Skip Navigation

Predictors of Liver Fibrosis in HIV-Infected Patients with Chronic Hepatitis C Virus (HCV) Infection: Assessment Using Transient Elastometry and the Role of HCV Genotype 3

  1. Pablo Barreiro,
  2. Luz Martín-Carbonero,
  3. Marina Núñez,
  4. Pablo Rivas,
  5. Adolfo Morente,
  6. Nuria Simarro,
  7. Pablo Labarga,
  8. Juan González-Lahoz, and
  9. Vincent Soriano
  1. Department of Infectious Diseases, Hospital Carlos III, Madrid, Spain
  1. Reprints or correspondence: Dr. Vincent Soriano, Dept. of Infectious Diseases, Hospital Carlos III, Calle Sinesio Delgado 10, 28029 Madrid, Spain (vsoriano{at}dragonet.es).
 
Next Section

Abstract

Background. Liver fibrosis is accelerated in patients coinfected with hepatitis C virus (HCV) and human immunodeficiency virus (HIV). The reasons for this faster liver disease progression are unclear, although higher plasma HCV RNA levels and distinct HCV genotype distribution in this population, compared with in HCV-monoinfected subjects, could play a role.

Methods. Liver fibrosis was assessed using elastometry in all consecutive HIV-infected patients with chronic hepatitis C who attended our institution (Hospital Carlos III, Madrid) during the past 12 months. Hepatic stiffness was measured in kiloPascal units (kPa) and was interpreted on the basis of Metavir score: no or mild fibrosis (score, F0–F1) when liver stiffness is ⩽7.1 kPa, and fibrosis with septa or cirrhosis (F2–F4) when >7.1 kPa.

Results. A total of 283 patients (71% were male; mean age, 42 years; 94% were injection drug users and 94% were receiving antiretrovirals; mean CD4 cell count, 554 cells/µL; 72% with plasma HIV RNA level of <50 copies/mL) were analyzed. The mean alanine aminotransferase level was 68 IU/L, and the mean plasma HCV RNA level was 5.9 log IU/mL. HCV genotype distribution was as follows: genotype 1, 60% of patients; genotype 2, 2%; genotype 3, 26%; and genotype 4, 12%. Overall, 164 (58%) of the patients had scores indicating advanced liver fibrosis (F2–F4), as determined using elastometry. In the univariate and multivariate analyses, respectively, a significant odds ratio (OR) for score F2–F4 was found for HCV genotype 3, compared with the other genotypes (OR, 1.9 [95% confidence interval {CI}, 1.1–3.4] vs. 4.3 [95% CI, 1.4–13.3]); for older age (OR, 1.1 [95% CI, 1.03–1.17] vs. 1.1 [95% CI, 1.01–1.25]); and for elevated alanine aminotransferase levels (OR, 1.02 [95% CI, 1.01–1.03] vs. 1.03 [95% CI, 1.01–1.04]). Although patients with HCV genotype 1 had higher mean serum HCV RNA levels than did those with HCV genotype 3 (6.1 log IU/mL vs. 5.7 log IU/mL; P = .01), patients with HCV genotype 3 tended to have F2–F4 scores more frequently than did those with HCV genotype 1 (69% vs. 58%; P = not significant).

Conclusions. HCV genotype 3, older age, and elevated alanine aminotransferase levels are independent predictors of advanced liver fibrosis in HCV-HIV–coinfected patients.

The development of liver fibrosis is the underlying pathogenic phenomenon that leads to most clinical complications in patients with chronic hepatitis C virus (HCV) infection. Several factors, such as male sex, older age, longer duration of HCV infection, and/or high levels of alcohol consumption, have classically been associated with more severe liver damage in patients with chronic hepatitis C [1]. More recently, HIV coinfection has been demonstrated to be a strong independent predictor of accelerated HCV-related liver fibrosis [2]. Accordingly, liver complications are currently one of the leading causes of morbidity and mortality among HIV-HCV–coinfected patients [3, 4].

Although an inverse relationship between CD4 cell count and the severity of liver fibrosis has been found [5, 6], the potential profibrotic role of other factors is less clear [7]. For instance, HAART, by reverting immune suppression, could be beneficial for patients with HCV-related liver disease [8, 9]. However, liver damage due to antiretroviral toxicity could worsen liver disease [10, 11]. In addition, although HCV genotypes were considered to cause liver fibrosis with similar frequency, recent reports have questioned this. For example, patients infected with HCV genotype 1 seem to show higher HCV RNA levels in both plasma [12] and the liver [13], with more rapid progression to end-stage liver disease than in patients with other HCV genotypes. On the other hand, patients infected with HCV genotype 3 frequently show liver steatosis, which ultimately accelerates liver fibrosis [14].

