Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-27T14:33:53.488Z Has data issue: false hasContentIssue false

Hospitalization rates associated with hepatitis B and HIV co-infection, age and sex in a population-based cohort of people diagnosed with hepatitis C

Published online by Cambridge University Press:  19 November 2010

H. F. GIDDING*
Affiliation:
National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia
J. AMIN
Affiliation:
National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia
G. J. DORE
Affiliation:
National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia
M. G. LAW
Affiliation:
National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia
*
*Author for correspondence: Ms. H. F. Gidding, National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Cliffbrook Campus, Building CC4, 45 Beach Street, Coogee, NSW, Australia2034. (Email: [email protected])
Rights & Permissions [Opens in a new window]

Summary

To determine the extent age, sex and co-infection affect morbidity in people infected with hepatitis C virus (HCV), we performed a population-based study linking HCV notifications in New South Wales, Australia with their hospital (July 2000 to June 2006), hepatitis B virus (HBV) and HIV notification, and death records. Poisson models were used to calculate hospitalization rate ratios (RRs) for all-cause, illicit drug and liver-related admissions. Co-infection RRs were used to estimate attributable risk (AR). The 86 501 people notified with HCV contributed 422 761 person-years of observation; 0·8% had HIV, 3·7% HBV, and 0·04% had both. RRs for males were equal to or lower than for females in younger ages, but higher in older ages (P for interaction ⩽0·013). HBV/HIV co-infection resulted in ARs of over 70% for liver disease and 30–60% otherwise. However, at the cohort level the impact was minimal (population ARs 1·3–8·7%). Our findings highlight the importance and success of public health measures, such as needle and syringe exchange programmes, which have helped to minimize the prevalence of co-infection in Australia. The findings also suggest that the age of study participants needs to be considered whenever the burden of HCV-related morbidity is reported by sex. The results are likely to be representative of patterns in hospital-related morbidity for the entire HCV-infected population in Australia and the ARs generalizable to other developed countries.

Type
Original Papers
Copyright
Copyright © Cambridge University Press 2010

INTRODUCTION

Infection with hepatitis C virus (HCV) is known to be associated with increased morbidity compared to the general population [Reference Amin1Reference McDonald6] and certain cofactors are thought to add to this burden. There is good evidence that age at infection, duration of infection, male gender, and co-infection with either HIV or hepatitis B virus (HBV) are predictors of liver disease progression in people with chronic HCV [Reference Dore7, Reference Poynard8]. However, this evidence has mostly come from clinic-based studies (usually cross-sectional), studies of small cohorts infected through transfusion of blood products or injecting drug use (IDU) [Reference Harris9, Reference Thomas10], or using a larger cohort of veterans in the USA [Reference Kramer11] which may not be representative of the general HCV-infected population [Reference Dore7, Reference Kramer11, Reference Fu, Tom and Bird12]. Recent population-based studies examining predictors of excess morbidity have been conducted in Scotland [Reference McDonald13, Reference McDonald14]. However, they did not examine the excess burden associated with HBV co-infection and focused on all-cause morbidity [Reference McDonald13] or first hospital admission (or death) due to decompensated liver disease only [Reference McDonald14]. The aim of this study was, therefore, to determine the relative effect of age, sex and both HIV and HBV co-infection status on all-cause, as well as liver and illicit drug-related, hospitalization rates in all people notified with chronic HCV in New South Wales (NSW), Australia.

Methods

Data sources

Our study cohort included all people notified with HCV infection in NSW (population 7 million), as recorded on the NSW Notifiable Diseases Database (NDD) between 1992 (when personal identifiers were first recorded) and 2006. HCV cases co-infected with HIV and HBV were identified by linkage to NDD notifications for HBV and to NSW data from the National HIV Registry (NHR) and National AIDS Registry (NAR). Under the Public Health Act 1991 all new HBV, HCV, HIV and AIDS diagnoses are notifiable to the NSW Department of Health. HIV infections have been notifiable since 1985 and NAR contains data on all AIDS diagnoses since 1982. The NDD, NHR and NAR records contain demographic information [including full name for NDD and name code (first two letters of surname and given name) for HIV and AIDS notifications] and variables for disease code and diagnosis date.

