January 3, 2012

Risk Factors for Hepatocellular Carcinoma in a Cohort Infected With Hepatitis B or C

Scott R Walter; Hla-Hla Thein; Heather F Gidding; Janaki Amin; Matthew G Law; Jacob George; Gregory J Dore

Posted: 12/28/2011; J Gastroenterol Hepatol. 2011;26(12):1757-1764. © 2011 Blackwell Publishing

Abstract and Introduction

Abstract

Background and Aim: The incidence of hepatocellular carcinoma (HCC) has increased in Australia in recent decades, a large and growing proportion of which occurs among a population chronically infected with hepatitis B virus (HBV) or hepatitis C virus (HCV). However, risk factors for HCC among these high-risk groups require further characterization.
Methods: We conducted a population-based cohort study using HBV and HCV cases notified to the New South Wales Health Department between 2000 and 2007. These were linked to cause of death data, HIV/AIDS notifications, and hospital records. Proportional hazards regression was used to identify significant risk factors for developing HCC.
Results: A total of 242 and 339 HCC cases were linked to HBV (n = 43 892) and HCV (n = 83 817) notifications, respectively. For both HBV and HCV groups, being male and increasing age were significantly associated with risk of HCC. Increasing comorbidity score indicated high risk, while living outside urban areas was associated with lower risk. Hazard ratios for males were two to three times those of females. For both HBV and HCV groups, cirrhosis, alcoholic liver disease, and the interaction between the two were associated with significantly and considerably elevated risk.
Conclusion: This large population-based study confirms known risk factors for HCC. The association with older age highlights the potential impact of HBV and HCV screening of at-risk groups and early clinical assessment. Additional research is required to evaluate the impact of improving antiviral therapy on HCC risk.

Introduction

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer incidence and mortality worldwide.[1–3] Although less common in Australia than other regions, there has been a marked increase in HCC incidence in recent decades.[4–6] Chronic infection with hepatitis B virus (HBV) or hepatitis C virus (HCV) is the main risk factor for HCC,[7,8] with over 80% of cases worldwide developing in the presence of these infections.[9] The increasing prevalence of chronic viral hepatitis in Australia has been identified as a key driver behind the rising incidence of HCC.[10,11] Other known HCC risk factors include cirrhosis, alcoholic liver disease (ALD), aflatoxin B1,[12] hemochromatosis,[8] HIV,[13] diabetes,[14–16] and HBV/HCV co-infection.[17–20] Increasing age, being male,[21] and certain ethnicities[22] have also been identified as risks, along with lifestyle factors, such as high alcohol intake and smoking. The prevalence of risk factors can vary considerably between geographical regions.[21]

Many published studies have examined risk factors for HCC in various regions of the world,[8,21,23–26] some of which have looked at risk within HBV- or HCV-infected groups.[23–25] However, there are very few studies of HCC risks in the Australian context,[10] and none which quantify risk among HBV- or HCV-infected people at a population level. To this end, we conducted a population-based, retrospective cohort study to identify and quantify risk factors for HCC among an already high-risk group of HBV or HCV infected individuals in New South Wales (NSW), Australia's most populous state.

Methods

Data Sources

The study group consisted of all HBV and HCV notifications recorded in the NSW Notifiable Diseases Database between 1 January 1992 and 31 December 2007. Notification of HBV or HCV infection has been required by law since 1991 (NSW Public Health Act 1991). A notifiable HBV case requires detection of HBV surface antigen or HBV–DNA, while a notifiable HCV case requires detection of anti-HCV antibody and/or HCV-RNA.

