MD Nathalie Ganne-Carrié
email: nathalie.ganne@jvr.aphp.fr

MD Richard Layese

Valérie Bourcier

MD Carole Cagnot

Patrick Marcellin

MD Dominique Guyader

MD Stanislas Pol

MD Dominique Larrey

Victor De De Lédinghen

MD Denis Ouzan

MD Victor De Lédinghen

MD Fabien Zoulim

MD Dominique Roulot

MD Albert Tran

MD; Jean-Pierre Bronowicki

MD; Jean-Pierre Zarski

MD Ghassan Riachi

MD; Paul Calès

MD; Jean-Marie Péron

MD Laurent Alric

MD Marc Bourlière

MD Philippe Mathurin

MD; Jean-Frédéric Blanc

MD Armand Abergel

MD Lawrence Serfaty

MD Ariane Mallat

MD; Jean-Didier Grangé

MD Pierre Attali

MD Yannick Bacq

MD Claire Wartelle

MD Thông Dao

MD Yves Benhamou

Christophe Pilette

MD; Christine Silvain

MD Christos Christidis

MD Dominique Capron

MD Brigitte Bernard-Chabert

MD David Zucman

MD Vincent Di Martino

MD; Jean-Claude Trinchet

principal investigator Pierre Nahon

MD Françoise Roudot-Thoraval

Prof Wartelle

Dr Dao

Dr Benhamou

Prof Pilette

Dr Silvain

Prof Christidis

Dr Bernard-Chabert Capron

Dr Zucman

Prof Martino Di

Dr Nahon

Prof Ganne-Carrié

Dr Bourcier

Mr Layese

Mrs Cagnot

Hélène Fontaine

Vincent Leroy

Jean- Marie Péron

Sebastien Dharancy

Jean- Frédéric Blanc

Gérard Thiefin

Sophie Hillaire

Vincent Di

Prof Gilead Di

MSD, Janssen Bristol-Myers Gilead

Dr Squibb

Bacq

P Bedossa

M Bonjour

I Durand-Zaleski

A Laurent

P Marche

D Salmon

V Thibault

V Vilgrain

J Zucman-Rossi

V Petrov-Sanchez

Jean Chu

Bondy Verdier

H Pol

Fontaine

Mallat Chu

Paul Brousse

Bourcier, Layese, Marcellin, Guyader, Pol Ganne-Carrié Larrey

Ouzan, Zoulim, Roulot, Tran, Bronowicki, Zarski, Riachi, Calès, Péron, Alric, Bourlière, Mathurin, Blanc, Abergel, Serfaty, Mallat, Grangé, Attali, Bacq, Wartelle, Dao, Benhamou, Pilette, Silvain, Christidis, Capron De Lédinghen

Nahon, Roudot-Thoraval. Di Martino

Ganne - Carrié

Nomogram for individualized prediction of hepatocellular carcinoma occurrence in hepatitis C virus cirrhosis (ANRS CO12 CirVir)

Keywords: HBV: hepatitis B virus, HCV: hepatitis C virus, HCC: hepatocellular carcinoma, AFP: alfa-fetoprotein, SVR: sustained virological response Layese, Roudot-Thoraval

 [START_REF]EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma[END_REF]Hôpital Saint Eloi, Service d'Hépatologie, Montpellier; [START_REF] Bruix | Management of hepatocellular carcinoma[END_REF] Hôpital Haut-Lévêque, Service d'Hépatologie, Bordeaux; [START_REF] Degos | Hepatitis C virus related cirrhosis: time to occurrence of hepatocellular carcinoma and death[END_REF] Institut Arnaud Tzanck, Service d'Hépatologie, St Laurent du Var; [START_REF] N'kontchou | Risk factors for hepatocellular carcinoma in patients with alcoholic or viral C cirrhosis[END_REF] Hôpital Hôtel Dieu, Service d'Hépatologie, Lyon; 9 AP-HP, Hôpital Avicenne, Service d'Hépatologie, Bobigny; 10 CHU de Nice, Service d'Hépatologie, et INSERM U1065, Université de Nice-Sophia-Antipolis, Nice; [START_REF] Bravi | Coffee drinking and hepatocellular carcinoma risk: a meta-analysis[END_REF] Hôpital Brabois, Service d'Hépatologie, Vandoeuvre-les-Nancy; [START_REF] Nkontchou | Impact of metformin on the prognosis of cirrhosis induced by viral hepatitis C in diabetic patients[END_REF] Hôpital Michallon, Service d'Hépatologie, Grenoble; [START_REF] Mohanty | Statins Are Associated With a Decreased Risk of Decompensation and Death in Veterans With Hepatitis C-Related Compensated Cirrhosis[END_REF] Hôpital Charles-Nicolle, Service d'Hépatologie, Rouen; [START_REF] Alberti | The metabolic syndrome--a new worldwide definition[END_REF] CHU d'Angers, Service d'Hépatologie, Angers; [START_REF] Brunt | Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions[END_REF] Hôpital Purpan, Service d'Hépatologie, Toulouse; [START_REF] Bruix | Management of hepatocellular carcinoma: an update[END_REF] CHU Toulouse, Service de Médecine Interne-Pôle Digestif UMR 152, Toulouse; [START_REF] Bruno | Sustained virological response to interferon-alpha is associated with improved outcome in HCV-related cirrhosis: a retrospective study[END_REF] Hôpital Saint Joseph, Service d'Hépatologie, Marseille; [START_REF] Marco | Effects of Viral Eradication in Patients with HCV and Cirrhosis Differ With Stage of Portal Hypertension[END_REF] Hôpital Claude Huriez, Service d'Hépatologie, Lille; [START_REF] Huang | Baseline gamma-glutamyl transferase levels strongly correlate with hepatocellular carcinoma development in non-cirrhotic patients with successful hepatitis C virus eradication[END_REF] Hôpital St André, Service d'Hépatologie, Bordeaux; [START_REF] Ganne-Carrie | Predictive score for the development of hepatocellular carcinoma and additional value of liver large cell dysplasia in Western patients with cirrhosis[END_REF] Hôpital Hôtel Dieu, Service d'Hépatologie, Clermont-Ferrand; [START_REF] Velazquez | Prospective analysis of risk factors for hepatocellular carcinoma in patients with liver cirrhosis[END_REF] AP-HP, Hôpital Saint-Antoine, Service d'Hépatologie, Paris; [START_REF] Yang | Risk estimation for hepatocellular carcinoma in chronic hepatitis B (REACH-B): development and validation of a predictive score[END_REF] AP-HP, Hôpital Henri Mondor, Service d'Hépatologie, Créteil; [START_REF] Yuen | Independent risk factors and predictive score for the development of hepatocellular carcinoma in chronic hepatitis B[END_REF] AP-HP, Hôpital Tenon, Service d'Hépatologie, Paris; [START_REF] Wong | Clinical scoring system to predict hepatocellular carcinoma in chronic hepatitis B carriers[END_REF] AP-HP, Hôpital Paul Brousse, Service d'Hépatologie, Villejuif; [START_REF] Papatheodoridis | Incidence and predictors of hepatocellular carcinoma in Caucasian chronic hepatitis B patients receiving entecavir or tenofovir[END_REF] Hôpital Trousseau, Unité d'Hépatologie, CHRU de Tours; [START_REF] Abu-Amara | The applicability of hepatocellular carcinoma risk prediction scores in a North American patient population with chronic hepatitis B infection[END_REF] Hôpital d'Aix-En-Provence, Service d'Hépatologie, Aix-En-Provence; [START_REF] Chang | Clinicalguide risk prediction of hepatocellular carcinoma development in chronic hepatitis C patients after interferon-based therapy[END_REF] Hôpital de la Côte de Nacre, Service d'Hépatologie, Caen; [START_REF] Lee | Development and validation of a clinical scoring system for predicting risk of HCC in asymptomatic individuals seropositive for anti-HCV antibodies[END_REF] AP-HP, Groupe Hospitalier de La Pitié-Salpêtrière, Service d'Hépatologie, Paris; [START_REF] El-Serag | A new laboratory-based algorithm to predict development of hepatocellular carcinoma in patients with hepatitis C and cirrhosis[END_REF] CHU Le Mans, Service d'Hépatologie, Le Mans; [START_REF] Hosaka | Long-term entecavir treatment reduces hepatocellular carcinoma incidence in patients with hepatitis B virus infection[END_REF] CHU de Poitiers, Service d'Hépatologie, Poitiers; [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] Institut Mutualiste Montsouris, Service d'Hépatologie, Paris; 32 Hôpital Amiens Nord, Service d'Hépatologie, Amiens; 33 Approximately 80% of hepatocellular carcinomas (HCC) worldwide are related to chronic infection with hepatitis B (HBV) or hepatitis C virus (HCV).

