BACKGROUND

1. Prognostic value of FIB4 in HIV positive patients of the Icona cohort co-infected or not with HCV. C.Mussini1, P. Lorenzini2, A.De Luca3, M. Puoti4, M. Lichtner5, G. Lapadula6, A. Cozzi-Lepri7 and, A. d’Arminio Monforte8 for the Icona Foundation Study Group. 1 University of Modena and Reggio Emilia; 2. National Institte of Infectious Disease, Rome; 3. University of Siena 4. Niguarda Hospital, Milan; 5. University of Latina, Rome; 6. San Gerardo Hospital, Monza; 7. University College, London 8. University of Milan

2. BACKGROUND • Liver-related death due to HCV, HBV or metabolic complications still remains a main cause of death among patients with HIV infection. • FIB4 is a non-invasive serum fibrosis marker, which has been validated in HCV positive patients. • Aim of the present study is to evaluate the prognostic role of FIB4 at starting cART and during treatment to predict major liver events or liver-related death

3. PATIENTS & METHODS • Retrospective cohort study including all treatment-naive patients initiating ART enrolled in ICONA • with a known HCV serology • negative for HBsAg • with at least an available FIB4 index at cART start and during follow up • FIB4 was calculated as: _Age (years) X AST (U/L)___________ • Platelet count (109/L) X [ALT (U/L)]1/2 • We analyzed FIB4 both as continuous variable and as divided in categories as follows: • FIB4 value >3.25  (as a proxy for cirrhosis), • FIB4 value between 1.45 and 3.25 (in which cirrhosis status is considered as undetermined), • FIB4 value <1.45 (considered as absence of cirrhosis).

4. Time of starting cART was considered as “baseline” and patients were followed to the date of the first major liver event or liver-related death. • Major liver events were defined: • variceal or gastrointestinal bleeding, • ascites,  • hepatic encephalopathy, • other signs of liver de-compensation including hepato-renal syndrome • hepatocellular carcinoma (HCC). • The follow-up was censored at last clinical visit, at the event or at death for causes other than those liver-related.

5. STATISTICAL ANALYSES Incidence rate was calculated as number of major liver events or liver-related death divided by person year follow-up (PYFU). Multivariable Cox regression model was used to determine the association of FIB4 with the risk of major liver events or liver-related death. FIB4 was used both as baseline and time-updated co-variate (analyzing the change from baseline to current FIB4)

6. RESULTS Our analysis included 3,475 subjects who had a known HCV serology, were HBsAg negative and had a FIB4 index at baseline and at least one FIB4 determination during follow up.

7. General characteristics of the study population at cART start (N=3475)

8. Cumulative proportion experiencing a major liver event or liver-related death after cART initiation according to baseline FIB4 (n=3,475; 41 events during 18,662 PYFU) Overall IR 2.2 (1.6-3.0) per 1000 PYFU P at log-rank test<0.001

10. HCV negative subjects

11. HCV positive subjects

13. *Also adjusted for age, sex, mode of transmission, time from diagnosis, CDC stage at diagnosis, calendar year at cART initiation,

14. CONCLUSIONS In HIV-positive individuals, FIB4 at baseline and its modification after cART initiation are predictive of major liver events or liver-associated death independently of infection with HCVand could be used as surrogate markers of severe clinical events FIB4 could be used as a simple marker to prioritize HCV treatments in the HIV+ population

15. ICONA Foundation Study Group BOARD OF DIRECTORS M Moroni (Chair), M Andreoni, G Angarano, A Antinori, A d’Arminio Monforte, F Castelli, R Cauda, G Di Perri, M Galli, R Iardino, G Ippolito, A Lazzarin, CF Perno, F von Schloesser, P Viale SCIENTIFIC SECRETARY A d’Arminio Monforte, A Antinori, A Castagna, F Ceccherini-Silberstein, A Cozzi-Lepri, E Girardi, S Lo Caputo, C Mussini, M Puoti STEERING COMMITTEE M Andreoni, A Ammassari, A Antinori, A d’Arminio Monforte, C Balotta, P Bonfanti, S Bonora, M Borderi, MR Capobianchi, A Castagna, F Ceccherini-Silberstein, A Cingolani, P Cinque, A Cozzi-Lepri, A d’Arminio Monforte, A De Luca, A Di Biagio, E Girardi, N Gianotti, A Gori, G Guaraldi, G Lapadula, M Lichtner, S Lo Caputo, G Madeddu, F Maggiolo, G Marchetti, S Marcotullio, L Monno, C Mussini, M Puoti, E Quiros Roldan, S Rusconi STATISTICAL AND MONITORING TEAM A.Cozzi-Lepri, P. Cicconi, I. Fanti, T. Formenti, L. Galli, P. Lorenzini PARTICIPATING PHYSICIANS AND CENTERS Italy A Giacometti, A Costantini, S Mazzoccato (Ancona); G Angarano, L Monno, C Santoro (Bari); F Maggiolo, C Suardi (Bergamo); P Viale, E Vanino, G Verucchi (Bologna); F Castelli, E Quiros Roldan, C Minardi (Brescia); T Quirino, C Abeli (Busto Arsizio); PE Manconi, P Piano (Cagliari); J Vecchiet, K Falasca (Chieti); L Sighinolfi, D Segala (Ferrara); F Mazzotta, S Lo Caputo (Firenze); G Cassola, C Viscoli, A Alessandrini, R Piscopo, G Mazzarello (Genova); C Mastroianni, V Belvisi (Latina); P Bonfanti, I Caramma (Lecco); A Chiodera, AP Castelli (Macerata); M Galli, A Lazzarin, G Rizzardini, M Puoti, A d’Arminio Monforte, AL Ridolfo, R Piolini, A Castagna, S Salpietro, L Carenzi, MC Moioli, C Tincati, G. Marchetti (Milano); C Mussini, C Puzzolante (Modena); A Gori, G. Lapadula (Monza); N Abrescia, A Chirianni, MG Guida, M Gargiulo (Napoli); F Baldelli, D Francisci (Perugia); G Parruti, T Ursini (Pescara); G Magnani, MA Ursitti (Reggio Emilia); R Cauda, M. Andreoni, A Antinori, V Vullo, A. Cingolani, A d’Avino, L Gallo, E Nicastri, R Acinapura, M Capozzi, R Libertone, G Tebano (Roma); A Cattelan, L Sasset (Rovigo); MS Mura, G Madeddu (Sassari); A De Luca, B Rossetti (Siena); P Caramello, G Di Perri, GC Orofino, S Bonora, M Sciandra (Torino); M Bassetti, A Londero (Udine); G Pellizzer, V Manfrin (Vicenza).