Liver biopsy has been, for many years, the most reliable procedure to assess the extent of hepatic fibrosis in chronic hepatitis C. However, this tool is not free of complications [15] and may not always be as accurate as desired when therapeutic decisions need to be made. In this regard, 20% interobserver variation [16] and 33% sampling errors [17] have been reported for HCV disease staging. Moreover, liver biopsy has mainly been performed to assess the prospects of anti-HCV therapy in patients considered to be potential candidates for treatment. Thus, histological information derived from individuals who refuse to receive treatment is scarce. This lack exists particularly for subjects with normal alanine aminotransferase (ALT) levels, who have often been excluded from treatment protocols. Conversely, patients with HCV genotype 2 or 3 have often been given treatment in the absence of any histological information, given the good response to anti-HCV therapy in these patients. All these limitations complicate the knowledge of the main determinants of liver fibrosis progression in patients with chronic hepatitis C.

Transient elastometry is a new, noninvasive procedure that has recently been developed to measure the stiffness of liver tissue [18]. The accuracy of the method for measuring liver fibrosis has been compared with that of liver biopsy in 2 recent publications, both of which have shown impressive good correlations in HCV-monoinfected patients [19, 20]. On the basis of those results, we decided to investigate the extent of liver fibrosis in a relatively large group of HCV-HIV–coinfected patients, including patients not considered to be candidates for anti-HCV therapy. The factors associated with more advanced liver fibrosis in this population were subsequently examined.21

Previous SectionNext Section

Patients and Methods

Study population. All patients with HIV type 1 infection and chronic hepatitis C, defined as reactive HCV serologic test result and detectable HCV RNA in plasma, who attended our institution (Hospital Carlos III, Madrid) in a 12-month period (September 2004–August 2005) were identified and were invited to undergo transient elastometry testing. Individuals with chronic hepatitis C who had reached sustained virological response to HCV therapy in the past were not excluded. The study was approved by the ethics committee of the institution.

A case-report form was designed and was filled out for each individual. Laboratory parameters (ALT level, CD4 cell count, and HIV and HCV RNA loads) were recorded for the latest control values prior to the time of the elastometry examination. There were no lag times of >4 months between elastometry and laboratory testing.

HCV RNA load was measured using a commercial real-time PCR assay (Cobas Taqman; Roche Diagnostic Systems) that has a lower limit of detection of 10 IU/mL. HCV genotypes were assessed using a commercial reverse-hybridization method (InnoLiPA HCV II; Innogenetics).

Liver fibrosis assessment using elastometry. Liver stiffness was determined using transient elastometry [18]. In brief, the hepatic region of the patient was explored with an ultrasound transducer that was placed in the right intercostal spaces. When the echography window showed the characteristic image of liver tissue, an elastic shear wave was emitted by the vibration of the ultrasound probe. The speed of propagation of this vibration through the liver parenchyma was calculated by ultrasound scanning. On the basis of physical principles, the stiffer the liver is, the faster the vibration will pass through the organ. A good correlation between the speed of propagation of the elastic shear wave and the degree of liver fibrosis has been proven in 2 major studies that compared assessment of liver fibrosis by histology and by elastometry [19, 20]. The positive predictive value of advanced liver fibrosis (fibrosis with septa or overt cirrhosis; Metavir score F2–F4 [21]) was as high as 95% when elastometry yielded liver stiffness values of >7.1 kiloPascal units (kPa).

To avoid interindividual variation, a single experienced trainer performed all elastometry measurements in our study. The right lobe of the liver was explored through the intercostal space on patients lying in dorsal decubitus. With the guide of ultrasound images, the best access to the liver was selected, excluding areas with heterogeneous echogenicity or vascular structures. At least 10 valid elastometric measurements were obtained per patient. The elasticity of the liver was recorded as the median of all single measures taken. The proportion of valid elastometric measures in relation to the total (valid plus nonvalid) elastometric measures obtained per patient (i.e., the success rate of elastometry) was calculated. In accordance with prior recommendations, patients for whom elastometry success rates were <0.7 were excluded [20].