In Western countries, spread of HCV infection has been partly responsible for a rise in the incidence of cirrhosis and HCC during recent decades (1). In those countries, historical cohort studies reported 5-year cumulative incidences of HCC of nearly 17% in patients with HCV-cirrhosis (2). More recently, large prospective Western cohorts confirmed the high incidence of HCC in HCV-cirrhosis: in the subgroup of 410 patients with HCV-cirrhosis enrolled in the HALT-C American cohort, and who did not respond to peg-interferon and ribavirin (3), and among 1,323 patients with histologically proven and uncomplicated HCV cirrhosis enrolled from 2006 to 2012 in the ANRS CO12 CirVir French multicenter cohort (4), cumulative HCC incidences were 7% at 5 years and 11.4% at 4 years, respectively. Since HCC screening is considered cost-effective if the incidence of HCC is over 1.5% per year (5, 6), patients with HCV-cirrhosis should thus undergo periodic surveillance for HCC.

Moreover, in the ANRS CO12Cirvir French prospective cohort, this policy of periodic surveillance of cirrhosis was successful and resulted in detection of a high proportion of small HCC, fulfilling Milan criteria in 80% of cases and enabling curative treatment in 70% of cases (4). However, while patients with cirrhosis, whatever its etiology, are at risk of HCC and should undergo periodic surveillance, experience shows that not all of them have the same risk of developing HCC, suggesting that HCC surveillance in certain subsets of cirrhotic patients may not be cost-effective.

Several potential factors have been shown to be independently associated with higher risk of HCC occurrence in patients with HCV-cirrhosis: a) host factors, including male gender (7, 8), increasing age (3, 7, 8), black origins (3), diabetes and overweight (8); b) virological factors such as detectable serum HCV RNA (9) and HCV genotypes 1 (4) or 3 (10); c) disease factors, including liver failure assessed by albumin serum level (4) and portal hypertension assessed either by low platelet count (4) or by esophageal varices (3, 7); and d) environmental factors such as tobacco intake. Conversely, other factors were identified with lower risk of HCC and might be chemoprotective in patients with HCVcirrhosis, such as coffee consumption (11) and metformin (12) or statin treatment (13).

However, at an individual level, it remains difficult to assess the specific risk of HCC in a patient with HCV-cirrhosis, or to advise that person on the need for periodic screening for HCC. Personalized assessment of individual risk of HCC thus represents a challenge. Therefore, the aims of this study were to build and validate a simple personalized scoring system using baseline independent variables for HCC occurrence, and to develop a nomogram for predicting HCC risk in patients with HCV-related compensated cirrhosis included in the large French prospective multicenter ANRS CO12 CirVir cohort (4).

METHODS

Patient selection

Among patients with biopsy-proven compensated (Child-Pugh A) and uncomplicated virus-related cirrhosis who were enrolled in the French multicenter ANRS CO12 CirVir cohort between March 2006 and July 2012 and prospectively followed up for development of HCC (4), those with chronic infection by HCV (positive HCV serology whatever the level of viral replication) and without HBV co-infection (negative serum HBsAg) were selected. If data on well known predictive factors for HCC occurrence in patients with cirrhosis were not available, patients were secondarily excluded.

Pre-inclusion assessment included usual clinical and biological parameters (gender, age, body mass index (BMI), diabetes, arterial hypertension, dyslipidemia, metabolic syndrome, prothrombin time, bilirubin serum level, albumin serum level, platelet count, liver enzymes (ASAT, ALAT, GGT), AFP serum level, esophageal varices, HCV genotype, HCV viral load, HIV co-infection), histological lesions of steato-hepatitis and a Doppler ultrasonography (US) to rule out complications at baseline, including HCC.

Patient information was recorded in a computerized database by a clinical research associate specifically dedicated to the ANRS CO12 CirVir cohort at each center. For all patients, past and ongoing alcohol or tobacco consumption was quantified and recorded at inclusion. Excessive alcohol consumption was defined according to World Health Organization criteria (more than 2 glasses per day for females and more than 3 glasses per day for males); an overall minimal duration of 5 years was required.

Past medical history was also noted. In particular, the senior hepatologist in charge of a given patient at each center determined whether metabolic syndrome was present or not, based on clinical guidelines (14) and/or histological examination of liver biopsy (15).

Follow-up

Follow-up was scheduled according to French guidelines (Haute Autorité de Santé). Examination by Doppler US was performed every 6 months. For a given patient, it was recommended that US be formed at the same center by an experienced operator. A report was completed by each operator, mentioning the presence or not of focal liver lesions.

All events occurring during follow-up, liver-related or not, were recorded based on information obtained from medical files of patients at each center, and monitored by a panel of 3 dedicated clinical research associates. All treatments, including antiviral therapy, were recorded at inclusion, and any modification during follow-up was notified.

