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Keywords:

  • hepatitis C virus;
  • HIV;
  • liver fibrosis;
  • predictive model

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Objectives

Recently, several models incorporating laboratory measurements have been validated for use as surrogate markers for liver fibrosis in hepatitis C virus (HCV) mono-infection, the simplest of these being the aspartate aminotransferase (AST) to platelet ratio index (APRI). We evaluated how well the APRI predicts significant hepatic fibrosis in patients with HIV/HCV coinfection.

Methods

Forty-six HIV/HCV-coinfected patients who underwent liver biopsy and had concomitant laboratory measurements (±3 months) were included in the study. Significant fibrosis was defined as F2–F4 using Batt and Ludwig scoring (=3 Ishak). APRI=[(AST/upper limit of normal)/platelet count (109/L)] × 100. We used sas proc logistic (SAS Institute, Cary, NC) to calculate the area under the receiver operating curve (ROC) (AUC). Sensitivities, specificities, positive predictive value (PPV) and negative predictive value (NPV) were compared using cut-offs previously identified in the literature.

Results

Thirty-three of 46 patients (72%) had significant fibrosis on biopsy. For significant fibrosis, the area under the ROC for the APRI was 0.847±0.057. APRI scores >1.5 (the higher cut-off) were 100% specific and 52% sensitive; PPV was 100% and NPV 45%. Scores <0.5 (the lower cut-off) were 82% sensitive and 46% specific in ruling out significant fibrosis (PPV 79%; NPV 50%).

Conclusions

A simple model incorporating readily available laboratory data is highly predictive of significant fibrosis in HIV/HCV coinfection and could serve as a biopsy-sparing measure, thus making treatment more accessible for this population.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

HIV/hepatitis C virus (HCV) coinfection is associated with increased rates of HCV-related disease progression [1]. Death from liver disease has become one of the most common causes of death among HIV-infected individuals [2]. To prevent the consequences of chronic HCV infection, treatment is recommended for patients with significant fibrosis, as they are most likely to progress to end-stage liver disease [3,4]. Liver biopsy is, to date, the only accurate method to assess liver histology but is expensive, is not always accessible and poses some risks [5]. Consequently, a requirement for a liver biopsy prior to HCV therapy may prevent significant numbers of patients from receiving treatment [6]. In addition, recent data suggest that repeated liver biopsies may be necessary as often as every 3 years in order to assess the progression of liver disease in HIV/HCV coinfection, as patients with even minimal fibrosis may rapidly progress to cirrhosis [7].

Recently, several models incorporating laboratory measurements have been validated for use as surrogate markers for liver fibrosis in HCV mono-infection [8–10]. Most of the models developed involve measurement of nonroutine laboratory tests or use complex or proprietary formulae (e.g. the fibrosis index from MULTIVIRC is comprised of six markers: β2 macroglobulin, haptoglobin, gamma-globulin, apolipoptotein A1, γ-glutamyl-transpeptidase and total bilirubin). The aspartate aminotransferase (AST) to platelet ratio index (APRI) is one of the simplest formulae that has been validated in HCV mono-infection. We evaluated the predictive value of the APRI to identify significant fibrosis in patients with HIV/HCV coinfection.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We evaluated 46 HIV/HCV-coinfected patients from two tertiary care clinics who underwent liver biopsy for staging of HCV infection and had concomitant laboratory data (±3 months). Chronic HCV was defined as a positive serological test for HCV by enzyme-linked immunosorbent assay (ELISA) with a positive reverse transcriptase–polymerase chain reaction (RT-PCR) for HCV RNA (Roche Amplicor Assay version 2.0; Roche Diagnostics Corp., Indianapolis, IN). HIV infection was diagnosed by ELISA and with confirmatory western blot. Liver biopsies were scored using the Batt and Ludwig system, where F0 denotes no fibrosis, F1 denotes portal fibrosis, F2 denotes periportal fibrosis, F3 denotes septal fibrosis, and F4 denotes cirrhosis. Significant fibrosis was defined as F2–F4 (equivalent to Ishak score ≥3). All patients were HCV treatment-naïve and had no evidence of chronic hepatitis B virus infection (HBsAg negative). The APRI is defined as follows: [(AST/upper limit of normal)/platelet count (109/L)] × 100.