Hospital admissions for the cohort were obtained from the Admitted Patient Data Collection, a database which covers all in-patient admissions from all public (including psychiatric) and private hospitals in NSW. The data are collected by financial year (1 July to 30 June) of separation (discharge, transfer, death, or change in admission type within the same hospital). Each admission includes demographic and administrative information and diagnosis and procedure fields coded according to the 10th revision of the International Classification of Diseases – Australian Modification (ICD-10-AM). Up to 55 diagnostic codes can be recorded for each admission. For our analysis, admissions were categorized by their principal (first) diagnostic code (used to record the main condition responsible for the admission). Patient name has been recorded since 1 July 2000. For this reason, the study period was limited to separations from 1 July 2000 to 30 June 2006 (the most recent year data were available).

The Registry of Births Deaths and Marriages is a registry of all deaths (based on receipt of a medical certificate of cause of death) in NSW and includes the date of death. We used date of death to determine if and when a person died in order to censor their person-years at risk.

Linkage process

Data linkage was carried out by the Centre for Health Record Linkage (CHeReL) [15]. The NDD, hospitalization and death data were linked using probabilistic record-linkage methods and ChoiceMaker software [16]. Full name on the NDD dataset was then recoded to name code before linkage with the AIDS/HIV registries using deterministic methods based on a 100% match on name code, date of birth and sex.

Exclusions

Cases were excluded if age or sex was missing, and were ineligible if they died before the start of the study period or within 14 days of their diagnosis date, or were diagnosed within 14 days of the end, or after, the study period. All hospital admissions before or beginning within 14 days of diagnosis were excluded to reduce the bias towards higher rates of admission around the time of diagnosis [Reference McDonald6]. Duplicate and nested admissions (i.e. an admission wholly within the date range of another admission) were removed so that there was only one admission (and therefore one principal diagnostic code) for each time period. We also excluded admissions with a principal diagnostic code of extracorporeal dialysis (Z49.1). The high prevalence of HCV in patients undergoing dialysis is already known [Reference Fabrizi17] and dialysis accounted for by far the highest number of admissions in our cohort (17% of all admissions, rate 9·9/100 person-years) [Reference Gidding4] and could therefore subsume any other associations.

Statistical analysis

Rates of admission were calculated using person-years at risk as the denominator. This was calculated for each person as the time 14 days after diagnosis or from the start of the study period (whichever was later) until the end of the study period or death (whichever came first). Hospital admission rate ratios (RRs) with 95% confidence intervals (CIs) were calculated using a random effects Poisson regression model to account for the correlation between hospitalizations for the same person [Reference Kirkwood and Sterne18]. Three outcomes were examined: admission rates for all causes, illicit drug-related, and HCV-related liver disease (non-alcoholic liver disease and liver cancer). Independent risk factors included in each model were age [time dependent, in 15-year age groups (collapsed to 30-year age groups where the number of admissions were small)], sex, and co-infection with HIV and HBV. Each model was also adjusted for calendar year (time dependent). The interaction between age and sex was also investigated as our previous study identified higher admission rates in females than males in young age groups but the opposite trend in older age groups [Reference Gidding4]. There were too few people in the cohort with both HIV and HBV co-infection to investigate the interaction of these terms. The significance of each independent variable including the interaction term was determined using the likelihood ratio test.

The adjusted RRs for HIV and HBV co-infection obtained from the Poisson models were used to estimate the attributable risk per cent (AR%) and population attributable risk per cent (PAR%) using the following formulas [Reference Hennekens and Buring19]:

where Pe is the proportion of the cohort co-infected with either HBV or HIV.

Ethics approval was granted by the University of NSW and the NSW Population and Health Services Research Ethics Committee.

RESULTS

Study cohort

There were 91 986 people notified with HCV in 1992–2006; 4731 (5·1%) were ineligible and 754 (0·9%) of those eligible were missing information for age or sex. The remaining cases comprised the study cohort, which is described in Table 1.

Table 1. Description of hepatitis C cohort

* Study period is the 6 years for which hospital data were available (1 July 2000 to 30 June 2006).

