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Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

The potential impact of long-term antiviral therapy on the burden of chronic hepatitis B has hardly been documented. The aim of this study was to estimate the effects of prolonged antiviral therapy and antiviral resistance on the mortality and morbidity of active chronic hepatitis B patients. A population cohort of chronic hepatitis B patients in the Netherlands was constructed and stratified according to 10-year age groups, prevalence of hepatitis B surface antigen, hepatitis B virus DNA level, alanine aminotransferase level, hepatitis B e antigen status, and presence of cirrhosis. A Markov model was created to mathematically simulate the cohort's progression through a finite series of health states. The analysis was performed on the basis of four scenarios: natural history, long-term therapy with a high-resistance profile drug without or with salvage, and therapy with a low-resistance profile drug. It has been estimated that there were 64,000 people (0.4%) suffering from chronic hepatitis B infection in the Netherlands in 2005, with 6521 (10%) of them having high viremia and elevated alanine aminotransferase levels. Within a 20-year period, 1725 (26%) of the 6521 patients in the active chronic hepatitis B cohort will die because of liver-related causes. Of the 5685 without cirrhosis at entry, 1671 (29%) will develop cirrhosis. Of those 836 with cirrhosis at entry, 619 (74%) will die within a 20-year period. If this active chronic hepatitis B cohort is fully detected and treated, mortality related to liver disease can be reduced by 80% if a low-resistance profile drug is chosen from the start. The effect is due to both the reduction in complications of cirrhosis and the prevention of the development of cirrhosis. Conclusion: Long-term antiviral therapy with a strategy that minimizes or controls resistance will have a major preventive effect on liver-related mortality and morbidity. (HEPATOLOGY 2009.)

Worldwide, about 360 million people have a chronic hepatitis B (CHB) infection, and each year, 500,000 to 700,000 deaths are estimated to arise from hepatitis B virus (HBV)–related cirrhosis and hepatocellular carcinoma (HCC); therefore, CHB ranks as the 10th leading cause of death worldwide.1 Most HBV-related deaths occur in developing countries. However, in many developed countries, mortality from hepatitis B–related cirrhosis and HCC is also substantial and exceeds that of other infectious causes, including human immunodeficiency virus.2, 3

Vaccination is often seen as the key intervention to address the problem of HBV-related mortality over time. Although HBV vaccination programs clearly contribute to the reduction of new cases of HBV infection,4 vaccination does not have any impact on preexisting CHB. Antiviral therapy is the only option to control and prevent progression of disease in patients with active CHB. Evidence has accrued for the efficacy of continuous nucleot(s)ide analogue therapy, which provides highly effective HBV suppression.5–7 However, antiviral therapy has its limitations; with long-term use, it can be associated with the development of viral resistance that eventually can create serious clinical problems.5, 8

Public health planners would benefit from knowing the possible future outcome of antiviral therapy in active CHB infection in terms of reductions in morbidity and mortality and the impact of antiviral resistance in a low endemic country with migration from highly endemic countries. The impact of antiviral therapy can be assessed in a mathematical model, with cohort studies providing progression rate estimates for the natural history, and information on the outcome of treatment with different antiviral drugs from clinical trials is now available. The aim of this study was to quantify with a mathematical model the morbidity and mortality of active CHB infection and to evaluate the potential impact of long-term nucleot(s)ide analogue therapy and antiviral resistance in a population of active CHB patients for a median follow-up period of 20 years.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Cohort Definition

A population cohort of CHB patients was constructed with the recently updated age-stratified prevalence of hepatitis B surface antigen (HBsAg) in the Dutch population.9 We projected the age-stratified HBsAg prevalence to the total Dutch population, which was 16 million in 2005 (Statistics Netherlands).10

The HBsAg-positive cohort was first divided into two groups, active CHB and inactive CHB, based on hepatitis B e antigen (HBeAg) status, HBV DNA level, and serum alanine aminotransferase (ALT) level. The age-specific distribution of these factors was derived from a large database with 479 newly diagnosed CHB patients who were seen at the Municipal Public Health Service (Rotterdam-Rijnmond, the Netherlands).11 The differentiation between active CHB and inactive CHB is essential because progression of the disease is different in these two groups. Patients with high HBV DNA levels (HBV DNA ≥ 104 copies/mL for HBeAg-negatives and ≥ 105 for HBeAg-positives) and elevated ALT (>2 times the upper limit of normal) are classified as having active CHB, have potentially progressive liver disease, and are candidates for HBV antiviral therapy,12, 13 whereas those with low or undetectable HBV DNA and normal ALT levels usually are inactive HBsAg carriers with a low risk of disease progression.