Haematological and biochemical analyses were extracted from prospective computerized databases. Descriptive statistics were compared in relation to the presence of significant fibrosis using χ2 and Student's t-tests. All tests were two-tailed with P-values <0.05 considered significant. We used sas proc logistic (V.8.02; SAS Institute, Cary, NC) to calculate the area under the receiver operating curve (ROC) (AUC). Standard errors (SEs) for the AUC were calculated according to Hanley and McNeil [11]. Sensitivities, specificities, positive predictive value (PPV) and negative predictive value (NPV) were compared using cut-offs previously identified in the literature (i.e. APRI >1.5 for significant fibrosis and <0.5 for ruling out significant fibrosis [8]).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Of 46 patients, 33 (72%) had significant fibrosis on biopsy: 14 with F2, 10 with F3 and nine with F4. There was no difference between those with and those without significant fibrosis with respect to mean CD4 T-cell count or HIV viral load. Patients with F2–F4 fibrosis were less likely to be on antiretroviral therapy (58% versus 85%), had significantly higher mean alanine aminotransferase (ALT), AST and international normalized ratio (INR) and lower levels of albumin and platelets (P<0.05). Patients with significant fibrosis were also more likely to be drinking alcohol (any amount) at the time of biopsy (33% versus 0%; P=0.03). Characteristics of the study population are shown in Table 1.

Table 1.   Characteristics of the study population in relation to the presence or absence of significant fibrosis (defined as Batt and Ludwig score of F2–F4) on liver biopsy
 Fibrosis scoreP-value
F0–F1 (n=13)F2–F4 (n=33)
  1. Values are n (%) or mean±standard error. Descriptive statistics were compared using χ2 and Student's t-tests.

  2. HCV, hepatitis C virus; INR, international normalized ratio; ALT, alanine aminotransferase; AST, aspartate aminotransferase; APRI, AST to platelet ratio.

Age (years)40±1343±70.55
Sex (male)13 (93%)28 (85%)0.45
Risk factor  0.69
 Injection drug use9 (69%)22 (69%) 
 Men having sex with men2 (15%)3 (9%) 
 Endemic country2 (15%)5 (15%) 
 Blood product0 (0%)2 (3%) 
 Alcohol use011 (33%)0.03
Time since HCV diagnosis (years)2.22±4.293.55±4.70.37
Time since HIV diagnosis (years)8.74±7.037.55±5.650.55
HCV genotype  0.79
18 (73%)20 (77%) 
33 (27%)6 (23%) 
CD4 count (cells/μL)467.38±161.18414.82±196.350.40
HIV RNA (log copies/mL)2.45±1.182.7±1.340.57
HIV RNA <50 copies/mL9 (69%)18 (55%)0.36
AST (IU/L)42.38±14.7101.88±82.490.01
ALT (IU/L)56.43±26.18110.88±96.410.04
Alkaline phosphatase (U/L)66.31±21.72102.55±46.270.009
Bilirubin (umol/L)17.38±16.1527.19±45.260.45
Platelets 109/L220.71±45.29158.3±76.880.007
Albumin (g/L)39.93±2.436.34±4.810.012
INR0.99±0.061.11±0.130.002
APRI0.57±0.242.76±3.120.016

For significant fibrosis, the area under the ROC for the APRI was 0.847±0.06 (mean±SE) (Fig. 1). None of the 13 patients with a fibrosis score less than F2 had an APRI above the upper cut-off of 1.5, compared with 17 of 33 patients with scores between F2 and F4. Thus, APRI values above 1.5 were 100% specific and 52% sensitive for predicting significant fibrosis (with a PPV of 100% and an NPV of 45%). APRI values less than 0.5 (the lower cut-off value) were 82% sensitive and 46% specific in ruling out significant fibrosis (with a PPV of 79% and an NPV of 50%). Seven of nine patients (78%) with cirrhosis had an APRI score >1.5.