Statistical analyses. Descriptive values are expressed as percentages, means (±SD), or medians (range). Given the cross-sectional nature of the study, the association of multiple variables with the 2 distinct groups—patients with minimal (F0–F1) liver fibrosis and patients with advanced (F2–F4) liver fibrosis—was analyzed in univariate and multivariate analyses. Comparisons were made using the χ2 test for proportions and using parametric or nonparametric tests, as required, for continuous variables. Finally, all variables included in the univariate analysis that had P values of ⩽.5 were considered for a logistic regression analysis. All data were recorded and analyzed using SPSS, version 11.01 (SPSS).

Previous SectionNext Section

Results

Main characteristics of the study population. A total of 285 HCV-HIV–coinfected patients were identified during the study period. All consented to undergoing testing with transient elastometry. However, in 2 cases, invalid elastometric measurements were obtained, in both instances because of severe obesity. Therefore, all further analyses were performed for the remaining 283 patients (table 1). Among them, 71% were male, and the mean age was 42 ± 5 years. As expected, a high proportion (94%) were former injection drug users.

Table 1
View larger version:
Table 1

Characteristics of 283 patients coinfected with HIV and hepatitis C virus (HCV), by liver fibrosis stage estimated using transient elastometry.

Mean laboratory parameters were ALT level of 68 ± 56 IU/L, CD4 cell count of 554 ± 287 cells/µL, and HIV RNA load of 2 ± 0.9 log copies/mL. Most patients (94%) were receiving HAART, and 72% had an HIV RNA load of <50 copies/mL. The distribution of patients done according to the type of antiretroviral regimen being received at the time of examination was fairly heterogeneous. However, 35% were receiving protease inhibitors, 33% were receiving nonnucleoside reverse-transcriptase inhibitors, and 26% were receiving triple nucleoside/nucleotide analogue combinations. It should be pointed out that 17% were receiving dideoxynucleoside analogues (didanosine and/or stavudine).

The mean HCV RNA load was 5.9 ± 0.9 log IU/mL, and the distribution of genotypes was as follows: 60% of patients were infected with genotype 1, 2% with genotype 2, 25% with genotype 3, 12% with genotype 4, and 2 patients with mixed genotypes (2 and 3). Nearly half of the study population (49%) had been exposed to anti-HCV therapy in the past (37 patients to IFN monotherapy, 32 to IFN and ribavirin, and 65 to pegylated IFN and ribavirin). However, only 17% of them experienced sustained virological response. Given that no definitive information exists regarding a possible reversion of liver fibrosis in patients whose HCV infection has cleared with anti-HCV therapy, we decided to keep this small group of patients in our analysis.

All patients were evaluated with transient elastometry. At least 10 measurements were available for each patient (mean, 10.6 ± 1.9 measurements/patient). The mean success rate of elastometric measures (proportion of valid measures over all measures obtained) was 0.87 ± 0.13, with no rates of <0.8. Overall, 119 (42%) of the patients had median elastometric values compatible with no or mild liver fibrosis (liver stiffness, <7.1 kPa); the remaining 164 patients (58%) had advanced liver fibrosis (liver stiffness, >7.1 kPa). The accuracy of elastometry, in terms of the mean number of valid measures and elastometry success rates, was comparable when fibrotic and nonfibrotic patients were compared. The distribution of patients according to estimated Metavir scores for liver fibrosis (mean elastometric value) was as follows: F0–F1 (5.4 ± 0.95 kPa) in 69 patients (42%), F2 (8.2 ± 0.6 kPa) in 36 (22%), F3 (10.6 ± 0.7 kPa) in 16 (10%), and F4 (23.9 ± 13.3 kPa) in 43 (26%).

Comparisons between HCV genotypes. No significant differences between patients with HCV genotype 3 and patients with other genotypes were found when demographic characteristics or main laboratory parameters were compared, except for that there was a lower proportion of men with genotype 3 (57% vs. 76%; P = .004) and higher mean ALT value for those with genotype 3 than for those with other genotypes (75 ± 78 vs. 65 ± 46 IU/L; P < .001) (table 2). Likewise, no significant differences in plasma HIV RNA levels or CD4 cell counts were noticed when patients with distinct HCV genotypes were compared. Although subjects with HCV genotype 3 tended to have been exposed more frequently to anti-HCV therapy in the past than the other patients, the difference did not reach statistical significance (56.3% vs. 45.9%; P = not significant). However, as expected, sustained viral clearance had been experienced by a greater proportion of patients with genotype 3 than by those with other genotypes (19.6% vs. 7.7%; P = .01).

Table 2
View larger version:
Table 2

Characteristics of 283 patients coinfected with HIV and hepatitis C virus (HCV), by HCV genotype.