Excludes admissions for extracorporeal dialysis.

Age and sex

There was a significant interaction between age group and sex for all-cause [χ2 (5 d.f.)=292·25, P<0·001], illicit drug-related [χ2 (4 d.f.) = 20·29, P<0·001] and HCV-related liver disease [χ2 (4 d.f) = 12·65, P=0·013] admissions, and so results are presented by age and sex groupings combined (for details of added effect of interaction terms see Supplementary Table S1, available online).

RRs for all-cause hospitalizations were higher in females than in males for the <45 years age group while the reverse was the case for those aged ⩾60 years (Fig. 1). RRs for males increased with age, while RRs for females showed a peak in 15- to 29-year-olds as well as increasing with age in those aged ⩾60 years.

Fig. 1. All-cause hospital admission rate ratios with 95% confidence intervals by age group and sex (adjusted for calendar year, HIV and HBV co-infection).×, Indicates reference group (males aged 30–44 years). ——, Males; – – –, females.

RRs associated with illicit drug-related admissions were highest in the 15–29 years age group for both males and females (Fig. 2). Males and females had similar RRs in age groups <30 years, but in older age groups males had higher RRs.

Fig. 2. Illicit drug-related hospital admission rate ratios with 95% confidence intervals by age group and sex (adjusted for calendar year, HIV and HBV co-infection).×, Indicates reference group (males aged 30–44 years). ——, Males; – – –, females.

RRs for HCV-related liver disease tended to increase with age for both males and females (Fig. 3). However, in the ⩾75 years age group the RR for males was significantly higher than for females.

Fig. 3. Hospital admission rate ratios for HCV-related liver disease with 95% confidence intervals by age group and sex (adjusted for calendar year, HIV and HBV co-infection).×, Indicates reference group (males aged 30–44 years). ——, Males; – – –, females.

Hepatitis B and HIV co-infection

Co-infection with HBV or HIV significantly increased the rate of hospitalization for all causes, illicit drug-related admissions, and especially HCV-related liver disease (Table 2). For all-cause admissions, the RR for HIV co-infection was significantly higher than for HBV co-infection, whereas within the illicit drug-related or HCV-related liver disease admissions the RRs for HBV and HIV were not statistically different. In members of the cohort who were co-infected with either HIV or HBV, a considerable proportion of admissions could be attributed to their co-infection (if it is assumed that co-infection causes the increased rates). For example, 61% of all admissions in the HIV co-infected group could be attributed to their HIV infection. Despite the high AR, however, due to the low prevalence of co-infection (Table 1), especially with HIV, only a small percentage of hospitalizations for the whole cohort could be attributed to co-infection. The exception was HBV co-infection, which was attributed to 8·7% of admissions for HCV-related liver disease in the cohort.

Table 2. Effect of HIV and hepatitis B (HBV) co-infection on rates of hospitalization in people notified with hepatitis C, by type of admission

N, Number of hospitalizations; RR, hospital admission rate ratio; CI, confidence interval; AR, attributable risk; PAR, population attributable risk.

* Crude hospitalization rate per 100 person-years.

Adjusted for calendar year, age and sex.

Excludes admissions for extracorporeal dialysis.

§ HCV-related liver disease=liver cancer (C22) and non-alcoholic liver disease (K71–77 ).

DISCUSSION

Within the NSW cohort of people notified with HCV, co-infection with HIV and HBV, as well as a person's age and sex, impacted significantly on their rate of hospitalization. RRs for all-cause and liver-related morbidity increased with age, while the RR for illicit drug-related admissions was highest in the 15–29 years age group. However, for all three admission types examined there was a significant interaction between age and sex with RRs for males being equal to or lower than for females at younger ages, but higher in older ages. Individuals with HIV or HBV co-infection had significantly increased rates of hospitalization compared to those with HCV mono-infection, especially for liver disease. However, public health measures such as needle and syringe programmes (NSPs) [Reference Dolan20] have helped to minimize the prevalence of co-infection in Australia's HCV-infected population. Therefore the additional burden of morbidity attributable to co-infection in our HCV-infected cohort was minimal.