Lastly, we classified the active CHB patients into two categories, with cirrhosis and without cirrhosis, using age group–specific proportions from large HBeAg-positive and HBeAg-negative clinical trials, respectively.14, 15

Markov Model

A Markov mathematical simulation was used to model the outcome of the Dutch cohort of treatment-naïve active CHB patients with high viremia for each age group over a time period of 20 years, which is sufficient time to allow for all possible HBV-related outcomes (development of cirrhosis, liver failure, HCC, and death) to occur. The model describes disease progression and determines the long-term morbidity and mortality of the cohort during follow-up. The model uses annual probabilities of transition from CHB to virological response and of progression to cirrhosis, decompensated liver disease or HCC, and finally death; these were obtained mostly from systematic reviews published in the literature (Tables 1 and 2).16–26 These include both cohort studies describing the natural history of CHB and clinical trials reporting the effect of treatment. As the probability estimates for progression from chronic CHB are clearly different in younger patients and adults, the cohort was split by age, with age groups of 0 to 24 years and 25 to 65+ years. When progression rates were reported, these were transformed into annual probabilities with a standard formula:

  • equation image

where P is the probability, e is the base of the natural logarithm, r is the event rate, and t is the time interval.27 The term morbidity was defined as events related to decompensated cirrhosis, HCC, and liver transplantation, whereas hepatic death was death related to liver failure or other liver-related complications. Other causes of death not related to liver disease are included in the model as age-specific mortality rates derived from Statistics Netherlands.10 Mortality is the model's major outcome, but the expected number of cirrhosis, decompensated cirrhosis, HCC, and liver transplant cases is also quantified. The model was built with TreeAge Pro 2006 (TreeAge Software, Inc., Williamstown, MA).

Table 1. Annual Transition Estimates of the Natural History of Chronic Hepatitis B by Initial State and Age Group
Initial StateOutcomeAge Group: 0-24 YearsAge Group: 25-65+ Years
Estimate (%)*ReferenceEstimate (%)*Reference
  • Abbreviation: HBV, hepatitis B virus.

  • *

    Ranges are shown in parentheses.

Chronic hepatitis B e+Spontaneous virological response9.4 (8.3-23)22, 236.9 (2.0-23)16, 17
 Cirrhosis0.1 (0.0-0.1)22, 232.7 (1.6-3.8)21
 Hepatocellular carcinoma0.1 (0.0-0.1)22, 230.4 (0.3-0.6)21
 Chronic hepatitis B e−0.4 (0.2-0.6)22, 231.9 (1.0-3.8)21
Chronic hepatitis B e−Spontaneous virological response9.4 (8.3-11)22, 231.6 (0.0-11)16, 17
 Cirrhosis0.1 (0.0-0.1)22, 236.2 (2.8-9.7)21
 Hepatocellular carcinoma0.1 (0.0-0.1)22, 230.4 (0.3-0.6)21
Cirrhosis e+Decompensated cirrhosis3.9 (2.0-7.9)24–263.9 (2.0-7.9)24–26
 Hepatocellular cancer1.8 (0.9-3.8)24–261.8 (0.9-3.8)24–26
 HBV-related death3.1 (3.1-3.8)21, 24–263.1 (3.1-3.8)21, 24–26
Cirrhosis e−Decompensated cirrhosis2.7 (1.4-5.4)24–262.7 (1.4-5.4)24–26
 Hepatocellular cancer2.9 (1.0-5.6)24–262.9 (1.0-5.6)24–26
 HBV-related death3.1 (3.1-3.8)21, 24–263.1 (3.1-3.8)21, 24–26
Decompensated cirrhosisLiver transplantation3.3 (1.0-8.4)28, 293.3 (1.0-8.4)28, 29
 HBV-related death26 (15-62)2126 (15-62)21
Hepatocellular carcinomaLiver transplantation1.2 (0.2-5.0)28, 291.2 (0.2-5.0)28, 29
 HBV-related death35 (20-60)16, 1735 (20-60)16, 17
Liver transplantHBV-related death6.6 (2.0-12)16, 176.6 (2.0-12)16, 17
Table 2. Treatment-Related Annual Transition Estimates
Initial StateOutcomeEstimate (%)
High-Resistance Profile DrugLow-Resistance Profile DrugSalvage Therapy
HBeAg+HBeAg−HBeAg+HBeAg−HBeAg+HBeAg−
  • Estimates were taken from Kanwal et al.16, 17

  • Abbreviations: CHB, chronic hepatitis B; HBeAg, hepatitis B e antigen; HBV, hepatitis B virus.

  • *

    Initial therapy was the first 12 months (48 weeks) of therapy.

  • Estimates were calculated under the assumption that the natural progression rates of chronic hepatitis B taken from Kanwal et al.16, 17 are reduced by antiviral therapy. Similar to Kanwal's assumption of no progression of disease in HBeAg seroconversion, we assumed no progression of disease when HBV DNA was undetectable by polymerase chain reaction. In the studies by Chang et al.18 and Lai et al.,19 full suppression of HBV DNA was observed in 80% with a high-resistance profile drug and in 90% with a low-resistance profile drug. We took these percentages for our calculations.