The mean success rate of elastometry in patients with HCV genotype 3 was similar to that in patients with other genotypes (0.88 ± 0.17 vs. 0.87 ± 0.14, respectively). The proportion of patients with significant liver stiffness (>7.1 kPa; Metavir score, F2–F4) was significantly higher in the group infected with HCV genotype 3 than in the other groups (69% vs. 54%; P = .02).

Predictors of advanced liver fibrosis. A total of 164 (58%) of the 283 patients were found to show advanced (F2–F4) liver fibrosis on the basis of elastometry (liver stiffness, >7.1 kPa). Older age was the only demographic variable that could be associated with higher liver stiffness (P = .001). No differences were found with respect to sex, body mass index, or risk behavior (table 3).

Table 3
View larger version:
Table 3

Predictors of advanced liver fibrosis (Metavir score, F2–F4) in a population coinfected with HIV and hepatitis C virus (HCV).

Mean ALT values were higher in patients with advanced liver fibrosis than in those with minimal (F0–F1) liver fibrosis (81 ± 66 vs. 48 ± 27 IU/L; P < .001). Likewise, the proportion of patients with ALT levels above the upper limit of normality (>55 IU/L) was higher for subjects with liver stiffness >7.1 kPa than for those with liver stiffness ⩽7.1 kPa (56% vs. 29%; P < .001). Of note, the positive predictive value for significant liver stiffness (Metavir score, F2–F4) in subjects with elevated ALT levels was particularly high for HCV genotype 3 (87%; 95% CI, 75%–99%), whereas it was lower (68%; 95% CI, 59%–78%) for patients with other HCV genotypes. These differences persisted when the subset of patients whose chronic hepatitis C had been successfully treated with anti-HCV therapy were excluded from the analysis (data not shown).

Mean plasma HIV RNA loads and CD4 cell counts, as well as the proportion of patients receiving HAART and the duration of antiretroviral therapy, did not differ significantly when patients with advanced (F2–F4) and patients with minimal (F0–F1) liver fibrosis were compared. Likewise, mean plasma HCV RNA levels and prior experience with IFN-based therapies did not different either. As mentioned above, the proportion of patients with estimates of advanced liver fibrosis was higher among subjects infected with HCV genotype 3 (50 [69%] of 72) than among patients with other genotypes (114 [54%] of 211) (P = .02). Although no differences in liver fibrosis were observed with respect to alcohol consumption, all 6 patients with positive test results for hepatitis B surface antigen were in the group with advanced liver fibrosis.

The multivariate analysis was performed with a model including all variables that yielded a P value of ⩽.5 in the univariate analysis (table 3). Then, infection with HCV genotype 3 became the strongest independent predictor of advanced liver fibrosis (OR, 4.3; 95% CI, 1.4–13.3), compared with older age (OR, 1.12; 95% CI, 1.01–1.25) and elevated ALT level (OR, 1.03; 95% CI, 1.01–1.04)—the other 2 variables independently associated with advanced liver fibrosis.

Previous SectionNext Section

Discussion

Chronic hepatitis C is generally characterized by slow progression of liver fibrosis, which ultimately leads to cirrhosis. A wide interindividual variability in the time to reach end-stage liver disease exists. Although multiple factors are associated with faster liver fibrosis progression, including male sex, older age, coinfection with hepatitis B virus, HIV-related immunodeficiency, and high alcohol consumption [1], this information is mainly derived from a subset of patients with chronic hepatitis C; namely, those considered to be potential candidates for anti-HCV therapy. In the present study, liver fibrosis was assessed in a relatively large group of HCV-HIV–coinfected patients, including patients not considered to be candidates for anti-HCV therapy (i.e., subjects with normal ALT levels, neuropsychiatric conditions, active drug addiction, etc.). With this sample, an association between HCV genotype 3 and advanced liver fibrosis stages was found. This observation has significant clinical implications, because patients infected with HCV genotype 3 are among those with the best responses to current anti-HCV therapy; therefore, our observation reinforces that treatment should be pursued particularly for these patients [22].

The association between HCV genotype 3 and advanced liver fibrosis was highly significant, even though there was a greater proportion of women in the genotype 3 group compared with the rest and female sex has been associated with slower progression of liver fibrosis [23]. Moreover, the association between more advanced liver fibrosis and HCV genotype 3 was seen even when a larger proportion of the individuals had experienced clearance of HCV infection after a prior course of anti-HCV therapy.

