FIB-4 Cutoffs for Prediction of Liver-related Events in HIV/HCV CoinfectionLeire Pérez-Latorre1, Juan Berenguer1, Marisa Montes2, Miguel A Von Wichmann3, Manel Crespo4, Marta Montero5, Carmen Quereda6, María J Téllez7, José M Bellón1, Juan González-García2
1Hospital General Universitario Gregorio Marañón, Madrid, Spain. 2Hospital Universitario La Paz, Madrid, Spain. 3Hospital Donostia, San Sebastián, Spain. 4Complexo Hospitalario Universitario de Vigo, Vigo. 5Hospital Universitario La Fe, Valencia, Spain. 6Hospital Universitario Ramón y Cajal, Madrid, Spain. 7Hospital Clínico San Carlos, Madrid, Spain.Funding: Fondo de Investigacion de Sanidad en España (FIS) (Refs. EC07/90734, PI11/01556, and EC11/241) and by Red de Investigación en SIDA (AIDS Research Network) (RIS) Ref RD16/0025/0017 project as part of the Plan Nacional R+D+I and cofinanced by ISCIII – Subdirección General de Evaluación y el Fondo Europeo de Desarrollo Regional (FEDER).
CROI 2017Poster# 533
Conclusions1) A FIB-4 of 1 was the best cutoff for separating risk populations. Patients with a FIB-4 <1 had a 97% probability of
remaining free from LRE after a median follow-up of 5 years, and for each unit increase in FIB-4 above the 1 cutoff, the hazard of LRE increased 1.29.
2) Our findings are of relevance for both clinical practice and research because they suggest that FIB-4 is an easy an accurate method to stratify the risk of LRE in HIV/HCV-coinfected patients.
The GeSIDA 3603 Study Group: Hospital General Universitario Gregorio Marañón, Madrid: A Carrero, P Miralles, JC López, F Parras, B Padilla, T Aldamiz-Echevarría, F Tejerina, C Díez, L Pérez-Latorre, I Gutiérrez, M Ramírez, S Carretero, C Fanciulli, JM Bellón, and J Berenguer. Hospital Universitario La Paz, Madrid: E Rodríguez-Castellano, J Alvarez-Pellicer, JR Arribas, ML Montes, I Bernardino, JF Pascual, F Zamora, V Hontañón, JM Peña, F Arnalich, M Díaz, J González-García. Hospital Donostia, San Sebastián: MJ Bustinduy, JA Iribarren, F Rodríguez-Arrondo, MA Von-Wichmann. Hospital Universitari La Fe, Valencia: M Montero, M Blanes, S Cuellar, J Lacruz, M Salavert, J López-Aldeguer. Hospital Clinic, Barcelona: P Callau, JM Miró, JM Gatell, J Mallolas. Hospital Clínico Universitario, Valencia: A Ferrer, MJ Galindo. Hospital Universitari Vall d'Hebron, Barcelona: E Van den Eynde, M Pérez, E Ribera, M Crespo. Hospital Clínico San Carlos, Madrid: J Vergas, MJ Téllez. Hospital Universitario Ramón y Cajal, Madrid: JL Casado, F Dronda, A Moreno, MJ Pérez-Elías, MA Sanfrutos, S Moreno, C Quereda. Hospital Universitari Germans Trias i Pujol, Badalona: A Jou, C Tural. Hospital Universitario Príncipe de Asturias, Alcalá de Henares: A Arranz, E Casas, J de Miguel, S Schroeder, J Sanz. Hospital Universitario de Móstoles, Móstoles: E Condés, C Barros. Hospital Universitario de La Princesa, Madrid: J Sanz, I Santos. Hospital Universitario 12 de Octubre, Madrid: A Hernando, V Rodríguez, R Rubio, F Pulido. Hospital de la Santa Creu i Sant Pau, Barcelona: P Domingo, JM Guardiola. Hospital General Universitario, Valencia: L Ortiz, E Ortega. Hospital Universitario Severo Ochoa, Leganés: R Torres, M Cervero, JJ Jusdado. Hospital General Universitario de Guadalajara, Guadalajara: M Rodríguez-Zapata. Hospital Universitario de Getafe, Getafe: G Pérez, G Gaspar. Fundación SEIMC-GESIDA, Madrid: M Yllescas, P Crespo, E Aznar, H Esteban
CorrespondenceJ Berenguer - [email protected]
Background and Aims• FIB-4, a non-commercial index that is easily applied using routinely
collected data, is better than liver biopsy when assessing the prognosis of HIV/HCV-coinfected patients with compensated liver disease*.
