoux-Combe, MD, Service de Maladies Infectieuses, Hôpital Saint-Louis, AP-HP, Paris, France -Laurent Abel, MD, Unité de génétique, INSERM U550, Paris, France -Matthew Albert, PhD, Unité d'Immunologie, Institut Pasteur, Paris, France -Olivier Chazouillères, MD, Service d'Hépatologie, Hôpital Saint-Antoine, AP-HP, Paris, France -Jean Dubuisson, PhD, Unité de Virologie, INSERM U1019, CNRS UMR8204, Lille, France -Francesco Negro, MD, Hôpital Cantonal, Genève, Suisse -Georges-Philippe Pageaux, MD, Hôpital Saint Eloi, Montpellier, France Carrieri MP., Protopopescu C., Younossi Z. et al -Valérie Paradis, MD, Service d'anatomopathologie, Hôpital Beaujon, AP-HP, Clichy, France -Bruno Spire, PhD, Santé Publique, Sciences Humaines et Sociales, INSERM, Marseille, France -Anne-Marie Taburet, MD, Pharmacologie, Hôpital Bicêtre, AP-HP, Le Kremlin-Bicêtre, France -Jean-Claude Trinchet, MD, Service d'Hépatologie, Hôpital Jean Verdier, AP-HP, Bondy, France -Yazdan Yazdanpanah, MD, Economie de la Santé, Hôpital Bichat, AP-HP, Paris, France -Cécilie Dufour, INSERM UMR-S 707, Université Pierre et Marie Curie Paris 6, Paris, France -Céline Fréhaut, INSERM UMR-S 707, Université Pierre et Marie Curie Paris 6, Paris, France -Marion Pirot, INSERM UMR-S 707, Université Pierre et Marie Curie Paris 6, Paris, France -Aurélie Lesel, INSERM UMR-S 707, Université Pierre et Marie Curie Paris 6, Paris, France -Nathalie Zahraa, INSERM UMR-S 707, Université Pierre et Marie Curie Paris 6, Paris, France -Frédéric Chau, INSERM UMR-S 707, Université Pierre et Marie Curie Paris 6, Paris, France Running Heading Health-Related Quality of Life in HCV Patients Switching to Pegylated-Interferon-Free Regimens Abstract word count: 242 (max 250) Text word count: 3105 (max 4000) Running heading character count: 94 (max 100)

  in the following two studies conducted in France: the ANRS CO20 CUPIC cohort (in 2011-2012) and the SIRIUS trial (in 2013-2014). ANRS CO20 CUPIC (ClinicalTrials.gov number NCT01514890) was a multicenter cohort study which started in February 2011. It included HCV genotype 1 patients with compensated cirrhosis who had failed to eradicate HCV after completing a previous standard PEG-IFN/RBV therapy, and who were subsequently provided with protease inhibitor-based HCV therapy in the context Carrieri MP., Protopopescu C., Younossi Z. et al of the French Early Access Program and the cohort's Temporary Authorisation for Use (ATU)

  model A), results showed significantly higher values for both PCS and MCS scores during PEG-IFN-free treatment (SIRIUS) than with PEG-IFNcontaining treatment combined with telaprevir or boceprevir (CUPIC), after adjustment for baseline score values (before treatment), gender and age at each visit. The average increase in HRQL values during the follow-up of SIRIUS versus CUPIC -estimated by the coefficient in the multivariate linear regression mixed model -was 4.57 points (95% confidence interval (CI): [2.44; 6.71], p-value<0.0001) for the PCS score and 2.49 points (95% CI: [0.28; 4.69], p=0.027) for the MCS score.

7 .

 7 52], p-value=0.030) compared with after PEG-IFN-containing treatment (CUPIC), after adjustment for baseline PCS values, gender and age at each visit. However, for PCS score, there was a trend towards better HRQL when comparing PCS values after PEG-IFN-free treatment versus after PEG-IFN-containing treatment, but this increase of 2.07 points (95% CI: [-4.69; 8.84], p-value=0.548) was not statistically significant. 4 Discussion Carrieri MP., Protopopescu C., Younossi Z. et al To our knowledge, this is the first study to compare changes in HRQL in the same group of chronic HCV-infected patients switching from a PEG-IFN-containing regimen (including telaprevir or boceprevir) to a PEG-IFN-free regimen, while taking into account within-subject variability. The repeated-measure design of the study allowed us to control for pre-treatment values of HRQL while comparing HRQL values assessed during treatment and in post-treatment comparison.

Fig. 1 Fig. 1 Fig. 2

 112 Figures Legend

4 )Fig. 1

 41 Fig. 1 Boxplots of PCS and MCS scores in CUPIC and SIRIUS, during and post treatment comparisons

Table 1 .

 1 Descriptive statistics of PCS and MCS scores in CUPIC and SIRIUS, for the during-and post-treatment analyses Carrieri MP., Protopopescu C., Younossi Z. et al