HCC diagnosis and treatment

In case of focal liver lesions detected by US, the following procedures were carried out: i) echogenicity, number and diameter of nodules (classified as <10 mm, 11-20 mm, 21-30 mm, 31-50 mm or >50 mm) and anatomic localization according to the Couinaud classification were reported; ii) portal vasculature (main trunk and branches), hepatic veins, and vena cava were systematically examined; and iii) a diagnostic procedure using contrast-enhanced imaging (CT-scan or MRI), serum alpha-fetoprotein (AFP) assay and/or guided biopsy was performed according to 2005 AASLD guidelines (6) updated in 2011 (16). HCC diagnosis was thus established either by histological examination by an experienced pathologist, or using probabilistic non-invasive criteria (mainly dynamic imaging showing early arterial hypervascularization and portal washout) according to the different periods of time (before and after 2011). When the HCC diagnosis was established, treatment was decided using a multidisciplinary approach according to AASLD or EASL guidelines for HCC (5, 6, 16). Reports of imaging techniques showing liver focal lesions were secondarily reviewed by the two senior hepatologists from institution 1 (authors VB and PN).

Antiviral treatment and viral replication

From 2006 to January 2014 (before the introduction of second-generation direct antiviral agents [DAAs] in France), all antiviral therapies conducted were interferon-based according to international guidelines. Since January 2014, patients could also receive second-generation DAAs with or without pegylated interferon and ribavirin for 12 to 24 weeks as part of early access programs, or after market approval according to national and/or international guidelines. The primary efficacy outcome was a SVR, defined as HCV RNA undetectable by qualitative polymerase chain reaction assay (< 50 IU/mL) at the end of either a 24-week untreated follow-up period for interferon-based antiviral therapies without second generation DAAs, or a 12-week untreated follow-up period for antiviral therapy, including second generation DAAs.

Statistical analyses

To internally validate the final adjusted HCC algorithm, we used a split-sample approach to assess discrimination, calibration and predictive ability of the model. We randomly divided the studied population of HCV-related Child-Pugh A cirrhosis into a development subset (2/3, on which model parameter estimates and the corresponding model-based HCC probabilities were derived) and a validation subset (1/3) to which model results were applied), and used our final model in these 2 samples.

Descriptive statistics are presented for the entire cohort and for the 2 subsets, as median [interquartile range (IQR)] for continuous variables and as numbers (percentages) for categorical data. Comparisons of patient subsets were performed using the Student t-test or Wilcoxon rank sum test for continuous variables, and the Chi-square or Fisher's exact test for categorical variables.

The cumulative incidence of HCC was estimated in the training cohort in a competing risks framework, where deaths free of HCC were considered as competing events. Since no difference was observed with Kaplan-Meier estimates, univariate and multivariate Cox proportional hazards models were used in the training cohort to assess factors associated with occurrence of HCC. In particular, the effect of a SVR was assessed in Cox regression as a time-dependent co-variate, since patients without SVR at inclusion could be (re)treated and achieve SVR during follow-up. For these patients, end of treatment was defined as time T0, since patients with undetectable HCV RNA at that time were considered as having a SVR. All variables tested in univariate Cox analysis with a p value less than 0.20 were tested in multivariate Cox regression.

A predictive score was then constructed as a weighted sum of all independent predictive factors for the occurrence of HCC, identified in Cox multivariate analysis. The weight of each factor was given by a linear transformation (multiplied by 3) of the estimated coefficient in Cox regression analysis and rounded off to the nearest integer. Baseline HCC-free probabilities were also estimated from Cox multivariate analysis at 1, 3 and 5 years. Predicted risks for HCC were estimated by the following equation:

, where was baseline HCC-free probability and was the inverse multiplicative coefficient used to build the HCC score. Predicted probabilities of HCC at 1, 3 and 5 years are presented for each level of the score as a nomogram.

Cumulative incidence curves according to the different risk groups of HCC determined from the score were built using a clock reset approach. Patients who switched from non-SVR to SVR status were censored at the time of SVR, which was the date of the end of treatment. The time of SVR was reset at time 0 for patients having SVR status during follow-up.

Comparison of cumulative incidence curves was assessed with univariate Cox regression analyses.

Discrimination was assessed by receiver operating curve (ROC) analysis. Overall predictive accuracy of the derived score for predicting the development of HCC at 1 and 3 years after inclusion was tested by estimating the area under the ROC curve (AUROC).

Calibration of the model was assessed by Harrell's C statistics and the correlation coefficient between

predicted and observed probabilities of HCC.

The score was secondarily tested in the validation cohort.

Lastly, the score was reassessed after twelve months of follow-up.

All statistical analyses were performed using Stata 13.0 (StataCorp, College Station, TX). A P value of 0.05 or less was considered statistically significant. 1).

RESULTS

During a median follow-up of 51.0 months [32.3-71.9], a diagnosis of HCC was established for 142 of the 1,080 selected patients, i.e. 103 and 39 in the training and validation sets, respectively (Figure 1;

Table 2).

Most HCCs were uni-nodular (n=87, 64.9%) and smaller than 30 mm (n=100, 80.0%). Portal obstruction and a serum AFP level >200 ng/mL at diagnosis were observed in 7.9% and 12.3%, respectively. Overall, 107 (75%) patients with HCC fell within Milan criteria, and curative treatment as first-line therapy was performed in 83 (66.4%). There were no significant differences in HCC characteristics between the two groups of patients (Table 2).

Training cohort

Based on multivariate Cox regression analysis, 5 out of 23 variables listed in Table 3 3). An 11-point risk score was derived from the estimated βregression coefficients of these 5 variables, by linear transformation (multiplied by 3) of the coefficients and rounding off (Table 4). The population was stratified into three groups according to this scoring system, with HCC occurrence gradually increasing from 2% to 30.1% at 5 years for patients with the lowest (≤ 3, n = 117, 13.8%) and highest (≥ 8, n = 349, 40.6%) HCC risk scores, respectively (p < 0.001, Figure 2A). AUROC for 1-and 3-year predictions after baseline was 0.678 In order to develop an individualized prediction of HCC, a nomogram derived from this score was also built, given the 1-, 3-, and 5-year probabilities of HCC for each level of the score (Figure 3). The fit of the model was assessed by Harrell's C statistics at 0.72.

[
Calibration was also assessed for predicted HCC risk and observed risk, and showed a good correlation (r=.0.91, p<0.001).

Validation set

The cumulative incidence of HCC risk was estimated by the Kaplan-Meier method according to the 3 groups of the score built from the training cohort. HCC occurrence gradually increased from 0% to 20.3% at 5 years, for patients with the lowest (≤ 3, n = 64, 14.7%) and highest (≥ 8, n = 165, 37.9%) HCC risk scores (p < 0.001, Figure 2B).