Over 70% of hospital admissions for liver disease and 30–61% of admissions for all-cause and illicit drug-related conditions in individuals with HBV or HIV co-infection could be attributed to their co-infection status. Hence, at an individual level, co-infection added significantly to the burden of morbidity either directly or because treatment is more difficult [Reference Chu and Lee21]. Therefore ongoing efforts to prevent co-infection, including increased HBV vaccination coverage in IDUs [Reference Miller22] and wider access to NSPs [23] are important public health measures.

Despite the high AR, at a population level fewer than 9% of liver-related, 4% of illicit drug-related and 2% of all-cause admissions in our cohort were attributable to HBV co-infection and the PARs for HIV were less than 3%. This is because of the low prevalence of co-infection in the HCV-infected cohort, which mirrors the low prevalence in Australia's IDU population [Reference Miller22, 24] (who contribute most newly notified cases of HCV in Australia [Reference Gidding25]), but is in contrast with estimates reported from many other countries. HIV has been estimated in population-based HCV cohorts in Denmark (4%) and Scotland (4%) [Reference McDonald5, Reference Omland26], but more widely in IDUs. High prevalence estimates among IDUs have been reported in Eastern Europe (especially Estonia) [Reference Uuskula27], Spain, and South East Asia [Reference Mathers28, Reference Wiessing and Nardone29]. While the USA, China, Italy, India and France have prevalence estimates >10% [Reference Mathers28, Reference Wiessing and Nardone29]. Many of these countries, particularly China, and parts of South East Asia, also have a high prevalence (⩾8%) of chronic HBV in the community [30]. In such countries, the proportion of hospitalizations in the HCV-infected population attributable to co-infection and the overall burden of morbidity is expected to be considerably higher than in Australia.

The low prevalence of HIV and HBV co-infection in Australia's IDU population could be explained by the fact that blood to blood transmission of HIV is less likely than for HCV [Reference Crofts, Aitken and Kaldor31] and that a high proportion of adults infected with HBV clear the infection. In addition, blood screening programmes for HIV and HBV have been in place longer than those for HCV, and HBV is preventable by vaccination. However, it is likely that the introduction of NSPs in Australia in the late 1980s (while the prevalence of HIV and HBV in IDUs remained low but the prevalence of HCV was already >50% [Reference Crofts, Aitken and Kaldor31]) contributed significantly to preventing HIV and HBV co-infection. HIV, HBV and HCV are all blood-borne viruses and therefore can be transmitted via sharing infected needles and other injecting equipment. It is therefore biologically plausible that providing clean syringes would reduce the transmission of these viruses in IDUs. Indeed many studies have shown an impact [Reference Hagan32Reference MacDonald34], although randomized trials have not been conducted due to logistical and ethical concerns. A large ecological study involving 99 cities from around the world found HIV prevalence decreased by 18% per annum on average in cities with NSPs compared to an 8% increase in those that did not [Reference MacDonald34]. However, modelling studies in Australia [Reference Kwon35, Reference Murray36] suggest that at current levels of needle sharing HCV transmission would not be controlled in IDUs due to the higher infectiousness of HCV [Reference Crofts, Aitken and Kaldor31] and its underlying prevalence (60%) [24].

Interestingly, co-infection with HIV or HBV significantly increased the rate of admission for illicit drug-related conditions by 1·5 (AR 35%) and twofold (AR 51%), respectively. Population-based linkage studies examining mortality associated with illicit drug use have also shown higher standardized mortality ratios (SMRs) in cases who were co-infected with HIV and HBV compared to mono-infected cohorts [Reference Amin2, Reference Duberg3, Reference McDonald5]. In addition, clinical studies also suggest an increase in psychiatric and substance-use disorders with HIV co-infection [Reference Cherner37]. The additional hospital-related morbidity associated with co-infection may be partly a surrogate measure for riskier lifestyle behaviours (i.e. riskier IDU practices) which both increase the probability of infection with HIV and HBV (and HCV) and of hospitalization for illicit drug-related causes.