			CUPIC		FDC + Placebo RBV		Placebo->FDC + RBV
			(PEG-IFN regimens)		(SIRIUS arm 1)		(SIRIUS arm 2)
		n	mean ± SD	n	mean ± SD	n	mean ± SD
			median (IQR)		median (IQR)		median (IQR)
	PCS score
	Baseline §	33	43.4 ± 6.6	19	46.7 ± 6.3	24	47.1 ± 7.7
			43.2 (38.7-49.5)		46.2 (42.6-51.0)		48.2 (40.1-54.0)
	During-treatment
	Week 4	30	41.0 ± 5.8	14	45.5 ± 4.6
			40.8 (38.0-45.9)		46.0 (41.6-49.4)
	Week 8	24	43.2 ± 6.0
			43.0 (39.8-47.5)
	Week 12	24	40.2 ± 5.5	17	46.6 ± 7.7
			41.2 (36.9-43.5)		44.6 (39.5-54.0)
	Week 16			16	46.8 ± 7.3	21	47.2 ± 7.6
					45.8 (41.5-53.8)		48.3 (44.6-52.1)
	Week 24	14	37.8 ± 6.6	17	45.8 ± 7.7	18	47.0 ± 6.9
			39.1 (34.5-43.8)		46.4 (42.0-50.2)		47.9 (43.3-52.7)
	Week 36	9	41.4 ± 6.2
			42.0 (36.2-44.9)
	Week 48	8	41.6 ± 3.6
			42.1 (39.9-44.3)
	Post-treatment
	Week 36			18	45.7 ± 8.4	19	46.0 ± 7.7
					44.0 (38.6-53.4)		46.1 (39.3-53.4)
	Week 48			18	47.9 ± 7.5	20	51.2 ± 5.2
					49.2 (43.9-54.8)		51.9 (49.0-55.0)
	Week 72	7	42.9 ± 7.3
			42.8 (36.7-50.4)
	MCS score
	Baseline §	33	42.3 ± 5.8	19	42.4 ± 10.1	24	40.8 ± 12.2
			41.2 (38.6-45.4)		44.0 (34.1-49.3)		39.7 (29.8-51.9)
	During-treatment

Acknowledgements

We thank all the members of the CUPIC Study Group*. We especially thank all the patients who agreed to participate in the two studies and who completed the self-administered questionnaires.

We thank Bérengère Davin (PhD, Health Economist, ORS PACA, Marseilles, France) for suggestions about data analyses and interpretation of the results. Finally, we thank Jude Sweeney (Milan, Italy) for the English revision and editing of our manuscript.

Funding

The ANRS CO20 CUPIC cohort study was sponsored and funded by The National Agency for Research on AIDS and Viral Hepatitis (ANRS). The ANRS CO20 CUPIC cohort study was conducted with the support and participation of the Association Française pour l'Etude du Foie (AFEF). This work was supported by the French ANRS, with the participation of Gilead Sciences.

Author's contributions

Conflict of Interest

Zobair Younossi: research support and consultant for Gilead Sciences.

Hélène Fontaine: speaker fees from MSD, Janssen, Roche, BMS.

Christophe Hézode: consultancy fees from Abbott, MSD, Roche, Janssen, BMS, Gilead, and speaker fees from MSD, Janssen, Roche, BMS.

The other authors (Maria Patrizia Carrieri, Camelia Protopopescu, Antoine Vilotitch, Ventzislava Petrov-Sanchez, Fabienne Marcellin, Fabrice Carrat, and Marc Bourlière) declare that they have no conflict of interest.

Informed Consent

Written informed consent was obtained from all patients included in the study.

Ethical Approval

All procedures performed in this study were in accordance with the ethical standards of the


Léa Guyon

Jérémy Guez

Evelyne Heyer

Raphaëlle Chaix

Modeling the influence of human kinship systems on genetic diversity

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

Several studies have highlighted that kinship systems can leave genetic signatures on uniparental markers [START_REF] Chaix | From Social to Genetic Structures in Central Asia[END_REF][START_REF] Oota | Human mtDNA and Y-chromosome variation is correlated with matrilocal versus patrilocal residence[END_REF] and on X chromosomes [START_REF] Ségurel | Sex-Specific Genetic Structure and Social Organization in Central Asia: Insights from a Multi-Locus Study[END_REF], that are differentially transmitted according to the sex of individuals : By modeling human populations displaying different descent and post-marital residence rules, and computing several diversity estimators on different markers (Y, mt, X, autosomes), we will evaluate to which extent kinship rules impact genetic diversity in human populations, in order to trace back the history of kinship systems using genetic data. 2) Handle tree sequences and generate VCF files with tskit [START_REF] Kelleher | Efficient Coalescent Simulation and Genealogical Analysis for Large Sample Sizes[END_REF] and msprime [START_REF] Baumdicker | Efficient ancestry and mutation simulation with msprime 1.0[END_REF] 3) Compute diversity estimators Two different fission types [START_REF] Neel | Further studies on the Xavante Indians. X. Some hypotheses-generalizations resulting from these studies[END_REF][START_REF] Smouse | The impact of random and lineal fission on the genetic divergence of small human groups : a case study among the Yanomamai[END_REF] Diversity estimators

Nucleotide diversity π

Mean pairwise differences within a village [START_REF] Nei | Mathematical model for studying genetic variation in terms of restriction endonucleases[END_REF] • X / autosomes diversity ratio :

• mt / Y diversity ratio :

: mutation rate Genetic differenciation F ST between villages [START_REF] Weir | Estimating F-Statistics for the Analysis of Population Structure[END_REF] • X / autosomes diversity ratio :

• mt / Y diversity ratio :

Diversity ratios allow the differentiation between kinship rules (Fig 1,2). In particular, all ratios, except Qpi, enable to disciminate between patrilocal / patrilineal and matrilocal / matrilineal villages. However, only ratios using uniparental markers are able to make the difference between patrilocal villages with bilateral descent and patrilocal villages with patrilineal descent, as well as between random and lineal fission.

  are shaped by 3 major rules : -the descent rule -the alliance rule -the post-marital residence rule Post-marital residence rules Descent rules

  Definitions descent rules define to which kinship group an individual is affiliated in a population. unilineal descent is often associated with lineage exogamy, lineage fission and transmission of reproductive success. post-marital residence rules determine the place where a couple settles after marriage. Most modern human populations are patrilocal and patrilineal. But little is known about the history of human kinship systems and in particular, about when patrilocality and patrilineality became overrepresented in human populations. Cycles of migration / reproduction / fission / extinction for 100 generations fission extinction Lineages split when their size overpasses a fixed threshold and go extinct when their size is below a certain value. The fission is either random or lineal. Lineage exogamy : couples are formed so that the father and the mother are from different lineages Reproduction : monogamous couples reproduce within each village so that the size of villages stays constant Migration : villages exchange individuals at a rate m with a proportion of female m f Individuals display autosomes, X chromosomes, Y chromosomes and mtDNA Panmictic population of constant size 37

Fig 1 .Fig 2 .