In this group, the AUROC for the 3-year prediction of HCC was 0.736 [0.639-0.833], similar to that of the training group (p=0.75 between AUCs). Correlation between observed and predicted HCC risk was estimated with a coefficient at 0.86 (p<0.001)

DISCUSSION

Our results show that personalized prediction of HCC using easily available variables is feasible in patients with HCV-related cirrhosis. Indeed, a simple score combining 4 baseline variables and 1 timedependent variable was accurate in predicting HCC at the individual level in a large prospective cohort of French patients with HCV-cirrhosis. Relevant baseline independent variables used in this score were in accordance with the literature; indeed, increasing age (3, 7, 8), low platelet counts (4) and detectable serum HCV RNA (9) are the usual predictive factors for occurrence of HCC in patients with cirrhosis.

Conversely, it takes in account an original variable -the serum level of GGT -that was less frequently reported as an independent predictive factor for HCC (17-19) and not previously used by another scoring system. This simple test mainly summarizes the weight of co-morbidities, as patients with GGT above ULN (76%) had a higher body mass index (25.9 [23.1 -29.1] vs 25.4 [22.7 -28.1], p = 0.038), more frequent dyslipidemia (6% vs 3.2%, p = 0.042) and more frequent histological evidence of steato-hepatitis (44.8% versus 25.5 %, p = 0.01). Conversely, patients with GGT above the upper limit of normal did not have an increased proportion of diabetes (20.1% vs 16.4%, p = 0.13),

suggesting that increased serum GGT could be a very early surrogate marker of insulin resistance. Numerous personalized risk-scoring systems constructed using baseline-independent variables for HCC occurrence had been previously developed and validated in patients with cirrhosis due to various causes (8, 20, 21), and more recent ones are targeting patients with hepatitis B (22-24). In the last few years, Asian groups have derived and validated several HCC risk scores based on well-known risk factors such as cirrhosis, age, male sex and high HBV viral load (REACH-B, GAG-HCC, CU-HCC) (22-24). Overall, these recent scores have shown a high negative predictive value of over 95% for excluding HCC development in 3 to 10 years. These HCC risk scores were tested in several Western cohorts (25, 26), and appeared less effective in Caucasians.

In patients infected by HCV, a risk score for HCC was built whatever the stage of fibrosis (27, 28) and only one algorithm for HCC detection was developed and validated in American veterans with HCV-related cirrhosis (29), and in broader populations. While all risk scores for HCC in patients with

HBV included viral load (22-24), no risk score for HCC in patients with HCV took into account a SVR.

The enhanced HCC risk assessment in our model would enable personalized screening practices. The algorithm could optimize HCC surveillance by reducing false-positives, thus having considerable impact upon subsequent testing, reducing surveillance costs and avoiding unnecessary patient/provider anxiety, while optimizing approximations of individualized patient risk. HCC risk assessments yielded by our model-based instrument can be used to create a binary decision rule for clinical action;

for example, if HCC probability exceeds 20% at 5 years, then additional testing (e.g. cross-sectional imaging) could be performed. In contrast, in a very select group of patients (around 15%) with very low HCC risk (score ≤ 3, 5 years; HCC cumulative incidence around 2%), the need for HCC surveillance is questionable. However it is premature to adopt fixed cutoffs at this time.

The strengths of our study lie in the following: i) the homogeneity of patients selected using stringent criteria, particularly biopsy-proven cirrhosis; ii) its prospective design, conducted at 35 centers, with systematic periodic surveillance by liver imaging for HCC screening according to international guidelines; iii) stringent monitoring of all events during follow-up, in particular HCC; iv) internal validation of results in the split sample; and vi) the fact that SVR was taken into account. Conversely, our study had several limitations, mainly linked to the small number of patients with SVR at endpoint (39.5%), due to an inclusion period prior to introduction of second-generation DDAs in clinical practice. (30, 31). However, due to the high financial cost of these new antiviral treatments, only a minority of patients with HCV-cirrhosis worldwide had received them, even in Western countries, mainly in Europe. In addition, this HCC score could be used in countries with limited resources.

Finally, our score could be applied to SVR patients whose risk scores varied from 0 to 9, with a cumulative risk of HCC at five years ranging from 0 (for a score ≤ 3) to 30.1% (for a score ≥ 8). In addition, external validation outside of France is warranted. Interestingly, we showed that the score could be accurately updated with increasing age, but also with alterations in biochemical values and modification of viral status.

In conclusion, an HCC score constructed *Since SVR is a time-dependent variable, the total number of patients at risk seems higher than expected: patients achieving SVR during follow-up were considered before SVR and after SVR for the corresponding time.

1

  AP-HP, Hôpital Jean Verdier, Service d'Hépatologie, Bondy, Université Paris 13, Bobigny et INSERM U1162, Université Paris 5, Paris; 2 AP-HP, Hôpital Beaujon, Service d'Hépatologie, Clichy; 3 CHU Pontchaillou, Service d'Hépatologie, Rennes; 4 AP-HP, Hôpital Cochin, Département d'Hépatologie et INSERM UMS20, Institut Pasteur, Université Paris Descartes, Paris;

  Hôpital Robert Debré, Service Results: During follow-up (median: 51.0 months), 103 and 39 patients developed HCC in the training and validation sets, respectively. Five variables were independently associated with occurrence of HCC: age > 50 years (HR 1.94, 95%CI [1.16; 3.25], p=0.012); past excessive alcohol intake (HR 1.55, 95%CI [1.02; 2.36], p=0.041); low platelet count (< 100 Giga/ mm3: HR 2.70, 95% CI [1.62; 4.51], p < 0.001; [100; 150] Giga/ mm3: HR 1.87, 95%CI [1.10; 3.18], p=0.021); GGT above the upper limit of normal (HR 1.96, 95%CI [1.11; 3.47], p=0.021); and absence of a sustained virological response during follow-up (HR 3.02, 95%CI [1.67; 5.48], p<0.001). An 11-point risk score was derived from the training cohort and validated in the validation set. Based on this score, the population was stratified into three groups, in which HCC development gradually increased, from 0% to 30.1% % at 5 years for patients with the lowest (≤ 3) and highest (≥ 8) scores (p < 0.001). Using this score, a nomogram was built enabling individualized prediction of HCC occurrence at 1, 3 and 5 years.Conclusions: This HCC score can accurately predict HCC at an individual level in French patients with HCV-cirrhosis.

Furthermore, an increased

  serum level GGT (> ULN) is usually associated with more severe liver disease.This model, which can be easily applied to clinical practice, performed well in terms of discrimination (AUROC for 1-and 3-year predictions was 0.678 [0.555-0.801] and 0.717 [0.661-0.773], respectively, in the training group) in a split derivation sample of patients with HCV-related cirrhosis. Internal validation in the split sample confirmed the accuracy of this score in predicting HCC; the derived nomogram had good calibration, with an accurate correlation between predicted and observed HCC risk (r= 0.91). Moreover, updating of the score value 12 months after inclusion for patients still at risk of HCC was able to predict, with the same discriminatory accuracy, the risk of HCC, demonstrating the evolutive capacity of the score.