Co-infection with either HIV or HBV increased the rate of admission for liver disease by more than 3·5-fold. These findings are consistent with evidence from clinic-based studies and cohort studies of patients with haemophilia. In addition, a recent population-based study reported HIV co-infection more than doubled the risk of hospitalization for decompensated liver disease [Reference McDonald14]. Co-infection with either HBV or HIV is associated with an increased rate of fibrosis progression and risk of cirrhosis [Reference Benhamou38Reference Zarski42]. In addition, hepatocellular cancer has been reported to occur more often, and follow a more aggressive course, than in HCV mono-infected individuals [Reference Donato, Boffetta and Puoti43Reference Benvegnu45]. HIV co-infected individuals with low CD4 counts have been shown to have a worse prognosis [Reference Benhamou38, Reference Goedert39] but even in the era of highly active antiretroviral therapy (HAART) the risk of cirrhosis was reported to be 1·7 times higher than in HCV mono-infected individuals [Reference Thein41].

We found an interaction between age and sex for all three admission types examined. Females had similar or higher RRs than males in younger age groups, while in older age groups, where morbidity from all-cause and liver disease was greatest, males had significantly higher RRs than their female counterparts. Therefore, the age of study participants needs to be considered whenever the burden of morbidity is reported by sex. Individuals infected at an older age or for a longer duration have been shown to have a higher rate of fibrosis progression [Reference Poynard8, Reference Thomas10, Reference Ostapowicz46, Reference Thein47]. We were unable to measure these risk factors separately. However, a large cross-sectional study showed that, regardless of the duration of infection, the risk of cirrhosis increased significantly after the age of 50 years [Reference Poynard8], and our results are consistent with these findings. The divergence between males and females at older ages, especially for liver-related admissions, is consistent with previous studies showing that the RR of fibrosis progression in males is higher than for females, but mostly for developing severe fibrosis after 20 years of infection [Reference Poynard8, Reference Benvegnu45].

The results of our study need to be interpreted in the context of some limitations. First, being a population-based study, there were only a few patient-specific risk factors available for analysis. Therefore, we were unable to control for potential confounders such as alcohol use and ethnicity. However, previous studies indicate that alcohol use is similar in mono-infected and HIV or HBV co-infected patients [Reference Omland26, Reference Benhamou38], and in an Australian study there were no differences in fibrosis progression rates by ethnicity [Reference Danta48]. A second limitation is that not all cases of HBV and HIV co-infection in the cohort would have been identified. A high proportion of the cohort are likely to have been screened for HIV and HBV [49], but identifiers for matching HIV cases were not complete. However, unidentified co-infections would only lead to an underestimate of the true RR. Another limitation is that hospital data with identifiers for linkage were only available for a 6-year period from June 2000. A small proportion (2·3%) of the notified cases had died prior to this, so our ‘survivor cohort’ may have underestimated hospital-related morbidity for all notified cases. Finally, we were unable to exclude anti-HCV antibody-positive cases who cleared their infection. HIV co-infection is associated with an increased risk of chronic HCV infection [Reference Thomas10]. However, it is estimated that more than 70% of HCV infections are chronic [Reference Micallef, Kaldor and Dore50], regardless of their co-infection status, and therefore the additional risk due to co-infection is likely to be minimal. In addition, few patients are likely to have cleared their HCV infection following antiviral therapy; only 1·4% of those living with HCV were estimated to have received treatment in 2006 [Reference Gidding25].

To conclude, in our population-based cohort of people with HCV, an individual's age, sex and HIV/HBV co-infection status impacted significantly on their rate of hospitalization. The low prevalence of co-infection meant that the overall contribution of HIV and HBV to morbidity in our cohort was minimal. However, the high RRs indicate efforts to minimize HIV and HBV transmission, and improve HBV vaccine uptake in people with chronic HCV, are important. We found an interaction between age and sex with RRs for all-cause and liver-related hospitalizations highest in older men. The findings suggest that the burden of HCV-related morbidity in NSW will increase as the predominantly middle-aged male cohort move into age groups with higher hospitalization rates.

NOTE

Supplementary material accompanies this paper on the Journal's website (http://journals.cambridge.org/hyg).