 12 Fig 1 . Ratios of nucleotide diversity across generations from the introduction of kinship rules in villages

Perspectives : 1 -

 1 Identify other relevant estimators 2 -Test for the robustness of these estimators to low samples size and damaged pseudo-haploïd sequences (aDNA) 3 -Compute these estimators on ancient DNA data 4 -Compare the results with the expected ratios generated under different models 5 -Trace back the history of human kinship systems


Paul Hazemann

Jean-Marc Schweitzer

Dominique Decottignies

Sylvie Maury

Séverine Humbert

Yves Schuurman
email: yves.schuurman@ircelyon.univ-lyon1.fr

Impact of cobalt catalyst carburization on Fischer-Tropsch micro-kinetics

Keywords: Co/Siralox, micro-kinetic modeling, deactivation, deselectivation, carburization

Recent models of the Fischer-Tropsch synthesis are able to predict quite accurately the catalyst's initial activity and selectivity. However, these micro-kinetic models, rarely consider the performance loss with time on stream and in particular the heavy product selectivity loss. In this study, a deactivation model at the micro-kinetic scale is proposed to represent the effect of carburization on Fischer-Tropsch catalysts performances. Comparison of different mechanisms revealed that termination reactions were the most affected by cobalt carbide formation, before reactants adsorption or chain growth. Both activity and selectivity decline could be accurately described using linear and 2 nd order power laws expressions of active sites concentration and termination kinetic rate constants. The obtained model predicts a monotonous evolution of activity and selectivities from 10 to 80% carburization, above which an important increase of olefin selectivity is observed. The model did not indicate any change of the surface coverages after carburization.

Introduction

Fischer-Tropsch synthesis is a promising route for alternative fuel and chemicals production [START_REF] Martinelli | An overview of Fischer-Tropsch Synthesis: XtL processes, catalysts and reactors[END_REF] . Cobalt based catalysts have received particular attention because of their high selectivity toward heavy hydrocarbons [START_REF] Jahangiri | A review of advanced catalyst development for Fischer-Tropsch synthesis of hydrocarbons from biomass derived syn-gas[END_REF] , the most valuable products for fuel production. However, like in most chemical processes, the catalyst loses its activity and selectivity with time on stream 3- 5 and need to be eventually replaced. Several causes have already been identified to explain the deactivation phenomenon: carbon deposition [START_REF] Moodley | Carbon deposition as a deactivation mechanism of cobalt-based Fischer-Tropsch synthesis catalysts under realistic conditions[END_REF][START_REF] Weststrate | Fundamental issues on practical Fischer-Tropsch catalysts: How surface science can help[END_REF][START_REF] Keyvanloo | Kinetics of deactivation by carbon of a cobalt Fischer-Tropsch catalyst: Effects of CO and H2 partial pressures[END_REF][START_REF] Ahn | Catalyst deactivation by carbon formation during CO hydrogenation to hydrocarbons on mesoporous Co3O4[END_REF] sulfur poisoning [START_REF] Bartholomew | Hydrogen adsorption on supported cobalt, iron, and nickel[END_REF][START_REF] Leviness | Slurry hydrocarbon synthesis process with increased catalyst life[END_REF] carburization [START_REF] Ducreux | In Situ Characterisation of Cobalt Based Fischer-Tropsch Catalysts: A New Approach to the Active Phase[END_REF][START_REF] Claeys | In situ magnetometer study on the formation and stability of cobalt carbide in Fischer-Tropsch synthesis[END_REF][START_REF] Dai | Effect of Sodium on the Structure-Performance Relationship of Co/SiO2 for Fischer-Tropsch Synthesis[END_REF] water effects [START_REF] Hilmen | Selectivity and activity changes upon water addition during Fischer-Tropsch synthesis[END_REF][START_REF] Huber | Hydrothermal Stability of Co/SiO2 Fischer-Tropsch Synthesis Catalysts[END_REF][START_REF] Saib | Fundamental understanding of deactivation and regeneration of cobalt Fischer-Tropsch synthesis catalysts[END_REF][START_REF] Lancelot | Direct Evidence of Surface Oxidation of Cobalt Nanoparticles in Alumina-Supported Catalysts for Fischer-Tropsch Synthesis[END_REF][START_REF] Clarkson | Deactivation of alumina supported cobalt FT catalysts during testing in a Continuous-stirred tank reactor (CSTR)[END_REF] and surface reconstruction [START_REF] Saib | Fundamental understanding of deactivation and regeneration of cobalt Fischer-Tropsch synthesis catalysts[END_REF][START_REF] Somorjai | Adsorbate-induced restructuring of surfaces[END_REF] . The causes of the selectivity shift are however less documented, yet carburization and carbon deposition have recently been identified as a possible cause of deselectivation [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of carbon deposition[END_REF][START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] .

