PREDICTION OF SURVIVAL AND DECOMPENSATIONS OF CIRRHOSIS AMONG

HIV/HCV-COINFECTED PATIENTS: A COMPARISON OF LIVER STIFFNESS VERSUS

LIVER BIOPSY

Juan Macías1, Ángela Camacho2, Miguel A. von Wichmann3, Luis F. López-Cortés4, Enrique Ortega5, Cristina Tural6, MªJosé Ríos7, Dolores Merino8, Francisco Téllez9, Juan A. Pineda1.

1Hospital Universitario de Valme, Seville; 2Hospital Universitario Reina Sofía, Cordoba; 3Hospital de Donostia, San Sebastian; 4Hospital Universitario Virgen del Rocío, Seville; Hospital General Universitario de Valencia, Valencia; 6Hospital Universitario Germans Trias I Pujol, Barcelona; 7Hospital Universitario Virgen Macarena, Seville; 8Complejo Hospitalario de Huelva, Huelva; 9Hospital de La Línea de la Concepción, Cadiz. Spain

INTRODUCTION• The survival of individuals with chronic hepatitis C

depends on fibrosis stage.

• Liver biopsy (LB):

• Gold-standard to stage fibrosis.

• Limitations: invasive, sampling and interobserver variability.

• Transient hepatic elastography (TE):

• Reliable non-invasive diagnosis of fibrosis.

• Liver stiffness measurement (LSM) correlates with the portal venous pressure gradient.

• TE could replace LB to assess the risk of death and liver events in HIV/HCV coinfection.

OBJECTIVE

To compare the prognostic performance of LB

with that of LSM to predict survival and liver

decompensations among HIV/HCV-coinfected

patients.

PATIENTS AND METHODS • Retrospective cohort study (2005-2011). • Inclusion criteria:

• HIV infection.• HCV infection: Detectable plasma HCV-RNA at baseline.• LB and TE separated by ≤12 months.

• Baseline: Half the period of time between LB and LSM.

• Statistical analysis: • Primary end-points:

• Death due to any cause.• First decompensation of cirrhosis.

• Secondary end-point: Liver-related death.• Time to event:

• Cox regression models: Overall mortality.• Competing risks regression models: Decompensations.• Comparison of models: Integrated discrimination improvement (IDI) test.

RESULTS (I)Baseline characteristics (n=297)

Characteristic Value

Age¹, years 42 (39-45)

Male gender, n (%) 229 (77)

Injecting drug use, n (%) 253 (85)

Baseline CD4¹, cel/ml 514 (352-693)

HIV-RNA <50 c/ml, n (%) 233 (79)

Antiretroviral therapy, n (%) 275 (93)

AIDS, n (%) 91 (31)

1: Median (IQR)

RESULTS (II)Baseline characteristics (n=297)

Characteristics ValueHCV genotype², n (%)

1 and 4 239 (80)

2 and 3 51 (17.7)

Positive HBsAg, n (%) 6 (2)

Fibrosis stage (LB), n (%)

F0 42 (14)

F1 97 (33)

F2 79 (27)

F3 39 (13)

F4 40 (14)

Liver stiffness measurement¹, KPa 7.6 (5.6-11.6)

Therapy against HCV, n (%) 178 (60)

SVR³, n (%) 68 (38)

1: Median (IQR); 2: Not available in 7 patients; 3: SVR, sustained virological response, applicable to 178 patients who received therapy.

RESULTS (III)Probability of all-cause death

p=0.005 p<0.0001

According to fibrosis stage (LB) According to LSM category

Pro

babi

lity

of s

urvi

val

LSM ≤6 KPaLSM 6.1-8.9 KPaLSM 9-14.6 KPaLSM 14.6-21 KPaLSM ≥21 KPa

Pro

babi

lity

of s

urvi

val

F0F1F2F3F4

Median (IQR) follow-up: 5 (4.2-5.4) years. Lost to follow-up: 26 (8.8%) patients.Deaths: 21 (7.1%, 95%CI: 4.1%-10%). - Liver-related deaths: 12 (57%).- Other causes of death: 9 (43%)

RESULTS (IV)Probability of decompensations of cirrhosis

p<0.0001 p<0.0001

Pro

babi

lity

of re

mai

ning

free

of d

ecom

pens

atio

n

F0F1F2F3F4

LSM ≤6 KPaLSM 6.1-8.9 KPaLSM 9-14.6 KPaLSM 14.6-21 KPaLSM ≥21 KPa

According to fibrosis stage (LB) According to LSM category

Median (IQR) follow-up: 5 (4.2-5.4) years. Lost to follow-up: 26 (8.8%) patients.

Decompensations: 21 (7.1%, 95%CI: 4.1%-10%). - Ascites: 12 (57%) - Portal hypertensive gastrointestinal bleeding: 4 (19%). - Hepatic encephalopathy: 2 (9.5%).