The NSW Admitted Patient Data Collection contains information on all hospital admissions occurring in NSW hospitals, public psychiatric hospitals, public multipurpose services, and private day-only procedure centers. It also contains records of NSW residents who were admitted to interstate hospitals. The hospital data were only available for linkage from 1 July 2000. The NSW Central Cancer Registry contains information on all cancers diagnosed and mandatorily reported in NSW since 1972 (Public Health Act 1972). We obtained all HCC records, defined by ICD-O-3 topography code C22.0 and histology codes 81703–81753, which linked with a HBV or HCV record. HIV and AIDS are also legally notifiable conditions in Australia, and new diagnoses are recorded in the National HIV Database (NHD) and the National AIDS Registry (NAR), respectively. The NHD has recorded HIV diagnoses since 1985, and the NAR has recorded AIDS diagnoses since 1982. Both data sources record a four-letter name code in place of full name identifiers.

Linkage

Records of viral hepatitis notifications were probabilistically linked to cancer and hospital records using full name, address, sex, and date of birth identifiers. Linkage of both the HIV and AIDS records to the hepatitis notifications was performed by deterministic linkage using name code, date of birth, and sex only. All linkage was carried out by the NSW Centre for Health Record Linkage[27] using ChoiceMaker software (ChoiceMaker Technologies, New York, NY, USA).

Statistical Methods

Where multiple HBV or HCV records were matched to one individual, the earliest record was used to define date of diagnosis. When defining HBV/HCV co-infection, diagnosis date was defined by the date of the second infection. Since hospital admission data were only available from 1 July 2000, the analysis was restricted to HBV or HCV cases still alive at this date and without any record of HCC diagnosis prior to this date. Although cases with a viral hepatitis notification prior to 1 July 2000 did not have hospital data for the initial period of follow up, the conditions of interest were all chronic and were expected to be recorded in later hospital records as either principal diagnoses or comorbidities. These cases were treated as left truncated, when defining analysis time. Given that a primary objective was to identify factors associated with HCC that could guide chronic viral hepatitis therapeutic intervention and HCC screening, cases diagnosed with HCC within 6 months of their viral hepatitis diagnosis were excluded. Inclusion of "late HCC" diagnoses would also have potentially biased the estimation of HCC incidence. Therefore, follow-up time commenced 6 months after viral hepatitis diagnosis, and ended at the earliest of date of HCC diagnosis or the end of the study period: 31 December 2007.

Summary counts, percentages, and crude person-time rates were generated to characterize the study cohort. Cox proportional hazards models were developed for those with HBV, including HCV co-infection, and separately for those with HCV, including HBV co-infection, where HCC diagnosis was the outcome of interest. Potential covariates considered were sex, remoteness, HBV/HCV co-infection, age group, time period, health insurance status, and Charlson–Deyo comorbidity score, the latter four being treated as time-varying covariates. Remoteness was calculated from postcode of residence at the time of hepatitis notification using concordances defined by the Australian Bureau of Statistics. Comorbidity score was calculated according to the methods described by Charlson et al.[28] and Deyo et al.[29] This involves assigning a severity value if any of a set of predetermined conditions appeared in any diagnosis field for a hospital episode. Based on the sum of these values for a given episode, it is then categorized into one of three groups representing different degrees of comorbidity. Thus, the score reflects both the number of comorbid conditions, as well as their severity. All variables with a univariate log–rank test significant at the 0.20 level were initially chosen for inclusion in each model. Non-significant covariates were then removed from the model until those remaining were significant at the 0.10 level. The removal of each successive covariate was assessed with a likelihood ratio test between successive models and by examining the percentage change in coefficients.[30] Finally, variables that were non-significant in the univariate test were added to see if they became significant when adjusted for other factors. The proportional hazards assumption was assessed via a residual-based test, as described by Grambsch and Therneau.[31] Overall model fit was examined by plotting the Nelson–Aalen cumulative hazards estimates against Cox–Snell residuals and assessing their approximate adherence to the line of equality.

As it was not possible to include hospitalization for specific conditions in the same model as the comorbidity score due to collinearlity, separate models were developed, which replaced the comorbidity score with specific chronic comorbid conditions of interest. These conditions were diabetes, ALD, cirrhosis, hemochromatosis, and HIV. For the first four, a person was flagged as having a certain condition if the diagnosis code appeared in any diagnosis field on any hospital record for that person, while HIV status was determined by the presence of a HIV or AIDS notification record. The same model-building process was followed with the addition of plausible two-way interaction terms involving the conditions of interest. A more relaxed inclusion criterion of 0.15 was used to determine the significance of interaction terms.