Numerous studies have been recently devoted to Fischer-Tropsch kinetics, and accurate models are now available in the literature [START_REF] Kwack | Development of a kinetic model of the Fischer-Tropsch synthesis reaction with a cobalt-based catalyst[END_REF][START_REF] Visconti | Detailed Kinetics of the Fischer-Tropsch Synthesis on Cobalt Catalysts Based on H-Assisted CO Activation[END_REF][START_REF] Todic | Kinetic Model of Fischer-Tropsch Synthesis in a Slurry Reactor on Co-Re/Al 2 O 3 Catalyst[END_REF][START_REF] Yang | Reaction mechanism of CO activation and methane formation on Co Fischer-Tropsch catalyst: A combined DFT, transient, and steady-state kinetic modeling[END_REF][START_REF] Azadi | Microkinetic Modeling of the Fischer-Tropsch Synthesis over Cobalt Catalysts[END_REF][START_REF] Zhou | Advanced fundamental modeling of the kinetics of Fischer-Tropsch synthesis[END_REF][START_REF] Pandey | Modeling Fischer-Tropsch kinetics and product distribution over a cobalt catalyst[END_REF] . Some of them take the deactivation phenomena into account in the proposed model, which is necessary to predict long term performances. Visconti et. al. [START_REF] Visconti | Fischer-Tropsch synthesis on sulphur poisoned Co/Al2O3 catalyst[END_REF] for instance introduced a dependency of the CO consumption rate to the sulfur content of the syngas, to represent the deactivation linked to sulfur poisoning. Ghasvareh et al. [START_REF] Ghasvareh | Effects of Co Particle Size on the Stability of Co/Al 2 O 3 and Re-Co/Al 2 O 3 Catalysts in a Slurry-Phase Fischer-Tropsch Reactor[END_REF] defined a corrective factor applied on the kinetic expression of CO consumption, which is associated with the carbon deposition rate. Sadeqzadeh et al. [START_REF] Sadeqzadeh | Deactivation of a Co/Al2O3 Fischer-Tropsch catalyst by water-induced sintering in slurry reactor: Modeling and experimental investigations[END_REF][START_REF] Sadeqzadeh | Mechanistic Modeling of Cobalt Based Catalyst Sintering in a Fixed Bed Reactor under Different Conditions of Fischer-Tropsch Synthesis[END_REF] modeled the sintering-induced deactivation using 2 nd order general power law expression, able to represent accurately the sintering rate dependency to the particles dispersion.

Most of these studies were, however, only implemented with macro-kinetic models for Fischer-Tropsch synthesis, i.e. using an empirical description of the CO consumption rate, the selectivity loss never being represented. To our knowledge, only Klinke and Broadbelt [START_REF] Klinke | Construction of a mechanistic model of Fischer-Tropsch synthesis on Ni(1 1 1) and Co(0 0 0 1) surfaces[END_REF] introduced an elementary reaction of coke generation into a micro-kinetic model, which is a first step toward deselectivation modeling. They, however, did not comment on the effect of this reaction on the overall kinetics.

The present study aims at modeling the activity and the selectivity loss in Fischer Tropsch synthesis caused by one of the most plausible deselectivation phenomenon, namely carburization.

To this aim, the cobalt catalyst was carburized in situ and the subsequent activity and selectivity loss was monitored as a function of time using a high-throughput testing facility [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] . This phenomenon has indeed been identified as a possible deselectivation mechanism [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] , before carbon deposition [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of carbon deposition[END_REF] or other deactivation mechanisms. The method presented in this study should, however, also be extended to the carbon deposition to propose a comprehensive deselectivation kinetic model. A micro-kinetic analysis will first be carried out to propose in fine a model able to represent the carbide-induced selectivity loss.

Material and methods

Reaction scheme and kinetics

The reaction scheme used in this study is the one published by Visconti et al. [START_REF] Visconti | Detailed Kinetics of the Fischer-Tropsch Synthesis on Cobalt Catalysts Based on H-Assisted CO Activation[END_REF] , but adapted to better represent the selectivity dependency to the CO conversion level measured experimentally.

The CH4 selectivity is generally assumed to decrease with increasing CO conversion, while the heavy compounds (C5+) selectivity increases. This behavior, also observed with the experimental data used in this study, has been explained by the increase of the water partial pressure with CO conversion [START_REF] Todic | Effect of process conditions on the product distribution of Fischer-Tropsch synthesis over a Re-promoted cobalt-alumina catalyst using a stirred tank slurry reactor[END_REF][START_REF] Zhou | Advanced fundamental modeling of the kinetics of Fischer-Tropsch synthesis[END_REF][START_REF] Frøseth | Steady state isotopic transient kinetic analysis (SSITKA) of CO hydrogenation on different Co catalysts[END_REF][START_REF] Botes | Influences of Water and Syngas Partial Pressure on the Kinetics of a Commercial Alumina-Supported Cobalt Fischer-Tropsch Catalyst[END_REF][START_REF] Lögdberg | On the selectivity of cobalt-based Fischer-Tropsch catalysts: Evidence for a common precursor for methane and long-chain hydrocarbons[END_REF] , which modifies the H2/CO ratio at the catalyst surface and thus the selectivity.

The water adsorption equilibrium was therefore added to the initial model [START_REF] Visconti | Detailed Kinetics of the Fischer-Tropsch Synthesis on Cobalt Catalysts Based on H-Assisted CO Activation[END_REF] , and the scheme presented in Table 1 was considered. The model considers only a single type of active site, a reduced cobalt surface atom, although models that distinguish active sites for methane formation and chain growth have been proposed [START_REF] Chen | Influence of Carbon Deposits on the Cobalt-Catalyzed Fischer-Tropsch Reaction: Evidence of a Two-Site Reaction Model[END_REF] .

