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INTRODUCTION

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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 GermansTrias 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.

To compare the prognostic performance of LB with that of LSM to predict survival and liver decompensations among HIV/HCV-coinfected patients.

- Retrospective cohort study (2005-2011).
- Inclusion criteria:
- HIV infection.
- HCV infection: Detectable plasma HCV-RNA at baseline.
- LB and TE separated by ≤12 months.

- 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.

1: Median (IQR)

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

Probability of all-cause death

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%)

According to fibrosis stage (LB)

According to LSM category

LSM ≤6 KPa

F0

LSM 6.1-8.9 KPa

F1

LSM 9-14.6 KPa

F2

LSM 14.6-21 KPa

F3

LSM ≥21 KPa

F4

Probability of survival

Probability of survival

p=0.005

p<0.0001

Probability of decompensations of cirrhosis

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%).

According to fibrosis stage (LB)

According to LSM category

LSM ≤6 KPa

F0

LSM 6.1-8.9 KPa

F1

LSM 9-14.6 KPa

F2

LSM 14.6-21 KPa

F3

LSM ≥21 KPa

F4

Probability of remaining free of decompensation

Probability of remaining free of decompensation

p<0.0001

p<0.0001

Probability of liver-related death

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

Liver-related deaths: 12 (4%).

According to fibrosis stage (LB)

According to LSM category

LSM ≤6 KPa

F0

LSM 6.1-8.9 KPa

F1

LSM 9-14.6 KPa

F2

LSM 14.6-21 KPa

F3

LSM ≥21 KPa

F4

p=0.0004

p<0.0001

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

Model based on LB

Model based on TE

Age

(p=0.041)

Age

(p=0.038)

1.07

(1.003-1.14)

1.07

(1.004-1.14)

SVR

(p=0.151)

SVR

(p=0.071)

0.15

(0.02-1.17)

0.23

(0.03-1.72)

CD4

(p=0.159)

CD4

(p=0.066)

0.93

(0.84-1.03)

0.91

(0.83-1.01)

Platelets

(p=0.092)

0.94

(0.85-1.03)

Platelets

(p=0.453)

0.97

(0.90-1.05)

Fibrosis stage

(p=0.017)

LSM

(p=<0.001)

1.52

(1.08-2.15)

1.28

(1.12-1.46)

0

1

1.25

1.75

2

2.25

0

0.25

0.5

1

1.5

1.75

2

2.25

0.25

0.5

1.5

1.25

0.75

0.75

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

Models adjusted by gender.

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

Model based on LB

Model based on TE

Age

(p=0.394)

Age

(p=0.460)

1.03

(0.95-1.12)

1.04

(0.96-1.12)

SVR

(p=0.063)

0.15

(0.02-1.11)

SVR

(p=0.150)

0.22

(0.03-1.73)

CD4

(p=0.486)

0.97

(0.88-1.06)

0.94

(0.86-1.04)

CD4

(p=0.274)

Platelets

(p=0.014)

0.91

(0.84-0.98)

Platelets

(p=0.439)

0.97

(0.89-1.05)

Fibrosis stage

(p=0.007)

LSM

(p=<0.001)

1.37

(1.21-1.54)

1.67

(1.15-2.43)

0

0.25

1

1.25

1.5

1.75

2

2.25

0

0.25

0.75

1.25

1.5

1.75

2

2.25

0.5

0.75

0.5

1

The model based on TE performed 8.4% better than the model based on LB (p=0.045)

Models adjusted by gender.

- 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.