Wrigth et al. [24] were the first to describe a differential involvement of HCV genotypes in the evolution of liver fibrosis. In their original study, those authors pointed out that non-1 HCV genotypes were responsible for a more rapid progression of liver fibrosis. Thereafter, others found an association between HCV genotype 3 and more severe liver damage. For instance, in a cross-sectional study of 314 liver biopsy specimens from HCV-monoinfected patients, Cholet et al. [25] found that the 2 independent factors associated with advanced (F2–F4) liver fibrosis were HCV genotype 3 and underlying liver steatosis. It might be argued that both factors may overlap somewhat, because microvesicular steatosis is a common finding in patients with HCV genotype 3 [26, 27].

In the largest study conducted thus far on liver biopsy specimens from HCV-HIV–coinfected patients, no influence of HCV genotype on hepatic fibrosis stage could be demonstrated [7]. Similar results dismissing a significant influence of HCV genotype on liver fibrosis have been found by others [5]. However, as mentioned above, most liver biopsy specimens in these studies had been obtained from patients considered up front to be candidates for anti-HCV therapy, and often excluded or less well represented were individuals with repeatedly normal ALT levels, heavy alcohol consumption, neuropsychiatric conditions, and so forth, who otherwise would represent more than half of an HCV-HIV–coinfected population [28, 29].

Infection with HCV genotype 3 has been associated with higher rates of liver steatosis [26, 27]. More recently, a link between hepatic steatosis and inflammation has been reported [30, 31], which may explain a faster progression to liver fibrosis in patients with chronic hepatitis C due to HCV genotype 3 [26, 32, 33]. In the context of HIV infection, other factors might also contribute to an explanation of the greater fibrogenic effect of HCV genotype 3. First, the risk of hepatotoxicity following initiation of antiretroviral drugs is greater in patients infected with HCV genotype 3 than in those infected with other genotypes [34–37]. 38Second, the use of some antiretrovirals could favor steatosis of the liver [27, 38–41]. In summary, HCV genotype 3 and antiretroviral therapy might be synergistic, together causing liver steatosis and indirectly accelerating the progression of liver fibrosis in HCV-HIV–coinfected patients.

In agreement with prior studies [12, 42, 43], we found that patients infected with HCV genotype 1 presented with higher mean plasma HCV RNA levels than did those infected with HCV genotype 3. In HCV-HIV–coinfected patients with hemophilia, this finding has been associated with more rapid CD4 cell count declines and faster HIV disease progression [12]. However, to our knowledge, no studies have found a significant correlation between HCV RNA levels and the extent of liver fibrosis [44]. Our results of elastometry confirm that there is no significant correlation between HCV RNA load and the extent of liver fibrosis.

ALT elevations are not a good marker of liver fibrosis. This is particularly true for HIV-infected patients, in whom other factors besides chronic hepatitis C, such as use of antiretroviral drugs, may also contribute to ALT abnormalities [22]. However, the probability of liver fibrosis with an F2–F4 Metavir score, estimated using elastometry, in our patients with elevated ALT levels was as high as 87% for HCV genotype 3 and 68% for other genotypes. Conversely, it was <40% in patients with normal ALT levels. Thus, as in HCV-monoinfected individuals [44], persistently normal ALT levels should generally be viewed as a marker of less severe liver fibrosis in coinfected patients.

Among the limitations of this study is its cross-sectional design, which precluded analysis of the progression of liver fibrosis. However, most patients in our series were former injection drug users, and the majority were likely to have been exposed to HCV for the first time at the age of 16–20 years. Thus, the duration of HCV infection was, in general, fairly correlated with age and was estimated to be 20–25 years for most subjects. On the other hand, the assessment of liver fibrosis by use of elastometry instead of classic histologic examination of a liver biopsy specimen might be criticized. However, this noninvasive tool has already been validated in several studies, and the positive predictive value of elastometry for the diagnosis of advanced liver fibrosis, the variable we analyzed in this study, has been as high as 95% [20]. Therefore, we are confident with our data, which in turn highlight the usefulness of this technique to bring new insights into the natural history of chronic hepatitis C. The simplicity and indulgence of transient elastometry, compared with liver biopsy, may probably facilitate, in the near future, a better understanding of the role of other factors involved in the progression of liver fibrosis in the HCV-HIV–coinfected population.

Previous SectionNext Section

Acknowledgments

We thank Victor de Ledinghen for comments and critical reading of the manuscript.

Potential conflicts of interest. All authors: no conflicts.

Financial support. This work was funded in part by grants from Fundación Investigación y Educación en Síndrome Ímmunodeficiencia Adquirida (SIDA), Red de Investigación en SIDA, and the VIRGIL Network.