Adsorption of H2 is assumed to be dissociative, while CO adsorption is considered molecular [START_REF] Reuel | The stoichiometries of H2 and CO adsorptions on cobalt: Effects of support and preparation[END_REF][START_REF] Bartholomew | Sulfur poisoning of cobalt and iron Fischer-Tropsch catalysts[END_REF] , H-assisted CO activation mechanism has been chosen since it gives, according to Visconti et al. [START_REF] Visconti | Detailed Kinetics of the Fischer-Tropsch Synthesis on Cobalt Catalysts Based on H-Assisted CO Activation[END_REF] , a better representation than the non-assisted one. Chain propagation is represented through the CH2 insertion mechanism, with a maximum carbon number 𝑛 equal to 50 (heavier hydrocarbons are assimilated to C50 hydrocarbons). Olefins termination reactions are reversible because of their tendency to re-adsorb [START_REF] Todic | Effect of process conditions on the product distribution of Fischer-Tropsch synthesis over a Re-promoted cobalt-alumina catalyst using a stirred tank slurry reactor[END_REF] . Methane and ethylene termination have their own kinetics, in order to represent the deviation of these products in the ASF distribution [START_REF] Van Der Laan | Kinetics and Selectivity of the Fischer-Tropsch Synthesis: A Literature Review[END_REF] . The chain growth and product terminations are considered independent of the chain length. The formation of CO2 is not accounted for in this model. CO2 selectivity under reaction conditions over a fresh catalyst amounted to 0.5% and increased to 0.6% over a carburized sample [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] . The rates of each elementary reaction of the scheme (Table 1) are described using the general expression:

𝑟 𝑘 • 𝑐  , (1)

Reactor modeling

The reactor model used to simulate the experimental data (cf section 2.4) is a plug-flow model, considered as isothermal and isobaric, and in which phase compositions are estimated by gas/liquid equilibrium calculations. The validity of these hypotheses has already been discussed elsewhere [START_REF] Hazemann | Kinetic data acquisition in high-throughput Fischer-Tropsch experimentation[END_REF] . The reactant and product flowrates along the reactor can thus be described according to the following material balances (supplementary information):

𝜕𝐹 𝜕𝑡 1 𝛽  , • 𝑟 • 𝑆 • 𝜌 • 𝜀 𝜕𝐹 𝜕𝑧 (2)
where corresponds to the accumulation term (molꞏs -1 ), to the convective term (molꞏm - 1 ꞏs -1 ), and ∑  , • 𝑟 • 𝑆 • 𝜌 • 𝜀 to the generation term.  , is the stoichiometric coefficient of the compound 𝑖 in the reaction 𝑗 of rate 𝑟 (mol•s -1 •gcat -1 ), 𝜌 and 𝜀 the density (gꞏm -3 ) and volume of catalyst per reactor volume respectively, and 𝑆 the reactor section (m 2 ).

𝛽 is expressed as:

𝛽 𝑆 𝐹 1 𝐾 , 𝜌 𝑀 • 1 𝛼 • 𝜀 𝑃 • 𝐾 , 𝑅 • 𝑇 • 𝛼 • 𝜀 (3)
𝐹 being the total molar flowrate (molꞏs -1 ), 𝛼 the molar gas fraction, 𝐾 , 𝐾 • the ratio of gas and liquid flowrates where 𝐾 , the partition coefficient, is estimated by Antoine's equation [START_REF] Boyer | Development of the Fischer-Tropsch Process: From the Reaction Concept to the Process Book[END_REF][START_REF] Schweitzer | Reactor Modeling of a Slurry Bubble Column for Fischer-Tropsch Synthesis[END_REF] . 𝜌 , 𝜀 and 𝑀 are respectively the liquid density (gꞏm -3 ), liquid volume per reactor volume and liquid molar mass (gꞏmol -1 ). 𝜀 is the volume of gas per reactor volume, and 𝑃, 𝑇, 𝑅 the pressure (Pa), temperature (K) and the universal gas constant (J•mol -1 •K -1 ).

Since the adsorbed species are not moving along the bed, their material balances can be written in its simplified form:

𝜕𝑐 * 𝜕𝑡  * , • 𝑟 (4)
with 𝑐 * (mol•gcat -1 ) corresponding to the concentration of the adsorbed species 𝑖 * at the catalyst surface.

Numerical methods

The differential Equations ( 2) and ( 4) are solved using the Livermore Solver for Ordinary Differential Equations [START_REF] Hindmarsh | TWO NEW INITIAL VALUE ORDINARY DIFFERENTIAL EQUATION SOLVERS[END_REF] , implemented as a Fortran program.

In order to fit the experimental data presented in the next section, the kinetic parameters 𝑘 of the model are estimated by minimizing the objective function 𝑓 :

𝑓 𝑤 𝑓 𝑓 (5)
in which 𝑓 corresponds to the model-estimated value of the experimental data 𝑓 . The data to fit are the CO conversion, and the CH4, C2H4, C2H6, C3H6, C3H8, C4H8, C4H10 selectivities. The optimization weighting factor 𝑤 are all fixed to 10, except for the CO conversion for which it is fixed to 1 because of its higher order of magnitude. Starting from an initial guess, a Levenberg-Marquardt algorithm is used for local optimization.

Experimental data

The description of the Fischer-Tropsch experiments can be found in detail in [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] . Briefly, 2 mm diameter reactors of a high-throughput 16-parallel reactors unit were loaded with about 350 mg of catalyst (15 wt.% Co/Siralox catalysts). The catalysts were reduced in-situ under 0.45 NL•h - 1 of pure H2, at 400°C for 16 h. Then the reduced catalysts were either tested fresh or pre-carburized

in situ, under different conditions of GHSV (1.2 -6.8 NL•h -1 •g -1 )
and syngas composition (H2/CO = 1.85 -2.12) at fixed temperature (220C°) and pressure (20 barg).

For the fresh catalyst evaluations, the different operating conditions were explored just after the reduction step, in a successive manner to avoid errors associated with the mass effect [START_REF] Hazemann | Kinetic data acquisition in high-throughput Fischer-Tropsch experimentation[END_REF] .