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

Results

Study Cohort

There were 43 892 people with HBV monoinfection, and 83 817 with HCV monoinfection in the final study cohort, of which 13 645 (31%) and 35 615 (43%), respectively, had a linked hospital record (Table 1). The median ages at viral hepatitis diagnosis were very similar between the two monoinfected groups, both being just under 35 years. A total of 242 (0.6%) people in the HBV monoinfected group, and 339 (0.4%) in the HCV group, had a linked HCC record, 71% and 80% of whom also had a linked hospital record, respectively. There were 3347 people co-infected with HBV and HCV; 1670 (50%) of these had a linked hospital record, and 23 (0.7%) had a linked HCC record. Those co-infected with HIV made up less than 1% of the cohort and accounted for less than five HCC cases.

The overall crude rate of HCC incidence was significantly higher among those with HBV monoinfection compared to those with HCV monoinfection (9.5 vs 6.9 cases per 10 000 person years, P < 0.001) (Table 2). For both groups, rates increased significantly with age category, were higher among males and among those living in metropolitan areas. People with a comorbidity score of three or more had rates over 15 times higher than people with a comorbidity score of one (HBV 187.0 vs 12.0, HCV 171.5 vs 5.5 per 10 000 person years). Having a hospital record for diabetes, ALD, or cirrhosis was associated with significantly higher crude rates of HCC incidence, particularly cirrhosis, which was associated with more than a 50-fold increase in crude rates for the HBV and HCV monoinfected groups, respectively.

HBV and HCV Proportional Hazards Models, Including Comorbidity Score

For those infected with HBV, including HBV/HCV co-infection, age, sex, time period, remoteness, comorbidity score, and insurance status, were all significant at the univariate level and were included in the initial model. Only age group, sex, remoteness, and comorbidity remained significant at the 0.10 level in the final model after following the model-building process described above. The risk of developing HCC increased with age, with those aged 75 or over having 14 times the risk of those aged under 45 (hazard ratio [HR]: 14.0, 95% confidence interval: 8.6–22.7) (Table 3). The risk for males was threefold that of females (HR: 3.1, 95% CI: 2.3–4.3). Risk increased with increasing comorbidity score, while those not hospitalized had significantly lower risk compared to those in the lowest comorbidity group (HR: 0.4, 95% CI: 0.3–0.5). Those living outside metropolitan areas had lower risk compared to city dwellers (HR: 0.5, 95% CI: 0.3–1.0), although there were only seven cases of HCC in the non-metropolitan group.
For the HCV cohort, the final model included the same four covariates as the HBV model, with the exception that HBV/HCV co-infection was also included. An increase in risk with age was also observed, although with a somewhat steeper gradient of risk than in the HBV model, and with a peak in the 65–74-year age group. Males had just over double the risk of females (HR: 2.3, 95% CI: 1.8–2.9), while the distribution in risk across comorbidity groups was similar to the HBV model. The 39 non-metropolitan HCC cases were also observed to have significantly lower risk (HR: 0.5, 95% CI: 0.4–0.8), and HBV/HCV co-infection was associated with increased risk (HR: 1.6, 95% CI: 1.1–2.5).