  • Received October 29, 2005.
  • Accepted December 7, 2005.
Previous Section
 

References

  1. ↵
    1. Ryder S
    . Progression of hepatic fibrosis in patients with hepatitis C: a prospective repeat liver biopsy study. Gut 2004;53:451-5.
    Abstract/FREE Full Text
  2. ↵
    1. Poynard T,
    2. Mathurin P,
    3. Lai C,
    4. et al
    . A comparison of fibrosis progression in chronic liver diseases. J Hepatol 2003;38:257-65.
    CrossRefMedlineWeb of Science
  3. ↵
    1. Martín-Carbonero L,
    2. Soriano V,
    3. Valencia E,
    4. García-Samaniego J,
    5. López M,
    6. González-Lahoz J
    . Increasing impact of chronic viral hepatitis on hospital admissions and mortality among HIV-infected patients. AIDS Res Hum Retroviruses 2001;17:1467-71.
    CrossRefMedlineWeb of Science
  4. ↵
    1. Bica I,
    2. McGovern B,
    3. Dhar R,
    4. et al
    . Increasing mortality due to end-stage liver disease in patients with HIV infection. Clin Infect Dis 2001;32:492-7.
    Abstract/FREE Full Text
  5. ↵
    1. Benhamou Y,
    2. Bochet M,
    3. Di Martino V,
    4. et al
    . Liver fibrosis progression in HIV and HCV coinfected patients. The Multivirc Group. Hepatology 1999;30:1054-8.
    CrossRefMedlineWeb of Science
  6. ↵
    1. Puoti M,
    2. Bonacini M,
    3. Spinetti A,
    4. et al
    . Liver fibrosis progression is related to CD4 depletion in patients coinfected with hepatitis C virus and HIV. J Infect Dis 2001;183:134-7.
    Abstract/FREE Full Text
  7. ↵
    1. Martín-Carbonero L,
    2. Benhamou Y,
    3. Puoti M,
    4. et al
    . Incidence and predictors of severe liver fibrosis in HIV-infected patients with chronic hepatitis C: a European collaborative study. Clin Infect Dis 2004;38:128-33.
    Abstract/FREE Full Text
  8. ↵
    1. Benhamou Y,
    2. De Martino V,
    3. Bochet M,
    4. Poynard T
    . Factors affecting liver fibrosis in HIV and hepatitis C virus coinfected patients: impact of protease inhibitor therapy. Hepatology 2001;34:283-7.
    CrossRefMedlineWeb of Science
  9. ↵
    1. Tural C,
    2. Fuster D,
    3. Tor J,
    4. et al
    . Time on antiretroviral therapy is a protective factor for liver fibrosis in HIV and hepatitis C virus co-infected patients. J Viral Hepat 2003;10:118-25.
    CrossRefMedlineWeb of Science
  10. ↵
    1. Macías J,
    2. Castellano V,
    3. Merchante N,
    4. et al
    . Effect of antiretroviral drugs on liver fibrosis in HIV-infected patients with chronic hepatitis C: harmful impact of nevirapine. AIDS 2004;18:767-74.
    CrossRefMedlineWeb of Science
  11. ↵
    1. Nuñez M,
    2. Soriano V
    . Risks and benefits of antiretroviral therapy in HIV-HCV co-infected patients. J Hepatol 2005;42:290-2.
    CrossRefMedlineWeb of Science
  12. ↵
    1. Yoo T,
    2. Donfield S,
    3. Lail A,
    4. Lynn H,
    5. Daar E
    . Effect of hepatitis C virus (HCV) genotype on HCV and HIV-1 disease. J Infect Dis 2005;191:4-10.
    Abstract/FREE Full Text
  13. ↵
    1. Tedeschi R,
    2. Pivetta E,
    3. Zanussi S,
    4. et al
    . Quantification of hepatitis C virus in liver specimens and sera from patients with HIV coinfection by using Versant HCV RNA 3.0 (branched DNA-based) assay. J Clin Microbiol 2003;41:3046-50.
    Abstract/FREE Full Text
  14. ↵
    1. Rubbia-Brandt L,
    2. Fabris P,
    3. Paganin S,
    4. et al
    . Steatosis affects chronic hepatitis C progression in a genotype specific way. Gut 2004;53:406-12.
    Abstract/FREE Full Text
  15. ↵
    1. Bravo A,
    2. Sheth S,
    3. Chopra S
    . Liver biopsy. N Engl J Med 2001;344:495-500.
    CrossRefMedlineWeb of Science
  16. ↵
    1. Afdhal N
    . Diagnosing fibrosis in hepatitis C: is the pendulum swinging from biopsy to blood tests? Hepatology 2003;37:972-4.