For the carburized catalysts evaluation, a syngas stabilization step was carried out after the reduction and the catalyst was then carburized in-situ, using two CO temperature treatments to obtain two different extents of carburization. The first treatment, carried out at 220°C, induced carburization of 32% of the cobalt, while the second treatment, carried out at 230°C, gave an extent of carburization of 48% [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] . Temperature programed hydrogenation experiments showed that this carburization treatment led to very low amounts of carbon [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] , which can thus be discarded as the cause of deactivation. The different operating conditions were finally explored in the same way as for the fresh catalyst.

In summary, 14 experimental data points with different GHSV and H2/CO ratios are used to optimize the kinetic parameter on the fresh catalyst, while 12 points are used for the carburized catalyst at two different extent of carburization. We have evaluated different criteria to assess the presence of mass and heat transfer limitations in a previous study [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] . All criteria were fulfilled indicating intrinsic kinetic conditions.

Results and discussion

Fresh catalyst performances modeling

The ability of the model to simulate fresh catalyst performances is shown in Figure 1, which represents the parity plot of the CO conversion. The deviation of the simulated conversion regarding the experimental one is comparable to the accuracy of the measurements (10%). In line with literature [START_REF] Storsaeter | Microkinetic modelling of the formation of C1 and C2 products in the Fischer-Tropsch synthesis over cobalt catalysts[END_REF][START_REF] Ma | Fischer-Tropsch Synthesis: Influence of CO Conversion on Selectivities, H2/CO Usage Ratios, and Catalyst Stability for a Ru Promoted Co/Al2O3 Catalyst Using a Slurry Phase Reactor[END_REF][START_REF] Bukur | Effect of CO Conversion on the Product Distribution of a Co/Al2O3 Fischer-Tropsch Synthesis Catalyst Using a Fixed Bed Reactor[END_REF][START_REF] Lillebø | Fischer-Tropsch Synthesis at High Conversions on Al2O3-Supported Co Catalysts with Different H2/CO Levels[END_REF] , the CH4 and olefins selectivity decrease with increasing CO conversion while the C5+ selectivity increases. A decrease of the heavy compounds and olefins selectivity is observed with the H2/CO ratio increase, which is again coherent with experimental results and literature.

The calculated surface coverages of the catalysts at the reactor entrance is presented in Figure 3a, and at the outlet in Figure 3b. In accordance with several micro-kinetic studies [START_REF] Boyer | Development of the Fischer-Tropsch Process: From the Reaction Concept to the Process Book[END_REF][START_REF] Visconti | Detailed Kinetics of the Fischer-Tropsch Synthesis on Cobalt Catalysts Based on H-Assisted CO Activation[END_REF][START_REF] Den Breejen | On the Origin of the Cobalt Particle Size Effects in Fischer-Tropsch Catalysis[END_REF][START_REF] Storsaeter | Study of the effect of water on Fischer-Tropsch synthesis over supported cobalt catalysts[END_REF][START_REF] Kocić | Activity and selectivity loss modelling on Co based Fischer-Tropsch catalysts[END_REF] , the main adsorbed species are CO* and H*. Despite a higher fraction of H* than those generally reported (10 -30%) [START_REF] Boyer | Development of the Fischer-Tropsch Process: From the Reaction Concept to the Process Book[END_REF]243,[START_REF] Yang | Reaction mechanism of CO activation and methane formation on Co Fischer-Tropsch catalyst: A combined DFT, transient, and steady-state kinetic modeling[END_REF][START_REF] Storsaeter | Microkinetic modelling of the formation of C1 and C2 products in the Fischer-Tropsch synthesis over cobalt catalysts[END_REF] , the obtained value remains plausible for higher H2/CO ratios 51 (73%).

The OH* fraction is in good agreement with SSITKA measurements of den Breejen et al. [START_REF] Den Breejen | On the Origin of the Cobalt Particle Size Effects in Fischer-Tropsch Catalysis[END_REF] , who 160 measured values comprised in the range 5-10%. Additionally, the free sites content is similar to the one reported by Yang et al. [START_REF] Yang | Reaction mechanism of CO activation and methane formation on Co Fischer-Tropsch catalyst: A combined DFT, transient, and steady-state kinetic modeling[END_REF] . The low fraction of Cx* intermediates (corresponding to 𝑅 * in Table 1) is mainly due to the high propagation and termination rates [START_REF] Kocić | Activity and selectivity loss modelling on Co based Fischer-Tropsch catalysts[END_REF] .

Figure 2 Effect of CO conversion (left) and syngas composition (right) on selectivity 165

The surface comparison between the entrance (Figure 3a) and the outlet (Figure 3b) of the reactor clearly shows the importance of the water adsorption equilibrium in the micro-kinetic model. When the CO conversion increases (i.e. going toward the reactor outlet) the fraction of OH* species at the catalyst surface also increases due to higher generated water partial pressures.