HBV and HCV Proportional Hazards Models, Including Chronic Conditions

The final model for both HBV and HCV groups retained the same variables, namely, age, sex, remoteness, health insurance status, ALD, and cirrhosis, as well as the interaction between these two chronic conditions. The only exception was that the HCV model also found HBV/HCV co-infection to be significant (HR: 1.6, 95% CI: 1.1–2.5). Despite crude rates of HCC being much higher among those with diabetes, this risk factor did not remain significant in the model when adjusted for other factors. For insurance status in both models, although most categories were non-significant, removing this variable made a significant difference to the model fit, so its deletion could not be justified. HIV co-infection and hemochromatosis were omitted from both models due to the very small numbers of HCC cases having been hospitalized with these conditions. Age, sex, and remoteness effects were similar to those seen in the models described above; however, the age-related HRs were somewhat amplified (Table 4). Compared to those without hospitalization for major liver disease, those hospitalized with ALD without cirrhosis had a significantly elevated risk (HBV HR: 6.4, 95% CI: 2.6–15.9; HCV HR: 10.8, 95% CI: 7.3–16.1), while those hospitalized with cirrhosis, but not ALD, had even higher risk of HCC (HBV HR: 24.1, 95% CI: 17.8–32.7; HCV HR: 17.9, 95% CI: 13.7–23.4). Among those with HBV, having been hospitalized with both cirrhosis and ALD was associated with further increase in risk (HR: 28.2, 95% CI: 11.3–70.5), but this interaction was slightly less than additive. For those with HCV, the combined effect was somewhat greater (HR: 36.4, 95% CI: 10.8–122.5), which showed that the interaction was more than additive, but less than multiplicative.
Discussion

This study identifies sociodemographic and health factors predictive of developing HCC among a cohort of people with chronic HBV or HCV infection in NSW. The incidence of HCC increased with age and comorbidity score, and was higher among males, metropolitan residents, and those with ALD, and particularly cirrhosis. Older age, being male, and having a high comorbidity score were significantly and independently associated with the risk of HCC. Co-infection with HBV and HCV was associated with increased HCC risk in the HCV cohort, and of all risk factors considered, cirrhosis conferred the greatest additional risk, regardless of infection type.

The risk of HCC was observed to increase significantly with age for both HBV- and HCV-infected groups. Such an increase in risk with age has been widely observed,[32] but in some countries, age-specific incidence peaks in the 60s, rather than late 70 s or beyond, possibly due to variation in the prevalence of certain risk factors between regions.[17,21]

Being male is another well-known risk factor for HCC, although there is considerable regional variation in the relative risk compared to females.[21] While relative risks of males compared to females for HCC among the general population range from close to one to almost nine, in most regions in the world, males have two to four times the risk of females,[21] consistent with our results.

A clear increase in the risk of HCC with comorbidity score was observed for both infection groups. Few studies have assessed the association between comorbidity score and HCC risk, as it is often more informative to examine individual health conditions. Each comorbid condition influences the risk of HCC by varying degrees, and multiple conditions might interact in complex ways. However, in terms of identifying high-risk individuals, the comorbidity score quantifies the combined effect of multiple conditions, without the need to interpret risks associated with multiple factors and their interactions.

A number of papers have reported a twofold to threefold increase in HCC risk due to diabetes,[14–16,26] some of which also found an interaction between viral hepatitis and diabetes.[14,16] While including diabetes in the models suggested an increase in the risk of comparable magnitude, the difference was not sufficiently significant to remain in the final model, suggesting that in our cohort, this is a low-risk condition relative to other factors considered.

Alcohol consumption has been identified as a key risk factor for HCC, interacting synergistically with chronic viral hepatitis infection,[16,33] but relatively few studies have examined the risk associated with ALD.[34] We observed significant risk associated with hospitalization with this condition, possibly through the combined effects of alcohol-related and hepatitis-related liver injury. The observed increased risk of HCC among those with HBV/HCV co-infection is consistent with other studies, which found that the combined effect of the two infections is more than additive, but less than multiplicative.[17,18,20,35]

Cirrhosis is well known as the precursor for the vast majority of chronic viral hepatitis-related HCC cases.[19,36,37] Not surprisingly, our study identified cirrhosis as the strongest predictor of HCC for both HBV and HCV cohorts. Two studies based in Taiwan found a 12-fold and 50-fold increase in risk due to cirrhosis among a HBV-infected cohort.[25,38] Sherman reports a more than 20-fold increase in HCC incidence in people with HCV and cirrhosis, compared to those with HCV alone.[36] The magnitude of these estimates approximately agrees with the very high risk identified in our study. The combined effects of cirrhosis and ALD indicated further amplified risk of HCC, particularly among those with HCV. Having a hospital record for both conditions likely indicates advanced or rapidly-progressing liver disease.