ACKNOWLEDGEMENTS

The authors thank Lee Taylor, Kim Lim, and the staff at the CHeReL (especially Katie Irvine, Anita Bobba, and Glenda Lawrence) for their advice and for conducting the data linkage. The NSW Department of Health, especially Kate Ward, are acknowledged as the data custodians and for their advice. We acknowledge the University of New South Wales for a Health Data Linkage grant to support the cost of record linkage. The National Centre in HIV Epidemiology and Clinical Research is funded by the Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, The University of New South Wales. The views expressed in this publication do not necessarily represent the position of the Australian Government.

DECLARATION ON INTEREST

None.

References

REFERENCES

1.Amin, J, et al. Cancer incidence in people with hepatitis B or C infection: a large community-based linkage study. Journal of Hepatology 2006; 45: 197203.CrossRefGoogle ScholarPubMed
2.Amin, J, et al. Causes of death after diagnosis of hepatitis B or hepatitis C infection: a large community-based linkage study. Lancet 2006; 368: 938945.CrossRefGoogle ScholarPubMed
3.Duberg, A-S, et al. Cause of death in individuals with chronic HBV and/or HCV infection, a nationwide community-based register study. Journal of Viral Hepatitis 2008; 15: 538550.CrossRefGoogle ScholarPubMed
4.Gidding, HF, et al. Hospital-related morbidity in people notified with hepatitis C; a population-based record linkage study in New South Wales, Australia. Journal of Hepatology 2010; 53: 4349.CrossRefGoogle ScholarPubMed
5.McDonald, SA, et al. A population-based record linkage study of mortality in hepatitis C-diagnosed persons with or without HIV coinfection in Scotland. Statistical Methods in Medical Research 2009; 18: 271283.CrossRefGoogle ScholarPubMed
6.McDonald, SA, et al. A record-linkage study of the development of hepatocellular carcinoma in persons with hepatitis C infection in Scotland. British Journal of Cancer 2008; 99: 805810.CrossRefGoogle ScholarPubMed
7.Dore, GJ, et al. Is severe liver disease a common outcome for people with chronic hepatitis C? Journal of Gastroenterology and Hepatology 2002; 17: 423430.CrossRefGoogle ScholarPubMed
8.Poynard, T, et al. Rates and risk factors of liver fibrosis progression in patients with chronic hepatitis C. Journal of Hepatology 2001; 34: 730739.CrossRefGoogle ScholarPubMed
9.Harris, HE, et al. Survival of a national cohort of hepatitis C virus infected patients, 16 years after exposure. Epidemiology and Infection 2006; 134: 472477.Google ScholarPubMed
10.Thomas, DL, et al. The natural history of hepatitis C virus infection: host, viral, and environmental factors. Journal of the American Medical Association 2000; 284: 450456.Google ScholarPubMed
11.Kramer, JR, et al. The effect of HIV coinfection on the risk of cirrhosis and hepatocellular carcinoma in U.S. veterans with hepatitis C. American Journal of Gastroenterology 2005; 100: 5663.CrossRefGoogle ScholarPubMed
12.Fu, B, Tom, BD, Bird, SM. Re-weighted inference about hepatitis C virus-infected communities when analysing diagnosed patients referred to liver clinics. Statistical Methods in Medical Research 2009; 18: 303320.Google ScholarPubMed
13.McDonald, SA, et al. Excess morbidity in the hepatitis C-diagnosed population in Scotland, 1991–2006. Epidemiology and Infection 2010 (in press).Google ScholarPubMed
14.McDonald, SA, et al. Hospitalization of hepatitis C-diagnosed individuals in Scotland for decompensated cirrhosis: A population-based record-linkage study. European Journal of Gastroenterology and Hepatology 2010; 22: 4957.CrossRefGoogle ScholarPubMed
15.CHeReL. The Centre for Health Record Linkage (www.cherel.org.au). Accessed 28 September 2009.Google Scholar
16.ChoiceMaker Technologies Inc. ChoiceMaker software. New York, USA.Google Scholar