Interestingly, this evolution occurs at the expense of the H* covering, inducing a lowering of the H*/CO* ratio at the catalyst surface. The introduction of the water adsorption equilibrium in the model creates a dependency of the H*/CO* ratio to the CO conversion level, resulting in a change in the selectivity. These results confirm the role of water adsorption on the selectivity dependency as a function of the CO conversion level [START_REF] Todic | Effect of process conditions on the product distribution of Fischer-Tropsch synthesis over a Re-promoted cobalt-alumina catalyst using a stirred tank slurry reactor[END_REF][START_REF] Zhou | Advanced fundamental modeling of the kinetics of Fischer-Tropsch synthesis[END_REF][START_REF] Frøseth | Steady state isotopic transient kinetic analysis (SSITKA) of CO hydrogenation on different Co catalysts[END_REF][START_REF] Botes | Influences of Water and Syngas Partial Pressure on the Kinetics of a Commercial Alumina-Supported Cobalt Fischer-Tropsch Catalyst[END_REF][START_REF] Lögdberg | On the selectivity of cobalt-based Fischer-Tropsch catalysts: Evidence for a common precursor for methane and long-chain hydrocarbons[END_REF] . The main mechanism of deactivation by carburization is the loss of metallic cobalt, known as the active phase in Fischer-Tropsch synthesis. It was however observed [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] that the turnover frequency could also be lower on carburized catalysts. This behavior corresponds to a decreased intrinsic activity of the metallic sites, but could also be linked to the complex FT mechanism, for which a simple modification leads to more dramatic reactivity changes. Since no evolution of the particle size (i.e. dispersion) was observed after carburization [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] , the loss of metallic cobalt due to carburization was assumed to be proportional to the loss of reduced cobalt surface sites. The number of active sites (𝑁 ) in the model is therefore written as:

𝑁 1 𝐷𝑂𝐶 • 𝑁 , (6)
𝑁 , being the number of active sites of the freshly reduced catalyst.

Note, however, that this does not signify that carburization is a surface phenomenon that induces site poisoning. It might rather be interpreted as a full carburization of some particles, which induces a loss of active sites, while others remain metallic. In this sense, the model is consistent with the core-shell model we proposed [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] , in which small particles would be fully carburized while larger ones only exhibit a carbide shell under their metallic surface.

The carburized catalyst performances were simulated using the same kinetic parameters values as for the fresh catalysts, and the obtained results are shown in Figure 4. Experimental CO conversions are well represented by the model, suggesting that the simple loss of active sites is the main carburization induced deactivation mechanism. However, this model does not predict the selectivity shift (Supporting information), and a change in the elementary reaction rates has to be considered. For model (B), only the values of the H2O and H2 adsorption equilibrium constants were adjusted by the optimizer. DRIFTS experiments showed that the CO adsorption strength was not affected by carburization [START_REF] Hazemann | Selectivity loss in Fischer-Tropsch synthesis: The effect of cobalt carbide formation[END_REF] , thus the CO adsorption equilibrium was not adjusted. The obtained fit (Figure S1, supplementary information) is, however, not completely satisfactory, because of the inadequate predictions of the CO conversion and olefins selectivity. For model (C), the propagation and CH4/paraffins termination rate constants were varied, and a much better fit was obtained with a residual sum of squares value divided by 2-3 compared to optimization (B). This mechanism is therefore more likely to explain deselectivation. We still verified that the combination of (B) and (C) did not improve the fit, and only a slight diminution of the residual sum of squares value was observed. A fourth optimization (D) was carried out where only termination reactions were considered (including the olefin termination rate constant). This optimization gave the best results among all the different hypotheses, and was thus repeated on the 220°C treated catalyst data. The obtained parity plots are presented on Figure 2 for both 220°C and 230°C treated catalyst. It can be seen that CO conversion, CH4, paraffins and olefins selectivity are correctly modeled considering the experimental error. The plot of residuals is given in Figure S2 (supplementary information).

These results indicate that the effect of carburization on the catalyst selectivity is not linked to the 235 modification of reactant adsorption equilibrium, but rather to a change of the intrinsic site reactivity. More precisely, the main product termination reactions are significantly accelerated.

The relative evolution of the modified rate constant on carburized catalysts compared to the fresh one is presented in Table 3. It can be noted that hydrogenation reactions (paraffins and methane termination) are much more accelerated than dehydrogenation ones (olefins termination). Additionally, the increase of the extent of carburization induces a more important rate constant evolution as illustrated on Figure 3.

A correlation can be made between the DOC and the rate constant variations. Since methane termination rate constant evolution seems to follow the paraffin rate constant, and because these two kinds of products are generated with a similar mechanism (Table 1), a unique regression was used for the two rate constants. A second order equation represents quite accurately the rate constant evolutions. Such functions were therefore chosen to model the kinetic rate constants dependency to the DOC.

Figure 3 Termination rate constant variation as function of carburization extent

Based on these regressions, methane, paraffins and olefins termination reaction rate constants can be calculated from the following equations: 260

𝑘 , 𝐷𝑂𝐶 𝑘 , 1 8.0 • 𝐷𝑂𝐶 (7) 𝑘 𝐷𝑂𝐶 𝑘 1 2.4 • 𝐷𝑂𝐶 (8)
These Equations, together with (6), describe at the micro-kinetic scale, the carburization effect on catalyst performances. A modified model, including the extent of carburization as input variable, can thus be proposed to predict carburized catalyst performances.

Effect of carburization on catalyst performances 265

Figure 4 presents the predicted catalyst activity and selectivity as a function of its extent of carburization, at 220°C, 20 barg and H2/CO = 2.12 for different CO conversion levels.

The detrimental effect of carburization on activity is clearly visible, the CO consumption rate drops from 8.5 µmol•s -1 •g -1 on the non-carburized catalyst down to 0.3 µmol•s -1 •g -1 on the 90% carburized one. It can also be observed that the reactant partial pressures, directly linked to the CO conversion level, have a lower impact on the CO consumption rate for carburized catalysts.