Figure 1 :

 1 FIGURES LEGENDS

Figure 2 :

 2 Figure 2: Incidence of HCC according to predictive score:

Figure 3 :

 3 Figure 3: Nomogram for individualized prediction of HCC occurrence at 1, 3 or 5 years. A

  Among 1,671 patients consecutively enrolled between March 2006 and July 2012 in the French ANRS CO12 CirVir cohort, 1,323 patients had HCV-cirrhosis and were HBsAg-seronegative. Secondarily, 243 of them were excluded from analysis due to missing data regarding known predictive factors for

	HCC. Finally, 1,080 patients were analyzed and randomly assigned to training (n=720) and
	validation (n=360) sets (Figure 1).
	Patient characteristics at inclusion were similar in the two groups, except for prothrombin time, which
	was slightly higher in the validation group. Patients were mainly male (64.0%), median age 55.6 years
	[48.9-64.0]. Median body mass index was 25.7 kg/m2. Co-morbidities were frequent, including
	overweight or obesity in 57.8%, diabetes in 18.9% and past excessive alcohol consumption in 31.3%

of cases (median alcohol consumption 80 g/day (IQR 50-100) for 11.5 years (IQR 10-20)). Patients were mainly mono-infected (4.6% of patients with HIV co-infection) by genotype 1 (69.1%). Only 212 (19.6%) of them had SVR at baseline, confirmed at endpoint; overall, at endpoint, 427 of the 1,080 selected patients (39.5%) had SVR, including 215 who achieved SVR during follow-up (Table

  0.555-0.801] and 0.717 [0.661-0.773], respectively, in the training group. Implementation of this score after twelve months of follow-up, taking into account increasing age, new values of platelets and GGT and potential recent SVR, gave an AUROC for the 1 and 3-year predictions of 0.678 [0.574-0.783] and 0.727 [0.655-0.800], respectively, in this subset of patients still at risk of HCC.

ACKNOWLEDGMENTS

Funding/Support: This study was sponsored by the ANRS (France REcherche Nord & Sud Sida-hiv Hépatites: FRENSH).

Role of the sponsor:

The funding sponsor had no role in the design or conducting of the study: collection, management, analysis, interpretation of data, nor preparation, review or approval of the manuscript. Funding/Support: This study was sponsored by the ANRS (France REcherche Nord & sud Sida-hiv Hépatites: FRENSH). Author contributions: Professors Ganne-Carrié and Roudot-Thoraval had full access to all data in the study and take responsibility for the integrity of data and the accuracy of data analysis. Alric consults for and received grants from Bristol-Myers Squibb, MSD, and Gilead. He received grants from Roche and Janssen. The funding sponsor had no role in the design or conducting of the study; collection, management, analysis, interpretation of data, nor preparation, review or approval of the manuscript.


Gabriel S S Leal

Wided Guédria

Hervé Panetto

Erik Proper
email: erik.proper@list.lu

Mario Le- Zoche
email: mario.lezoche@univ-lorraine.fr

Using formal measures to improve maturity model assessment for conceptual interoperability

Keywords: Networked Enterprise, Maturity Model, Enterprise Interoperability Assessment, Conceptual Interoperability, Formal Measures

To handle challenges such as globalization, new technologies and fast-changing environments, enterprises are progressively collaborating with others and becoming part of a Networked. In this context, Enterprise Interoperability (EI) is a crucial requirement that needs to be respected by enterprises when starting a collaborative relationship. As soon as this requirement is not achieved, EI becomes a problem that must be solved. To avoid these problems and consequently, take corrective actions on time, enterprises need to predict and solve potential problems before they occur. The Maturity Model for Enterprise Interoperability (MMEI) was proposed to assess the interoperability potential of an enterprise as well as to help enterprises evaluating the suitability of partners in an interoperability context. However, this method has some inconveniences such as the lack of formal definitions specifying the boundaries between each maturity level. Hence the objective of this paper is to formalize the MMEI maturity levels boundaries by defining formal measures. Finally, a case study is proposed to validate the defined measures.

Introduction

With the current fast changing environment, enterprises are progressively collaborating with each other and participating to a Networked Enterprise (NE) [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF], to face challenges such as globalisation, new technologies, financial crisis, new markets, etc. Considering this NE context, we argue that one of the difficulties enterprises may face is the development of Enterprise Interoperability (EI) [2], [START_REF]ISO: Advanced automation technologies and their applications -Part 1: Framework for enterprise interoperability[END_REF] among their Collaborative Enterprise Systems (CESs) [START_REF] Leal | Towards a comparative analysis of interoperability assessment approaches for collaborative enterprise systems[END_REF]. EI is a crucial requirement having to be verified by enterprises when starting a relationship with others to attain shared goals [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF], [START_REF] Mallek | The application of interoperability requirement specification and verification to collaborative processes[END_REF].

As soon as this requirement is not achieved, interoperability becomes a problem that must be solved [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF], [START_REF] Naudet | Towards a systemic formalisation of interoperability[END_REF]. To deal with this kind of problem, accurate evaluations can be performed to have a clear view of strengths and weaknesses of the considered NE regarding interoperability, at an early stage [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF]. Some surveys and comparisons [START_REF] Leal | Towards a comparative analysis of interoperability assessment approaches for collaborative enterprise systems[END_REF], [START_REF] Ford | Interoperability Measurement[END_REF], [START_REF] Panetto | Towards a Classification Framework for Interoperability of Enterprise Applications[END_REF], [START_REF] Guedria | Interoperability maturity modelssurvey and comparison[END_REF], have been performed to evaluate existing interoperability assessment methods. Among these evaluation methods, the Maturity Model for Enterprise Interoperability (MMEI) [START_REF] Guedria | Maturity model for enterprise interoperability[END_REF], [START_REF] Guedria | Maturity model as decision support for enterprise interoperability, On the Move to Meaningful Internet Systems[END_REF] proposes five maturity levels, describing the stages through which systems should evolve to reach higher completeness in the realisation of a given objective. It covers the three main interoperability aspects which are: Conceptual, Technical and Organizational interoperability [START_REF]ISO: Advanced automation technologies and their applications -Part 1: Framework for enterprise interoperability[END_REF]. MMEI was mainly conceived to assess the potentiality of an enterprise (or a system) to be interoperable with a possible future partner whose identity is not known at the moment of evaluation.