17.Fabrizi, F, et al. Hepatitis C virus infection and the dialysis patient. Seminars in Dialysis 2007; 20: 416422.CrossRefGoogle ScholarPubMed
18.Kirkwood, BR, Sterne, JAC. Essential Medical Statistics, 2nd edn. Malden, Massachusetts: Blackwell Science Ltd, 2003.Google Scholar
19.Hennekens, CH, Buring, JE. Epidemiology in Medicine, 1st edn. Boston: Little Brown and Co., 1987.Google Scholar
20.Dolan, K, et al. Needle and syringe programs: a review of the evidence. Canberra: Australian Government Department of Health and Ageing, 2005.Google Scholar
21.Chu, C-J, Lee, S-D. Hepatitis B virus/hepatitis C virus coinfection: epidemiology, clinical features, viral interactions and treatment. Journal of Gastroenterology and Hepatology 2008; 23: 512520.CrossRefGoogle ScholarPubMed
22.Miller, ER, et al. Markers and risk factors for HCV, HBV and HIV in a network of injecting drug users in Melbourne, Australia. Journal of Infection 2009; 58: 375382.CrossRefGoogle Scholar
23.National Centre in HIV Epidemiology and Clinical Research. Return on investment 2: evaluating the cost-effectiveness of needle and syringe programs in Australia, 2009. Sydney: National Centre in HIV Epidemiology and Clinical Research, The University of NSW, 2009.Google Scholar
24.National Centre in HIV Epidemiology and Clinical Research. Australian NSP survey national data report, 2005–2009. Sydney: National Centre in HIV Epidemiology and Clinical Research, The University of NSW, 2010.Google Scholar
25.Gidding, HF, et al. The epidemiology of hepatitis C in Australia: notifications, treatment uptake and liver transplantations, 1997–2006. Journal of Gastroenterology and Hepatology 2009; 24: 16481654.CrossRefGoogle ScholarPubMed
26.Omland, LH, et al. The impact of HIV-1 co-infection on long-term mortality in patients with hepatitis C: a population-based cohort study. HIV Medicine 2009; 10: 6571.CrossRefGoogle ScholarPubMed
27.Uuskula, A, et al. High-prevalence and high-estimated incidence of HIV infection among new injecting drug users in Estonia: need for large scale prevention programs. Journal of Public Health 2008; 30: 119125.CrossRefGoogle ScholarPubMed
28.Mathers, BM, et al. Global epidemiology of injecting drug use and HIV among people who inject drugs: a systematic review. Lancet 2008; 372: 17331745.CrossRefGoogle ScholarPubMed
29.Wiessing, L, Nardone, A. Ongoing HIV and viral hepatitis infections in IDUs across the EU, 2001–2005. Eurosurveillance 2006; 11: E061123.2.Google ScholarPubMed
30.CDC. Travelers' health, yellow book. Atlanta, GA: US Department of Health and Human Services, 2008.Google Scholar
31.Crofts, N, Aitken, CK, Kaldor, JM. The force of numbers: why hepatitis C is spreading among Australian injecting drug users while HIV is not. Medical Journal of Australia 1999; 170: 220221.CrossRefGoogle ScholarPubMed
32.Hagan, H, et al. Reduced risk of hepatitis B and hepatitis C among injection drug users in the Tacoma syringe exchange program. American Journal of Public Health 1995; 85: 15311537.CrossRefGoogle ScholarPubMed
33.Hurley, SF, Jolley, DJ, Kaldor, JM. Effectiveness of needle-exchange programmes for prevention of HIV infection. Lancet 1997; 349: 17971800.CrossRefGoogle ScholarPubMed
34.MacDonald, M, et al. Effectiveness of needle and syringe programmes for preventing HIV transmission. International Journal of Drug Policy 2003; 14: 353357.Google Scholar
35.Kwon, JA, et al. The impact of needle and syringe programs on HIV and HCV transmissions in injecting drug users in Australia: a model-based analysis. Journal of Acquired Immune Deficiency Syndromes 2009; 51: 462469.CrossRefGoogle Scholar
36.Murray, JM, et al. The impact of behavioural changes on the prevalence of human immunodeficiency virus and hepatitis C among injecting drug users. International Journal of Epidemiology 2003; 32: 708714.CrossRefGoogle ScholarPubMed