    CrossRefMedlineWeb of Science
  17. ↵
    1. Regev A,
    2. Berho M,
    3. Jeffers L,
    4. et al
    . Sampling error and intraobserver variation in liver biopsy in patients with chronic HCV infection. Am J Gastroenterol 2002;97:2614-8.
    CrossRefMedlineWeb of Science
  18. ↵
    1. Sandrin L,
    2. Fourquet B,
    3. Hasquenoph J,
    4. et al
    . Transient elastography: a new non-invasive method for assessment of hepatic fibrosis. Ultrasound Med Biol 2003;29:1705-13.
    CrossRefMedlineWeb of Science
  19. ↵
    1. Ziol M,
    2. Handra-Luca A,
    3. Kettaneh A,
    4. et al
    . Non-invasive assessment of liver fibrosis by measurement of stiffness in patients with chronic hepatitis C. Hepatology 2005;41:48-54.
    CrossRefMedlineWeb of Science
  20. ↵
    1. Castera L,
    2. Vergniol J,
    3. Foucher J,
    4. et al
    . Prospective comparison of transient elastography, fibrotest, APRI and liver biopsy for the assessment of fibrosis in chronic hepatitis C. Gastroenterology 2005;128:43-50.
    CrossRefMedlineWeb of Science
  21. ↵
    1. Bedossa P,
    2. Poynard T
    . An algorithm for grading of activity in chronic hepatitis C. Hepatology 1996;24:289-93.
    CrossRefMedlineWeb of Science
  22. ↵
    1. Soriano V,
    2. Puoti M,
    3. Sulkowski M,
    4. et al
    . Care of patients with hepatitis C and HIV co-infection: updated recommendations from the HIV-HCV International Panel. AIDS 2004;18:1-12.
    CrossRefMedline
  23. ↵
    1. Bissell D
    . Sex and hepatic fibrosis. Hepatology 1999;29:988-9.
    CrossRefMedlineWeb of Science
  24. ↵
    1. Wright M,
    2. Goldin R,
    3. Fabre A,
    4. et al
    . Measurement and determinants of the natural history of liver fibrosis in hepatitis C virus infection: a cross sectional and longitudinal study. Gut 2003;52:574-9.
    Abstract/FREE Full Text
  25. ↵
    1. Cholet F,
    2. Nousbaum J,
    3. Richecoeur M,
    4. et al
    . Factors associated with liver steatosis and fibrosis in chronic hepatitis C patients. Gastroenterol Clin Biol 2004;28:272-8.
    MedlineWeb of Science
  26. ↵
    1. Adinolfi L,
    2. Gambardella M,
    3. Andreana A,
    4. Tripodi M,
    5. Utili R,
    6. Ruggiero G
    . Steatosis accelerates the progression of liver damage of chronic hepatitis C patients and correlates with specific HCV genotype and visceral obesity. Hepatology 2001;33:1358-64.
    CrossRefMedlineWeb of Science
  27. ↵
    1. De Mendoza C,
    2. Soriano V
    . The role of hepatitis C virus (HCV) in mitochondrial DNA damage in HIV/HCV-coinfected individuals. Antivir Ther 2005;10(Suppl 2):109-15.
    MedlineWeb of Science
  28. ↵
    1. Fleming C,
    2. Craven D,
    3. Thornton D,
    4. Tumilty S,
    5. Nunes D
    . Hepatitis C virus and HIV coinfection in an urban population: low eligibility for interferon treatment. Clin Infect Dis 2003;36:97-100.
    Abstract/FREE Full Text
  29. ↵
    1. Rauch A,
    2. Egger M,
    3. Reichen J,
    4. Furrer H
    . Chronic hepatitis C in HIV-infected patients: low eligibility and applicability of therapy with pegylated interferon-α plus ribavirin. The Swiss HIV Cohort Study. J Acquir Immune Defic Syndr 2005;38:238-40.
    CrossRefMedlineWeb of Science
  30. ↵
    1. Day C,
    2. James O
    . Steatohepatitis: a tale of two “hits”? Gastroenterology 1998;114:842-5.
    CrossRefMedlineWeb of Science
  31. ↵
    1. Lonardo A,
    2. Adinolfi L,
    3. Loria P,
    4. Carulli N,
    5. Ruggiero G,
    6. Day C
    . Steatosis and hepatitis C virus: mechanism and significance for hepatic and extrahepatic disease. Gastroenterology 2004;126:586-97.
    CrossRefMedlineWeb of Science
  32. ↵
    1. Nuñez M,