Although the MMEI maturity levels are well structured, their definitions are based on qualitative measures i.e. the levels are subjective and the evaluation depends on the expertise of the assessors. This kind of measure has some inconveniences such as the lack of formal definitions specifying the boundaries between each maturity level and requires a very high level of expertise to apply these models in an industrial context [START_REF] Panetto | New Perspectives for the Future Interoperable Enterprise Systems[END_REF]. A possibility raised by [START_REF] Leal | Towards a comparative analysis of interoperability assessment approaches for collaborative enterprise systems[END_REF] to formalise the boundaries between each maturity level, is the use of quantitative measures (numeric values characterising the interoperations between CESs). Indeed, quantitative methods such as [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF], [START_REF] Ford | The Interoperability Score[END_REF], [START_REF] Barut | Measuring supply chain coupling: an information system perspective[END_REF], [START_REF]Guidelines and Best Practices for Applying the ATHENA Interoperability Framework to Support SME Participation in Digital Ecosystems[END_REF], are capable of formalising and quantifying interoperability between known systems. However, they are not prepared and/or they do not have coherent value scales to be used with maturity models. Hence, the objective of this paper is to improve the MMEI interoperability evaluation by formalising its maturity levels boundaries. This will allow quantifying and qualifying the degree of interoperability between heterogeneous enterprises that need to participate in a NE. In this paper, we will focus only on the conceptual interoperability aspect. The technical and organisational aspects are out of the scope and will be investigated in future work. The formalisation of the MMEI conceptual maturity levels will be done by defining formal measures based on the quantitative methods. It will allow us to establish the transition between each maturity level by specifying thresholds (numeric values) for levels' boundaries. The proposed improvement is essential and will serve as one more step towards proposing a new approach for assessing enterprise interoperability within a NE, using both qualitative and quantitative measures. The rest of the paper is organised as follow -Section 2 presents the relevant related work. It is followed by Section 3 where the formal measures are proposed and the levels' boundaries are established. Section 4 illustrates a real case study based on an active NE in the field of marketing and communication in Luxembourg. The conclusion and future work are given in Section 5.

Related work

This section gives an overview of the Networked Enterprise Meta-Model (NEMO) [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF], highlighting the core concepts of NE and interoperability, as well as, relationships between them. The different classifications and properties of enterprise interoperabil-ity assessment methods are also presented. Furthermore, the MMEI and its five maturity levels, as well as some formal measures proposed to assess the conceptual interoperability aspect, are brought forward.

Networked Enterprise and Enterprise Interoperability

NEMO [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF] aims at providing a common understanding of the NE and interoperability concepts, based on a systemic approach. It defines a NE as: "a system composed of at least two autonomous systems (enterprises) that collaborate during a period of time to reach a shared objective". According to [START_REF] Chen | GRAI integrated methodology and its mapping onto generic enterprise reference architecture and methodology[END_REF] and [START_REF] Naudet | Extending the Ontology of Enterprise Interoperability (OoEI) using Enterprise-As-system Concepts[END_REF] enterprise systems are all sub-systems of an enterprise (e.g. Information systems, decisional systems, physical systems, etc.). Taking into account this view, [START_REF] Leal | Towards a comparative analysis of interoperability assessment approaches for collaborative enterprise systems[END_REF] adopt the term Collaborative Enterprise System (CES) in order to represent the enterprise systems that collaborate with systems from other enterprises within the NE. Considering these perspectives, NEMO describes two views of interoperability: as a requirement that needs to be met when there is a need for at least two CESs to work together and as a problem when this requirement is not fulfilled. To describe the interoperability concepts within a NE, NEMO is based on the interoperability dimensions [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF], [START_REF]ISO: Advanced automation technologies and their applications -Part 1: Framework for enterprise interoperability[END_REF]. Here, we present the three most important concepts that will be considered in the metrics proposition in section 3. The first one is the interoperability concerns representing the areas concerned by interoperability in an enterprise (business, process, service and data). The second, is conceptual interoperability aspect dealing with knowledge and information sharing among systems. Finally, the conceptual barriers concerning with the syntactic and semantic incompatibilities of information to be exchanged between systems. This kind of barrier can be related to enterprise models and the capacity of knowledge and semantic representation. More details about interoperability dimensions and other concepts can be found on [START_REF] Leal | Towards a Meta-Model for Networked Enterprise. 21st international conference on exploring modelling methods for systems analysis and design[END_REF], [START_REF]ISO: Advanced automation technologies and their applications -Part 1: Framework for enterprise interoperability[END_REF].

Enterprise Interoperability Assessment

In order to support enterprises to better interoperate with their partners within a NE, the interoperability between their CESs requires being assessed and continuously improved. According to [START_REF] Leal | Towards a comparative analysis of interoperability assessment approaches for collaborative enterprise systems[END_REF], [START_REF] Guedria | Maturity model for enterprise interoperability[END_REF], the interoperability assessment methods can be classified based on the criteria depicted on Table 1. It is worth noting that interoperability is a non-bidirectional property [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF]. It means that: Given two entities A and B and measuring their interoperability level I(x,y) it is structurally coherent to find 𝐼(𝐴,𝐵)≠ 𝐼(𝐵,𝐴). This structural property doesn't impact the evaluated methods because of its internal feature but it explains the behavioural aspects of the approached property concepts [START_REF] Leal | Towards a comparative analysis of interoperability assessment approaches for collaborative enterprise systems[END_REF]. The following sections present the MMEI (a qualitative method) and quantitative methods.

Maturity Model for Enterprise Interoperability (MMEI)

MMEI has two primary purposes: (1) Define a common framework for assessing and measuring potential interoperability maturity, providing information for how far along an enterprise is regarding targeted maturity levels.

(2) Provide information about 'best practices' that allow enterprises to improve their interoperability potential [START_REF] Guedria | Maturity model for enterprise interoperability[END_REF]. MMEI is a levelling method using qualitative measures and following a white box approach. It is mainly used when interoperation partners are unknown. MMEI defines five enterprise interoperability maturity levels: Unprepared, Defined, Aligned, Organized and Adaptive. Each maturity level is an instantiation of the main elements of an interoperability aspect with an evolution of the elements regarding the evolution of the level. When considering the conceptual interoperability aspects, these elements are: data models, service models, process models, business models, enterprise visions, strategies, objectives, policies, etc. Aligned to the enterprise maturity levels, MMEI identify five conceptual maturity levels that are: Incomplete, Modelled, Adhered, Mapped and Accommodate [START_REF] Guédria | A Maturity Model for Enterprise Interoperability[END_REF].

According to [START_REF] Guedria | Maturity model as decision support for enterprise interoperability, On the Move to Meaningful Internet Systems[END_REF], in order to verify if two enterprises are interoperable, the concerned enterprises must assess their potential interoperability individually, using the MMEI model and then compare the obtained results. Having their maturity levels and identifying which criteria were not achieved from both sides, enterprises can foresee potential interoperability problems related to those non-achieved criteria.