A limitation of this study was the incompleteness of country of birth information in the viral hepatitis notification data, which inhibited analysis of the differential risk of developing HCC between people born in different regions. This is particularly pertinent, given that more than half of the HBV-infected group have immigrated from HBV-endemic countries, such as China and Vietnam,[39,40] while the majority of those with HCV are Australian born.[41] Region of birth might also confound the association between remoteness and HCC, since there are much higher proportions of Asian born people in metropolitan areas than non-metropolitan areas.[42] This is particularly likely to be a factor among the HBV-infected cohort. More limited access to specific HCC diagnostic services in non-metropolitan areas might also be a factor in producing an apparently lower incidence of HCC.

A further limitation was the availability of cirrhosis data only through hospitalization codes, particularly as liver biopsy and hepatic elastography diagnosis are generally undertaken through outpatient services. Also, linked treatment data were not available for this study, which eliminated the possibility of examining the extent to which antiviral therapy reduces HCC risk; however, this might form the basis of future studies when additional data permit.

HCC screening and surveillance among at-risk groups have only relatively recently been shown to improve survival.[43,44] Cases only presenting when symptomatic often have a poorer prognosis and fewer treatment options than those detected in the asymptomatic stage of disease.[24,45] In light of its ability to detect tumors early and improve treatment eligibility and survival, screening and surveillance play a key role in reducing the burden of HCC. However, it is only practiced by some groups in NSW, with less than 20% of HCC cases being identified via surveillance.[45,46] Identifying and quantifying risk factors specific to a population, as we have done, forms an integral part of targeting cost-effective surveillance and provides motivation for more widespread screening of high-risk groups.

Antiviral therapy has been shown to limit the progression of liver disease, and in some HBV cases, can reverse decompensated cirrhosis, considerably reducing the risk of HCC.[37,47] Thus, antiviral therapy of chronic viral hepatitis represents a pivotal pathway for reducing the burden of HCC. This also bolsters the case for increasing treatment uptake in general among those with chronic viral hepatitis infection, given that currently, approximately 5% of HBV-infected people[48] and 1–2% of HCV-infected people[41] receive antiviral therapy. A combination of surveillance and treatment has been shown to be a more cost-effective way to reduce the burden of liver cancer than surveillance alone.[46]

In summary, this study has identified and quantified important risk factors for HCC within a high-risk, population-based cohort. Several key factors emerged as independent and significant risks for HCC. Although some previously-reported risk factors were not significant in our analysis, those that were identified were largely consistent with studies conducted in other regions of the world. The association with older age highlights the potential impact of HBV and HCV screening of at-risk groups and early clinical assessment. Antiviral therapy for chronic viral hepatitis is an important strategy for preventing HCC, and further research is required to quantify its mitigation of HCC risk at a population level in the Australian context.

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Acknowledgments
The authors thank Dr Lee Taylor, Ms Kate Ward, Ms Kim Lim, Ms Narelle Grayson, Ms Hui You, and the staff at the Centre for Health Record Linkage, and Ms Katie Irvine and Ms Anita Bobba for their advice and conducting the data linkage.

SW is supported by the NSW Health Biostatistical Officer Training Program. HHT is currently supported by the Ontario Institute for Cancer Research Health Services Research Program New Investigator Award. JG is supported in part by the Robert W. Storr bequest to the Sydney Medical School Foundation. GD is supported by a NHMRC Practitioner Fellowship. This publication was funded by the Australian Government Department of Health and Ageing and the NSW Cancer Council STREP Grant (SRP08-03).

J Gastroenterol Hepatol. 2011;26(12):1757-1764. © 2011 Blackwell Publishing

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