    2. Soriano V
    . Hepatitis C virus (HCV) genotypes and disease progression in HIV/HCV-coinfected patients. J Infect Dis 2005;191:1-3.
    FREE Full Text
  33. ↵
    1. Núñez M,
    2. Rios P,
    3. Martín-Carbonero L,
    4. Pérez-Olmeda M,
    5. González-Lahoz J,
    6. Soriano V
    . Role of hepatitis C virus genotype in the development of severe transaminase elevation after the introduction of antiretroviral therapy. J Acquir Immune Defic Syndr 2002;30:65-8.
    CrossRefMedlineWeb of Science
  34. ↵
    1. Torti C,
    2. Lapadula G,
    3. Puoti M,
    4. et al
    . The influence of genotype 3 hepatitis C virus co-infection on liver enzyme elevation in HIV-positive patients after commencement of a new HAART regimen: results from the EPOKA-MASTER cohort. J Acquir Immune Defic Syndr 2006;41:180-5.
    CrossRefMedlineWeb of Science
    1. Sharma P,
    2. Balan V,
    3. Hernandez J,
    4. et al
    . Hepatic steatosis in hepatitis C virus genotype 3 infection: does it correlate with body mass index, fibrosis, and HCV risk factors? Dig Dis Sci 2004;49:25-9.
    CrossRefMedlineWeb of Science
    1. Hui J,
    2. Sud A,
    3. Farrell G,
    4. et al
    . Chronic hepatitis C virus infection and insulin resistance: how do they interact, and what is the effect on hepatic fibrosis? Gastroenterology 2003;125:1695-704.
    CrossRefMedlineWeb of Science
  37. ↵
    1. Aranzabal L,
    2. Casado J,
    3. Moya J,
    4. et al
    . Influence of liver fibrosis on highly active antiretroviral therapy-associated hepatotoxicity in patients with HIV and hepatitis C virus coinfection. Clin Infect Dis 2005;40:588-93.
    Abstract/FREE Full Text
  38. ↵
    1. Sulkowski M,
    2. Mehta S,
    3. Torbenson M,
    4. et al
    . Hepatic steatosis and antiretroviral drug use among adults coinfected with HIV and hepatitis C virus. AIDS 2005;19:585-92.
    MedlineWeb of Science
    1. Monto A,
    2. Dove L,
    3. Bostrom A,
    4. Kakar S,
    5. Tien P,
    6. Wright T
    . Hepatic steatosis in HIV/hepatitis C coinfection: prevalence and significance compared with hepatitis C monoinfection. Hepatology 2005;42:310-6.
    CrossRefMedlineWeb of Science
    1. Martin-Carbonero L,
    2. Soriano V
    . Interplay between hepatitis C, liver steatosis and antiretroviral therapy in HIV-infected patients. AIDS 2005;19:621-3.
    CrossRefMedlineWeb of Science
  41. ↵
    1. Berger A,
    2. Prondzinski M,
    3. Doerr H,
    4. Rabenau H,
    5. Weber B
    . Hepatitis C plasma viral load is associated with HCV genotype but not with HIV coinfection. J Med Virol 1996;48:339-43.
    CrossRefMedlineWeb of Science
  42. ↵
    1. García F,
    2. Roldán C,
    3. Hernández-Quero J,
    4. et al
    . Relationship between viral genotype and viral load in patients with chronic hepatitis C. Eur J Clin Microbiol Infect Dis 1996;15:884-7.
    CrossRefMedlineWeb of Science
  43. ↵
    1. Poynard T,
    2. Bedossa P,
    3. Opolon P
    . Natural history of liver fibrosis progression in patients with chronic hepatitis C. Lancet 1997;349:825-32.
    CrossRefMedlineWeb of Science
  44. ↵
    1. Alberti A,
    2. Noventa F,
    3. Benvegnu L,
    4. Boccato S,
    5. Gatta A
    . Prevalence of liver disease in a population of asymptomatic persons with hepatitis C virus infection. Ann Intern Med 2002;137:961-4.
    Abstract/FREE Full Text
| Table of Contents

This Article

  1. Clin Infect Dis. (2006) 42 (7): 1032-1039. doi: 10.1086/501021
  1. AbstractFree
  2. » Full Text (HTML)Free
  3. Full Text (PDF)Free

Classifications

Share

  1. Email this article

Navigate This Article

Current Issue

  1. March 1, 2012 54 (5)
  1. Clinical Infectious Diseases
  1. Alert me to new issues

Most