Quantitative methods for interoperability assessment

Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques [START_REF] Babbie | The practice of social research[END_REF]. Considering the enterprise interoperability domain, we identified the following methods dealing with the interoperability assessment: Based on a mathematical formalisation of the semantic relationship, Yahia et al. [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF] proposed two measures, the maximal potential and the minimum effective interoperability. The iscore [START_REF] Ford | The Interoperability Score[END_REF] intend to measure interoperability of complex networks using operational thread as its foundation and provides a single number measure of how well the systems interoperate along the thread. Barut et al. [START_REF] Barut | Measuring supply chain coupling: an information system perspective[END_REF] propose a single 2-tuple index that encompasses both the depth of the information exchanged and used within the network as well as the richness and the amount of the information exchanged and used. The compatibility matrix [START_REF]Guidelines and Best Practices for Applying the ATHENA Interoperability Framework to Support SME Participation in Digital Ecosystems[END_REF] provides a matrix with 24 interoperability areas where the value "1" is attributed when an incompatibility is found. The degree of compatibility is given by the sum of incompatibilities found, where "0" means higher compatibility and "24" poorest compatibility between the considered systems.

Improving MMEI with formal measures

In this section, our objective is to deal with the lack of formal definitions specifying the boundaries between each conceptual maturity level. First, we present the selected quantitative methods that will be used as basis to formulate the formal measures as well as the identified links between MMEI and those methods. Furthermore, the formal measures and the maturity levels' boundaries are presented.

Linking MMEI and the selected quantitative methods

Among the identified methods in section 2.4, we chose the approaches proposed by Yahia et al. [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF] and Barut et al. [START_REF] Barut | Measuring supply chain coupling: an information system perspective[END_REF] because they deal especially with the conceptual interoperability aspect. Moreover, both methods use a white box approach (where systems' inputs-outputs as well as their elements and structures are known) which facilitate the identification of problems in specific parts of a system. MMEI and the two selected approaches [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF], [START_REF] Barut | Measuring supply chain coupling: an information system perspective[END_REF], consider that interoperability is mainly concerned by the relationships and interactions between systems.

When dealing with the conceptual interoperability assessment, the Conceptual Models are the objects of evaluation. These models are composed by Semantic blocks that represent independent piece of knowledge containing their own minimal semantics. A Semantic Block is composed by Concepts which can be "Lexical" or "Non-Lexical" concepts [START_REF] Lezoche | Conceptualising and structuring semantics in Cooperative Enterprise Information Systems Models[END_REF]. Fig. 1 shows the links between MMEI concepts and the metamodel of semantic block structure [START_REF] Lezoche | Conceptualising and structuring semantics in Cooperative Enterprise Information Systems Models[END_REF] used by Yahia et al. [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF] to determine their proposed measures. The specific MMEI elements are coloured in grey and the metamodel elements are coloured in white. The "Conceptual Model" is coloured in black as it's an element used from both approaches. Considering the studied measures to assess the conceptual interoperability, Barut et al. [START_REF] Barut | Measuring supply chain coupling: an information system perspective[END_REF], provides two index: (1) the Information Extent describes how deep into the network that information is used. It can be compare with the potential interoperability index (ν) proposed by [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF], which represents the maximal number of semantic relationships existing into the considered network. (2) The Information Intensity describes the richness and amount of the information used. It can be compared with the effective interoperability index (ε) from [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF], which verifies the number of mandatory concepts that are instantiated. Here, a set of mandatory concept (MC) represents all the necessary and sufficient elements which make the conceptual model semantically coherent and understandable. On the contrary, a non-mandatory concepts (NMC) correspond to the non-mandatory roles and are only enriching the semantics of the CESs conceptual models.

Defining maturity levels' boundaries

Considering the five conceptual maturity levels and the index defined by [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF], [START_REF] Barut | Measuring supply chain coupling: an information system perspective[END_REF], we propose the boundary of each maturity level. These equations will be used to improve the step 4 (Assessment) from the MMEI methodology [START_REF] Guedria | Maturity model for enterprise interoperability[END_REF]. Before presenting the numerical values and the boundaries descriptions, we present the linguistic value' ranges and notations that we adopt to characterize if a level is achieved or not. It is based on [START_REF] Guedria | Maturity model for enterprise interoperability[END_REF] and [START_REF] Rout | SPICE in Retrospect: Developing a Standard for Process Assessment[END_REF] notations. The four defined values and their boundaries are: "Not Achieved (NA) (0 ≤ x ≤ 15)", "Partially Achieved (PA) (15 < x ≤ 50)", "Largely Achieved (LA) (50 < x ≤ 85)", "Fully Achieved (FA) (85 < x ≤ 100). Based on that, we define the following equations:

𝐶𝐴(%) = 𝐶𝐸𝑆𝑐 + 𝐶𝐸𝑆𝑎 𝐶𝐸𝑆𝑐 𝑒 + 𝐶𝐸𝑆𝑎 𝑒 (1)
Where CA(%) is the ratio of the number of CESs' concepts and attributes identified and modelled over the total expected number of CESs' concepts and attributes. CESc is the number of modelled concepts from the concerned CES . CESa is the number of modelled attributes from CES. 𝐶𝐸𝑆𝑐 𝑒 is the expected total number of modelled concepts from CES . 𝐶𝐸𝑆𝑎 𝑒 is the total expected number of modelled attributes from CES .

𝐶𝐿𝑁𝐿 (%) = 𝐶𝐿 +𝐶𝑁𝐿 𝐶𝑇 𝑒

(2)

Where CLNL (%) is the ratio of the sum of Lexical and Non-Lexical Concepts from the considered CES over the total expected number of concepts from the CES. CL is the number of Lexical concepts identified from CESs. CNL is the number of Non-Lexical concepts identified from CES. 𝐶𝑇 𝑒 is the expected total number of concepts from the considered CESs (𝐶𝑇 𝑒 = 𝐶𝐸𝑆𝑐 𝑒 + 𝐶𝐸𝑆𝑎 𝑒 ).

𝐶𝑀𝑁𝑀 (%) = 𝑀𝐶 +𝑁𝑀𝐶 𝐶𝑇 𝑒 (3)
Where CMNM (%) is the ratio of the sum of MC and NMC from both considered CESs over the total expected number of concepts from the considered CESs. The following equations are the same from Yahia et al. [START_REF] Yahia | Formal measures for semantic interoperability assessment in cooperative enterprise information systems[END_REF]. They represent the maximal potential interoperability (how many semantic relationships can be established within the considered network) and minimal effectiveness interoperability (the interoperability's quality).

Maximal potential = (𝑣

1→2 = |𝑅 𝐶 2 | |𝑅 𝐶𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 2 | , ε 1→2 = |𝑅 𝐶 2e | |𝑅 𝐶 2 | ) (4) Minimal effectiveness = ( v 1→2 𝑒 = |𝑅 𝐶 2e | |𝑅 𝐶𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 2 | , ε 1→2 𝑒 = 100% ) (5)
Where, |𝑅 𝐶 2 | is the set of the retrieved semantic relationships.

|𝑅 𝐶 2e | is a subset of |𝑅 𝐶 2 | that contains only MC. |𝑅 𝐶𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 2
| represents the set of the expected semantic relationships needed to ensure a full semantic interoperation.

Further, Table 2 describes the levels' boundaries and what need to be done to reach each one of them.

