7th IAS Conference on HIV Pathogenesis, Treatment and Prevention (IAS 2013)


TUAB0104 - Oral Abstract

Prediction of survival and decompensations of cirrhosis among HIV/HCV-co-infected patients: a comparison of liver stiffness versus liver biopsy

Presented by Juan Macías (Spain).

J. Macías1, Á. Camacho2, M.Á. von Wichmann3, L.F. López Cortés4, E. Ortega5, C. Tural6, M.J. Ríos7, D. Merino8, F. Téllez9, M. Márquez10, M. Mancebo1, A. Rivero2, J.A. Iribarren3, A. Torres-Cornejo4, P. Rubio5, J.A. Pineda1

1Hospital Universitario de Valme, Seville, Spain, 2Hospital Universitario Reina Sofía, Cordoba, Spain, 3Hospital de Donostia, San Sebastian, Spain, 4Hospital Universitario Virgen del Rocío, Seville, Spain, 5Hospital General Universitario de Valencia, Valencia, Spain, 6University Hospital Germans Trias I Pujol, Barcelona, Spain, 7Hospital Universitario Virgen Macarena, Seville, Spain, 8Complejo Hospitalario de Huelva, Huelva, Spain, 9Hospital de La Línea de la Concepción, La Linea de la Concepcion, Spain, 10Hospital Universitario Virgen de la Victoria, Malaga, Spain

Background: Survival in HCV infection depends on the fibrosis stage. Liver stiffness measurement (LSM) allows non-invasive diagnosis of fibrosis and also correlates with portal pressure. Thus, LSM could replace liver biopsy (LB) in assessing the risk of death and liver events in HIV/HCV coinfection. Because of these, we aimed to compare the prognostic performance of LB with that of LSM to predict survival and liver decompensations among HIV/HCV-coinfected patients.
Methods: 297 HIV/HCV-coinfected patients, with LB and LSM separated by ≤12 months, prospectively followed (2005-2011) were included in this cohort study. The baseline date was half the period of time between LB and LSM. LB was staged following the Scheuer's score. LSM was obtained by hepatic transient elastometry. Mortality from any cause and incidence of the first liver decompensation were estimated. The integrated discrimination improvement (IDI) was computed to compare the ability of survival models to predict outcomes.
Results: 229 (77%) patients were men. Median (IQR) follow-up was 5 (4.2-5.4) years. 275 (93%) were on antiretroviral therapy at baseline. Median (IQR) CD4 cell count was 514 (352-693) cells/µL, and 233 (79%) individuals showed undetectable plasma HIV RNA at baseline. 26 (8.8%) patients were lost to follow-up. Overall mortality rate was 1.56 (95%CI: 1.02-2.40) per 100 person-years. The adjusted hazard ratio [AHR (95% confidence interval, 95%CI)] of baseline fibrosis (per stage of fibrosis) was 1.52 (1.08-2.15, p=0.017) and of LSM (per 5 KPa increase) 1.28 (1.12-1.46, p< 0.001). Assessment of IDI indicated that LMS-including models yielded a performance 3.9% better than the LB-based models (p=0.072). The liver decompensation rate was 1.59 (95%CI: 1.03-2.43) decompensations per 100 person-years. For the prediction of liver decompensations, the AHR (95%CI) of baseline fibrosis by LB (per stage of fibrosis) was 1.67 (1.15-2.43, p=0.007) and of LSM (per 5 KPa increase) 1.37 (1.21-1.54, p< 0.001). Evaluation of IDI showed that LMS-based models yielded a performance 8.4% better than the LB-based models (p=0.045).
Conclusions: LSM-based prediction achieves a similar yield than LB-based models to predict overall mortality in HIV/HCV-coinfected patients and the former could predict better liver decompensations. LSM may replace LB as prognostic tool in this setting.

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