• However, no validated prediction model based on FIB-4 has been developed for liver-related events (LRE) in patients with chronic hepatitis C.
• We designed this study to define clinically useful FIB-4 cut-off points for prediction of LRE in HIV/HCV-coinfected patients with compensated liver disease.
1. Berenguer J, et al. Clin Infect Dis 2015; 60: 950-958
MethodsPatients • Patients from the GESIDA 3603 cohort composed of patients treated with
IFN+RBV between 2000 and 2008 at 19 institutions in Spain• We excluded those with SVR or EOT (relapsers) during FU because the
natural history of hepatitis C is modified in both responders and relapsers*Outcomes • The main outcome was LRE (decompensation or hepatocellular carcinoma,
whichever occurred first)
Statistics • We randomly allocated patients to an estimation cohort (EC) (two-thirds) and a validation cohort (VC) (one-third).
• To identify a FIB-4 cut-off to separate risk populations, we decided a priori that it would be preferable to identify patients who would not develop LRE.
• To estimate the hazard of LRE for FIB-4 values above the cut-off, we first assessed the assumption of linearity between FIB-4 and the proportion of LRE and then assessed the hazard of LRE per different FIB-4 values above the cut-off using the Fine and Gray proportional hazards model, considering death as a competing risk.
*Berenguer J, et al. J Hepatol 2013;58:1104-1112.
Patients characteristics & outcomesVariable Estimation cohort
(N=422)Validation cohort
(N=235)Total
(N=675)
Male sex – n (%) 325 (77.0) 182 (77.4) 507 (77.2)Age (yrs) – median (IQR) 40.3 (37.1 – 43.6) 40.7 (37.2 – 43.8) 40.5 (37.1 – 43.7)HIV-acquired by IDU – n (%) 339 (80.9) 194 (82.9) 533 (81.6)CDC category C – n (%) 106 (25.3) 57 (24.6) 163 (25.0)cART – n (%) 363 (86.0) 195 (83.0) 558 (84.9)HIV-RNA <50 copies/mL – n (%) 274 (65.2) 144 (61.5) 418 (63.9)CD4+ cells/mm3 – median (IQR) 514 (362 – 711) 475 (353 – 701) 500 (360 – 706)HCV Genotype 1 – n (%) 261 (61.8) 152 (64.7) 413 (62.9)FIB-4 value – median (IQR) 1.86 (1.25 – 3.24) 1.99 (1.29 – 3.99) 1.95 (1.26 – 3.32)Follow-up, years – median (IQR) 5.6 (3.7 – 7.1) 5.2 (3.1 – 6.9) 5.4 (3.5 – 7.0)New AIDS condition – n (%) 15 (3.6) 9 (3.8) 24 (3.7)Liver decompensation – n (%) 58 (13.7) 35 (14.9) 93 (14.2)Hepatocellular carcinoma – n (%) 14 (3.3) 5 (2.1) 19 (2.9)Liver-related event – n (%) 74 (17.5) 43 (18.3) 117 (17.8)Liver transplantation – n (%) 9 (2.1) 4 (1.7) 13 (2.0)Death – n (%) 41 (9.7) 29 (12.3) 70 (10.7)
Liver-related 27 (65.9) 19 (65.5) 46 (65.7)Non-Liver-non-aids related 12 (29.3) 9 (31.0) 21 (30.0)Aids-related 2 (4.9) 1 (3.4) 3 (4.3)
From the 1622 patients in the GESIDA 3603 database, we excluded 561 patients with SVR, 214 patients with EOT during FU, and 190 without baseline FIB-4. The final cohort included 657 patients.