37.Cherner, M, et al. Hepatitis C augments cognitive deficits associated with HIV infection and methamphetamine. Neurology 2005; 64: 13431347.CrossRefGoogle ScholarPubMed
38.Benhamou, Y, et al. Liver fibrosis progression in human immunodeficiency virus and hepatitis C virus coinfected patients. The Multivirc Group. Hepatology 1999; 30: 10541058.CrossRefGoogle Scholar
39.Goedert, JJ, et al. End-stage liver disease in persons with hemophilia and transfusion-associated infections. Blood 2002; 100: 15841589.Google ScholarPubMed
40.Sagnelli, E, et al. Virologic and clinical expressions of reciprocal inhibitory effect of hepatitis B, C, and delta viruses in patients with chronic hepatitis. Hepatology 2000; 32: 11061110.CrossRefGoogle Scholar
41.Thein, H-H, et al. Natural history of hepatitis C virus infection in HIV-infected individuals and the impact of HIV in the era of highly active antiretroviral therapy: a meta-analysis. AIDS 2008; 22: 19791991.CrossRefGoogle ScholarPubMed
42.Zarski, JP, et al. Characteristics of patients with dual infection by hepatitis B and C viruses. Journal of Hepatology 1998; 28: 2733.CrossRefGoogle ScholarPubMed
43.Donato, F, Boffetta, P, Puoti, M. A meta-analysis of epidemiological studies on the combined effect of hepatitis B and C virus infections in causing hepatocellular carcinoma. International Journal of Cancer 1998; 75: 347354.3.0.CO;2-2>CrossRefGoogle Scholar
44.Puoti, M, et al. Hepatocellular carcinoma in HIV-infected patients: epidemiological features, clinical presentation and outcome. AIDS 2004; 18: 22852293.CrossRefGoogle ScholarPubMed
45.Benvegnu, L, et al. Concurrent hepatitis B and C virus infection and risk of hepatocellular carcinoma in cirrhosis. A prospective study. Cancer 1994; 74: 24422448.3.0.CO;2-#>CrossRefGoogle Scholar
46.Ostapowicz, G, et al. Role of alcohol in the progression of liver disease caused by hepatitis C virus infection. Hepatology 1998; 27: 17301735.CrossRefGoogle ScholarPubMed
47.Thein, H-H, et al. Estimation of stage-specific fibrosis progression rates in chronic hepatitis C virus infection: a meta-analysis and meta-regression. Hepatology 2008; 48: 418431.CrossRefGoogle ScholarPubMed
48.Danta, M, et al. Factors associated with severity of hepatic fibrosis in people with chronic hepatitis C infection. Medical Journal of Australia 2002; 177: 240245.CrossRefGoogle ScholarPubMed
49.National Centre in HIV Epidemiology and Clinical Research. Australian NSP survey national data report, 2004–2008. Sydney: National Centre in HIV Epidemiology and Clinical Research, The University of NSW, 2008.Google Scholar
50.Micallef, JM, Kaldor, JM, Dore, GJ. Spontaneous viral clearance following acute hepatitis C infection: a systematic review of longitudinal studies. Journal of Viral Hepatitis 2006; 13: 3441.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Description of hepatitis C cohort

Figure 1

Fig. 1. All-cause hospital admission rate ratios with 95% confidence intervals by age group and sex (adjusted for calendar year, HIV and HBV co-infection).×, Indicates reference group (males aged 30–44 years). ——, Males; – – –, females.

Figure 2

Fig. 2. Illicit drug-related hospital admission rate ratios with 95% confidence intervals by age group and sex (adjusted for calendar year, HIV and HBV co-infection).×, Indicates reference group (males aged 30–44 years). ——, Males; – – –, females.

Figure 3

Fig. 3. Hospital admission rate ratios for HCV-related liver disease with 95% confidence intervals by age group and sex (adjusted for calendar year, HIV and HBV co-infection).×, Indicates reference group (males aged 30–44 years). ——, Males; – – –, females.

Figure 4

Table 2. Effect of HIV and hepatitis B (HBV) co-infection on rates of hospitalization in people notified with hepatitis C, by type of admission

Supplementary material: File

Gidding supplementary material

Tables.doc

Download Gidding supplementary material(File)
File 110.6 KB