Regarding the selectivity, dramatic changes are also observed when the extent of carburization increases. The methane selectivity is for instance doubled when the extent of carburization increases from 0% to 80%, while the C5+ selectivity is lowered from 80 to 65%. A surprising behavior is, however, observed above 80% of carburization. The CH4 selectivity does not increase anymore, but decreases while the C5+ selectivity slightly increases. A similar trend is moreover observed with the olefin selectivity: from 10 to 40% of carburization, the O/P ratio of C2-C5 compounds slightly decreases while above 40% this ratio increases. In particular, the O/P ratio dependency to the CO conversion level increases significantly when approaching full carburization of the catalyst, inducing a very high olefin selectivity for carburized catalysts operating at low conversion. This phenomenon could be due to olefins re-adsorption rate which was not considered as function of the extent of carburization, making the olefins adsorption equilibrium rather oriented toward desorption at high extent of carburization. However, since no experimental data are available with highly carburized catalysts (>50%), it is difficult to settle if the proposed model is valid at high extent of carburization or not. The predicted behavior is yet in line with recent findings of [START_REF] Zhong | Cobalt carbide nanoprisms for direct production of lower olefins from syngas[END_REF][START_REF] Li | Mechanism of the Mn Promoter via CoMn Spinel for Morphology Control: Formation of Co2C Nanoprisms for Fischer-Tropsch to Olefins Reaction[END_REF][START_REF] Li | Effects of Sodium on the Catalytic Performance of CoMn Catalysts for Fischer-485 Tropsch to Olefin Reactions[END_REF] , who reported the high FTO (Fisher-Tropsch to Olefins) activity of Co2C nanoprisms. It might thus be interesting to confirm the observed trend with dedicated experiments.

Conclusion

A micro-kinetic model has been established to predict the effect of carburization on Fischer-Tropsch cobalt catalyst performance. The first step was to add the water adsorption equilibrium, to obtain an accurate representation of the evolution of the catalyst selectivity with CO conversion. Water adsorption was found to modify significantly the H*/CO* ratio at the catalyst surface, and thus the selectivity. Micro-kinetic analysis then revealed that product termination was the most affected elementary step by carburization, and not reactants adsorption or chain propagation. The evolutions of the termination kinetic rate constants were connected to the extent of carburization, well represented by a 2 nd order equation. The obtained model was able to represent quite accurately the effect of carburization on both catalyst activity and selectivity. This work offers new perspectives to predict catalyst activity and selectivity evolution with time on stream, for instance by implementing a carburization reaction into the proposed reaction

Figure 1

 1 Figure 1 Parity plot of the experimental and predicted CO conversion of the fresh catalyst

Figure 3

 3 Figure 3 Catalyst surface composition estimated by the model at the entrance (a) and outlet (b) of the reactor, operating at 220°C, 20 barg, H2/CO = 2.12 and 55% CO conversion

Figure 4

 4 Figure 4 Parity plot of the experimental and predicted CO conversion of the carburized catalysts

Figure 2

 2 Figure 2 Parity plots of carburized catalysts performances obtained with optimization D (a: CO conversion, b: CH4 selectivity, c: C5+ selectivity, d: olefins/paraffins ratio of C2-C4 compounds)

Figure 4 Figure 5 .

 45 Figure 4 Carburization effect on activity and selectivity at 220°C, 20 barg and H2/CO = 2.12 for 290 different CO conversion levels (modeling results, a: CO consumption rate, b: CH4 selectivity, c: C5+ selectivity, d: olefins/paraffins ratio of C2-C4 compounds)

Figure 5

 5 Figure 5 80% carburized catalyst surface composition estimated by the model at outlet of the reactor, operating at 220°C, 20 barg, H2/CO = 2.12 and 55% CO conversion

Table 1

 1 Elementary steps of the micro-kinetic model of FTS

	Step	Name	Reaction
	(1)	H2 adsorption	𝐻	2 * ↔ 2𝐻 *
	(2)	CO adsorption	𝐶𝑂 * ↔ 𝐶𝑂 *
	(3)	CO complexation	𝐶𝑂 * 𝐻 * ↔ 𝐻𝐶𝑂 * *
	(4)	Monomer formation	𝐻𝐶𝑂 * 2𝐻 * → 𝐶𝐻 * 𝑂𝐻 * *
	(5)	Initiation	𝐶𝐻 * 𝐻 * → 𝐶𝐻 * *
	(6)	Propagation	𝑅 * 𝐶𝐻 * → 𝑅 * *	𝑛: 1 → 49
	(7)	Methane termination	𝐶𝐻 * 𝐻 * → 𝐶𝐻	2 *
	(8)	Paraffins termination	𝑅 * 𝐻 * → 𝑃	2 *	𝑛: 2 → 50
	(9)	Ethylene termination	𝐶 𝐻 * ↔ 𝐶 𝐻	𝐻 *
	(10)	Olefins termination	𝑅 * ↔ 𝑂	𝐻 *	𝑛: 3 → 50
	(11)	H2O desorption	𝑂𝐻 * 𝐻 * ↔ 𝐻 𝑂 2 *
	85
	𝑐 (mol•gcat -1 ) being the concentration of the reactant 𝑖 at the catalyst surface or in the liquid phase,
	 , the stoichiometric coefficient of reaction 𝑗, and 𝑘 the associated rate constant. The obtained

Table 2 .

 2 The residual sum of square values obtained after optimization are also reported in the same table. The residual sum of square obtained with the basic model considering a site loss only is put as reference (optimization A).

Table 2

 2 List of optimizations and obtained objective function values

	ref.
	reactions
	optimization

Table 3 .

 3 Impact of carburization on termination rate constants (optimization D)

	Reaction	Rate constant evolution
		(220°C treated catalyst) (230°C treated catalyst)
	(7) CH4 termination	+62%	+178%
	(8) Paraffins termination	+101%	+225%
	(10) Olefins termination	+34%	+56%

Acknowledgments

The authors would like to acknowledge the financial support from IFP Energies nouvelles.

scheme. This work should also be extended to other deactivating phenomena, to propose a comprehensive kinetic model considering both deactivation and deselectivation issues.