Table 2. Conceptual maturity levels and their boundaries.

Level -Boundaries description

Metric Level 1 -Modelled: In order to reach this maturity level the considered conceptual models need to be modelled. This is achieved by modelling the concepts and attributes from the concerned CES and achieving CA = FA.

(1)

Level 2 -Adhered: The conceptual model need to be fully modelled to achieve this level of maturity. The goal is reached using the standards and the translation of the Fact-oriented modelling. This is achieved by identifying and modelling the lexical and non-lexical concepts and their attributes from the considered CES i.e. CLNL = FA and the entire mandatory and nonmandatory concepts and their attributes from CES i.e. CMNM = FA.

(2), (3) Level 3 -Mapped. This level represents the capability to perform Meta modelling for multiple model mappings. Identifying and classifying all semantic relationships from the considered semantic blocks within the conceptual models tackle this issue. All concepts from the CESs must be identified and have all their potential semantics relationships recognized as well. This can be verified if the Maximal Potential Interoperability (MPI) is achieved i.e. (ν) = (ε) = FA.

(4) Level 4 -Accommodated. In order to reach this maturity level the business, processes, services and data models must be adaptive. That is, they might be capable to dynamically adjust and accommodate 'on the fly'. This can be verified if (ε e ) = 100% and (ν) = (ε) = (ν e ) = FA. It worth noting that when (ν) and (ε) are equal to 100%, the CES1 is fully interoperable to CES2.

(4), [START_REF] Mallek | The application of interoperability requirement specification and verification to collaborative processes[END_REF]

Case Study

This section illustrates the evaluation of the proposed metrics using a real case study.

The objective is to present the improvements brought to MMEI by implementing the formal measures and to prove that the metrics cover the lack of levels' boundaries formalization. The case study is based on The Factory Group (TFG) [START_REF]The Factory Group[END_REF], an active NE in the field of marketing and communication in Luxembourg. TFG brings together five independent companies linked by their capital structure or by joint venture agreement. In this case study, we consider two enterprises from TFG: Concept Factory [24] and Exxus [25]. Following the MMEI methodology assessment [START_REF] Guedria | Maturity model for enterprise interoperability[END_REF], [START_REF] Guedria | Maturity model as decision support for enterprise interoperability, On the Move to Meaningful Internet Systems[END_REF], the first step is to define the assessment scope which is to evaluate the interoperability between Exxus and Concept Factory, considering the collaborative process responsible for planning future collaborative tasks. The information used to define the scenario was gathered through interviews and analysis of provided documents by the different enterprises. The selected interviewees are members of the board of directors of each considered enterprise. Based on the gathered information, we have first applied the MMEI criteria assessment in each concerned enterprises individually and we have crossed the obtained results from each one of them in order to identify which potential incompatibilities may appear when the interoperation starts. One of the main points in this case study is that according to the gathered information, the collaborative process responsible for planning future collaborative tasks is not modelled. This process was introduced when the new responsible was chosen (the Concept Factory Account Director). This leads to work on the tacit knowledge [START_REF] Lezoche | Conceptualising and structuring semantics in Cooperative Enterprise Information Systems Models[END_REF]. In the specific case study the knowledge is trapped in employees mind. The assessors, working to structure and to understand the level of knowledge possessed, realised that despite the process was not modelled in both enterprises, most employees knows what need to be done i.e. which steps they need to take to realize the process. Table 3 shows some of the obtained results for each enterprise, considering the first MMEI maturity level (Modelled). Even though the process are not modelled in both enterprises, the assessors considered that both enterprises largely achieved the level 1. The assessment was based on the tacit knowledge presented by the interviewees and their perception considering the day-of-day from employees. However, the linguistic values assigned to those criteria are subjective, as it depends of the expertise and considerations of the assessors. Another inconvenience related to the dependence of the assessor's expertise, is that results may vary from among assessors. Using the same gathered information, we use the proposed measures, in the assessment step, to verify if the concepts and attributes from the processes conceptual models are really identified. The obtained results are the following: CA ConceptFactory = 40% (PA) and CA Exxus = 0% (NA). The assessment takes in count mainly the available conceptual models from both enterprises. Concept Factory has some data models that are used as basis to gather the needed information in order to plan the weekly tasks but the other process activities are not modelled nor documented. Exxus does not have any available conceptual model concerning this kind of process. Having this numeric values, allow assessor to identify what need to be done to achieve a given maturity level. For example, in this case study, Concept Factory need to model the remaining 60% concepts and attributes related to the assessed process and Exxus need to model the entire process. A possible solution could be both enterprises realize the process modelling together, taking into account what the "Concept Factory" already has.

Conclusion and Future Work

In this paper, we have proposed an improvement of the Maturity Model for Enterprise Interoperability by defining formal measures to identify the maturity levels boundaries. It has been asserted that despite being well structured, the boundaries of MMEI maturity levels lack formalization. Although, it is clear which requirements are need-ed to reach a given maturity level, the assessment depends on subjective criteria. Formal measures have been identified as a possibility to fulfil this gap. Furthermore, a brief analysis considering the MMEI conceptual aspect and quantitative methods was done. Based on the related work, we proposed to improve the MMEI conceptual interoperability assessment by establishing formal measures in order to define each maturity level boundaries. A real case study of an active NE in Luxembourg has been studied to validate the proposed approaches, by illustrating the interoperability evaluation between two enterprises. As future work, we intend to improve MMEI technical and organisational aspects, by applying quantitative evaluation methods. Furthermore, we intend to develop an Interoperability Assessment Approach for Networked Enterprise context. This approach will be part of a Framework for the Networked Enterprise Interoperability that will serve as basis to the development of a decision-support system for preventing and solving interoperability problems in the NE context.

Fig. 1 .

 1 Fig. 1. Linking concepts from MMEI and Yahia et al. [13] approach.

Table 1 .

 1 Interoperability assessment methods classification

		Criteria		Classification
		Structure	Levelling		Non-Levelling
	Method	Used measure	Qualitative		Qualitative
	properties	Used approach	White Box		Black Box
		Type of interop. assessment	Known partner	Unknown partner
		Interop. Aspects	Conceptual	Technical	Organisational

Table 3 .

 3 Simplified view of MMEI raiting. "L" stands for Level. "NA" stands for Not Achieved, "PA" for Partially Achieved, "LA" for Largely Achieved and "FA" for Fully Achieved.

	L	Activities to evaluate	Concept Factory	Exxus
			NA PA LA FA NA PA LA FA
	1	Process models are explicitly defined and documented (objective evaluation)	X	X
	1	Process models are explicitly defined and documented (assessors perception)	X	X

Acknowledgements

This work has been conducted in the context of the PLATINE project (PLAnning Transformation Interoperability in Networked Enterprises), financed by the national fund of research of the Grand Duchy of Luxembourg (FNR), under the grant C14/IS/8329172.