Pro

babi

lity

of re

mai

ning

free

of d

ecom

pens

atio

n

RESULTS (V)Probability of liver-related death

p=0.0004 p<0.0001F0F1F2F3F4

LSM ≤6 KPaLSM 6.1-8.9 KPaLSM 9-14.6 KPaLSM 14.6-21 KPaLSM ≥21 KPa

According to fibrosis stage (LB) According to LSM category

Median (IQR) follow-up: 5 (4.2-5.4) years. Lost to follow-up: 26 (8.8%) patients.Liver-related deaths: 12 (4%).

RESULTS (VI)Univariate Cox regression analysis:

Overall mortalityCovariate Category HR¹ (95%CI²) PAge Per year 1.08 (1.01-1.15) 0.010Gender Male vs. Female 0.94 (0.34-2.57) 0.905

HCV genotype 1 vs. Non-1 1.09 (0.79-1.52) 0.597

SVR Yes vs. No 0.15 (0.02-1.11) 0.063

AIDS AIDS vs. Non-AIDS 1.01 (0.39-2.61) 0.980

CD4 Per 50 cel/ml increase 0.997 (0.996-0.999) 0.022HIV-RNA ≤50 vs. >50 c/ml 0.67 (0.26-1.72) 0.406

ALT Per 10 UI/ml increase 1.0 (0.93-1.01) 0.898

Platelets Per 10x10³/ml 0.91 (0.84-0.97) 0.005LB Per stage increase 1.63 (1.16-2.29) 0.005LSM Per 5 KPa increase 1.05 (1.03-1.08) <0.001

1: Hazard Ratio; 2: 95% confidence interval.

RESULTS (VII)Multivariate Cox regression models:

Overall mortality

0.750.50.25 1.5

1.07(1.003-1.14)

Age (p=0.041)

0.75 1.25

SVR (p=0.071)

CD4 (p=0.159)

Platelets (p=0.092)

Fibrosis stage(p=0.017)

0.15 (0.02-1.17)

0.93 (0.84-1.03)

0.94 (0.85-1.03)

1.52 (1.08-2.15)

Model based on LB Model based on TE

LSM(p=<0.001)

1.28 (1.12-1.46)

0.97 (0.90-1.05)

0.91 (0.83-1.01)

0.23 (0.03-1.72)

1.07 (1.004-1.14)

Platelets(p=0.453)

CD4 (p=0.066)

SVR (p=0.151)

Age (p=0.038)

The model based on TE performed 3.9% better than the model based on LB (p=0.072)1.25

Models adjusted by gender.

1 0.5 11.75 20 2.25 0 0.25 1.5 1.75 2 2.25

RESULTS (VIII)Univariate competing risks regression analysis:

Decompensations of cirrhosisCovariate Category SHR¹ (95%CI²) P

Age Per year 1.05 (0.98-1.13) 0.185

Gender Male vs. Female 0.75 (0.29-1.91) 0.548

HCV genotype 1 vs. Non-1 1.02 (0.74-1.41) 0.906

SVR Yes vs. No 0.15 (0.02-1.12) 0.065

AIDS AIDS vs. Non-AIDS 1.22 (0.49-2.99) 0.669

CD4 Per 50 cel/ml increase 0.92 (0.83-1.02) 0.120

HIV-RNA ≤50 vs. >50 c/ml 0.88 (0.29-2.65) 0.818ALT Per 10 UI/ml increase 1.01 (0.97-1.04) 0.696

Platelets Per 10x10³/ml 0.88 (0.81-0.95) 0.001LB Per stage increase 2.00 (1.32-3.00) 0.001LSM Per 5 KPa increase 1.42 (1.31-1.55) <0.001

1: Subhazard ratio; 2: 95% confidence interval.

RESULTS (IX)Multivariate competing risks regression models:

Decompensations

0.750.5 1.25 0.50.25 1.5

Age(p=0.394)

SVR(p=0.063)

CD4 (p=0.486)

Platelets (p=0.014)

Fibrosis stage(p=0.007)

1.04 (0.96-1.12)

0.15 (0.02-1.11)

0.97 (0.88-1.06)

0.91 (0.84-0.98)

1.67 (1.15-2.43)

LSM(p=<0.001)

1.37 (1.21-1.54)

Platelets (p=0.439)

CD4 (p=0.274)

0.97 (0.89-1.05)

0.94 (0.86-1.04)

0.22 (0.03-1.73)

1.03 (0.95-1.12)

1 1

SVR(p=0.150)

1.5 20 0.25 1.75 2 2.25 0 0.75 1.25 1.75 2.25The model based on TE performed 8.4% better than the model based on LB (p=0.045)

Models adjusted by gender.

Model based on LB Model based on TE

Age(p=0.460)

CONCLUSIONS

• The performance of models based on TE to predict overall

survival among HIV/HCV-coinfected patients was similar to that

of LB-based models.

• TE predicts decompensations better than LB-based models.

• The non-invasive nature of TE should favor its use instead of

LB when the only issue is predicting the clinical outcome of

liver disease in HIV/HCV-coinfection.