image

Figure 1.  Area under the receiver operating curve (ROC) (AUC) for predicting significant hepatic fibrosis (Batt and Ludwig score of F2–F4).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We have demonstrated that the APRI is a simple, highly specific and noninvasive method for ruling in significant hepatic fibrosis in HIV/HCV coinfection. The APRI demonstrated a similar level of performance compared with other noninvasive measures that have been developed in HCV mono-infection, such as MULTIVIRC [9] and that proposed by Forn et al. [10], which have had ROCs ranging from 0.8 to 0.9. Of the models developed so far, the only index that has been validated in coinfection is the MULTIVIRC equation [13]. Although it performed well, it involves a complex and proprietary formula that cannot be readily applied in clinical practice or for research. The beauty of the APRI is its simplicity and its use of routine and readily available laboratory markers. The APRI was originally developed to amplify opposing effects of liver fibrosis on AST and platelets. It predicts fibrosis stage with a higher correlation coefficient than platelet count or AST level alone (r=0.60, P<0.001) [8]. In the original validation study, the area under the ROC for predicting F2–F4 fibrosis was 0.80, which is similar to the value we observed in our coinfected population [8].

Since the inception of our study, Sterling et al. presented a model that was developed from coinfected patients entering a randomized controlled trial of HCV therapy [12]. The model, called FIB-4, is calculated as follows:

age (years) × AST (U/L)/[platelet count (109/L) × ALT1/2].

In our population, the FIB-4 performed similarly to the APRI, with an area under the ROC of 0.85±0.06 (mean±SE). FIB-4 values ≥3.25 were similarly 100% specific but only 33% sensitive for predicting significant fibrosis (with a PPV of 100% and an NPV of 37%). However, the FIB-4 was somewhat better than the APRI for ruling out cirrhosis. Values of FIB-4≤1.45 were 79% sensitive and 85% specific (with a PPV of 93% and an NPV of 61%).

The relatively small number of patients evaluated, especially in the cirrhosis category, is a recognized limitation of our study and underlines the need for prospective evaluation of these simple surrogate measures in larger clinical cohorts. However, our study population did have a good distribution of fibrosis levels, genotypes and risk factors, similar to those that have been reported in other large cohorts of HCV/HIV-coinfected patients. Specifically, larger studies could address possible concerns about HIV-specific effects on platelet counts and effects of antiretroviral medications on AST measurements. If validated, the APRI could have both clinical and research implications. Given the high PPV of an APRI >1.5, such patients could be offered HCV therapy without undergoing a liver biopsy. In other words, our findings suggest that, for HCV treatment decisions, by determining the presence of fibrosis the APRI could reduce the need for liver biopsies by 50%. It remains important to note that patients with scores <1.5 may still have significant fibrosis and even cirrhosis, emphasizing the need to evaluate these individuals using liver histology. Finally, the APRI might serve as a useful and inexpensive tool for evaluating hepatic fibrosis and the long-term effects of various factors, such as hepatic steatosis, obesity, alcohol, diabetes and antiretroviral treatment, on the evolution of liver disease in large cohorts of coinfected patients.

In conclusion, the APRI, a simple model incorporating readily available laboratory data, is highly predictive of significant fibrosis in HIV/HCV coinfection and could serve as a biopsy-sparing measure, thus making treatment more accessible for this population.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We are grateful to Carolyn Kato and Karina Pourreaux for study coordination. Funding was provided by the Canadian Institutes of Health Research (New Investigator Award to MBK) and les Fonds de la Recherche en santé du Québec (infrastructure funding from the Réseau SIDA et Maladies Infectieuses to MBK).

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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