AUROCs of FIB-4 for prediction of LRE
The best cutoff value of FIB-4 to rule out LRE according to ROC curves was 1
To identify a threshold value of FIB-4 to separate different risk populations. it was a priori considered that it would be preferable to identify patients who would not develop LRE.
Ability of FIB-4 to predict LREParameters of validity at various cut-off points
of FIB-4 for prediction of LRE
Likelihood Predictive ValuesRatios for SAMPLE Prevalence
Youden ------------- ---------------------CUT-OFF SEN(%) SPE(%) Eff(%) J(%) LR+ 1/LR- PPV(%) NPV-(%)
---------- ------ ------ ------ ------ ------ ------ --------- --------->= 1.0 97.3 17.8 31.8 15.1 1.18 6.59 20.11 96.88>= 1.5 89.2 42.2 50.5 31.4 1.54 3.91 24.72 94.84>= 2.0 81.1 59.8 63.5 40.9 2.02 3.16 30.00 93.69>= 2.5 68.9 72.4 71.8 41.3 2.50 2.33 34.69 91.64>= 3.0 63.5 78.7 76.1 42.2 2.99 2.16 38.84 91.03>= 3.5 51.4 84.5 78.7 35.8 3.31 1.74 41.30 89.09>= 4.0 43.2 88.2 80.3 31.5 3.67 1.55 43.84 87.97>= 4.5 41.9 90.5 82.0 32.4 4.42 1.56 48.44 87.99>= 5.0 33.8 93.1 82.7 26.9 4.90 1.41 51.02 86.86>= 5.5 21.6 94.3 81.5 15.9 3.76 1.20 44.44 84.97>= 6.0 17.6 95.7 82.0 13.3 4.08 1.16 46.43 84.52----------------------------------------------------------------------------SAMPLE prevalence = 17.536%
Parameters of validity of the FIB-4 cutoff of 1 for the prediction of LRE
Estimation Cohort Validation Cohort Liver-related event Liver-related event FIB-4 No Yes Total FIB-4 No Yes Total < 1 62 2 64 < 1 25 0 25 ≥ 1 286 72 358 ≥ 1 167 43 210
Total 348 74 422 Total 192 43 235 Value (95%CI) Value (95%CI) SEN 97.3 (90.6 – 99.7) SEN 100 (91.8 – 100) SPE 17.8 (13.9 – 22.2) SPE 13.0 (8.61 – 18.6) PPV 20.1 (16.1 – 24.6) PPV 20.5 (15.2 – 26.6) NPV 96.9 (89.2 – 99.) NPV 100 (86.3 – 100) LR+ 1.18 (1.11 – 1.26) LR+ 1.15 (1.09 – 1.21) LR– 0.15 (0.04 – 0.61) LR– 0 (NA)
The probability of not developing LRE after a median follow-up of 5 years for patients with an FIB-4<1 was 96.9% in EC and 100% in VC
Hazard of LRE for FIB-4 values above the 1 cutoff
sHR of LR per unit of FIB-4 above 1
Δ LS sHR 95%CI PPer 1 unit 1.29 1.21 – 3.38 <.001
Above the 1 cutoff, the relationship between FIB-4 and the proportion of LRE was linear
Per 1 increase in FIB-4 above the 1 cutoff, the hazard of LRE increased 29%
Competing-risk regression considering death as the competitive risk
Hazard of LRE according to different FIB-4 cutoffs
FIB-4 sHR 95%CI P
< 1 Ref. − −
1 − <2 3.48 0.80 – 15.2 .098
2 − <3 8.66 2.01 – 37.3 .004
≥ 3 21.42 5.1 – 89.1 <.001
Hazard of liver-related events in the full data set of patients (estimation and validation cohorts). Fine and Gray proportional hazard regression analysis, considering death as the competitive risk.
Cumulative incidence of LREAccording to different FIB-4 cutoffs
Considering death as a competitive risk