  • Estimates were based on the reduction of progression rates by nucleoside analogue therapy of 50%.5

  • §

    Liver transplantation estimates for the Netherlands.

  • Estimates were taken from recent clinical trials by Chang et al.,18 Lai et al.,19 and Colonno et al.20

CHB: initial therapy*Sustained virological response201022111210
 Cirrhosis0.51.20.20.60.51.2
 Hepatocellular carcinoma0.20.20.20.20.20.2
CHB: long-term therapySustained virological response241027111210
 Cirrhosis0.51.20.20.60.51.2
 Resistance2323111.31.3
 Hepatocellular carcinoma0.20.20.20.20.20.2
Resistant CHB: long-term therapySustained virological response4.5050.54.50
 Cirrhosis2.76.22.76.22.76.2
 Hepatocellular carcinoma0.40.40.40.40.40.4
Cirrhosis: initial therapySustained virological response201022111210
 Hepatocellular carcinoma0.91.50.91.50.91.5
Cirrhosis: long-term therapySustained virological response2412711121
 Resistance221155
 Decompensated cirrhosis1.91.91.91.91.91.9
 Hepatocellular carcinoma1.61.61.61.61.61.6
 HBV-related death2.42.42.42.42.42.4
Resistant cirrhosis: long-term therapySustained virological response4.5050.54.50
 Decompensated cirrhosis7.97.97.97.97.97.9
 Hepatocellular carcinoma1.82.91.82.91.82.9
 HBV-related death3.13.13.13.13.13.1
Decompensated cirrhosisLiver transplantation§3.33.33.33.33.33.3
 HBV-related death262626262626
Hepatocellular carcinomaLiver transplantation§1.21.21.21.21.21.2
 HBV-related death353535353535
Liver transplantationHBV-related death6.66.66.66.66.66.6

Scenario Analyses

Four different scenarios were analyzed in the study. In the first scenario, the natural history of active CHB was simulated: patients received all medical care except antiviral medication to suppress the viral infection. In the second scenario, patients received antiviral treatment with a high-resistance profile drug.5 In the third scenario, patients received the high-resistance profile drug and salvage therapy17 upon the development of resistance. In a fourth scenario, patients received antiviral medication with a low-resistance profile.20 In all four scenarios, we followed the cohort over a period of 20 years through a series of Markov cycles governing patients' transitions between relevant health states.

Scenario 1: Natural History.

In this scenario, active CHB patients progressed according to the natural history; annual rates of progression derived from systematic reviews were followed (Table 1).16, 17Spontaneous virological response was defined as seroconversion to antibody against hepatitis B e antigen (anti-HBe) for HBeAg-positive patients and as persistent HBV DNA suppression and ALT normalization for HBeAg-negative patients. Deviations in the transmission estimates from Kanwal et al.16, 17 were introduced when new information on the progression rates of specific disease states or the impact of antiviral drugs became available. Such deviations are mentioned in the text and in Table 2.

The probabilities of receiving a liver transplant for decompensated cirrhosis and liver cancer were calculated on the basis of data from the European Liver Transplant Registry and the Dutch Transplantation Organization.28, 29 Yearly, four liver transplants are estimated to take place because of liver cancer, 80% of which is HCC. This corresponds to an annual probability of receiving a liver transplant for liver cancer of 1.2% as 264 cases of HCC were reported in 2005. The annual probability of receiving a liver transplant for decompensated cirrhosis was calculated to be 3.3%; this was based on an estimated number of 300 cases of decompensated cirrhosis and 10 liver transplants for this condition.

Scenario 2: High-Resistance Profile Drug.

In this scenario, patients received long-term therapy with the first licensed antiviral HBV drug, which is associated with a high incidence of resistance5; such monotherapy is still being practiced in many countries with limited resources.30 In HBeAg-positive patients, virological response was defined as HBe antigen loss and development of anti-HBe. In HBeAg-negative patients, virological response was defined as HBV DNA levels undetectable by polymerase chain reaction. We assigned different rates of virological response under long-term therapy between resistant and nonresistant patients (Table 2). Following current practice guidelines, we assigned patients who did not respond to initial therapy or who experienced relapse after initial response to long-term therapy.

According to the assumptions in the systematic reviews,16, 17 the disease stops progressing in patients who develop virological response, whereas in cases of nonresponse and viral resistance, the disease progresses as in the natural history. However, the rate of progression from compensated cirrhosis to decompensated cirrhosis is higher in patients presenting with resistance versus those following the natural history.17

Scenario 3: High-Resistance Profile Drug Followed by Salvage Therapy.

In this scenario, the same high-resistance profile drug used in scenario 2 was given. Once resistance occurred, patients were salvaged by the addition of a second antiviral drug with potency against the resistant strain (salvage therapy).17 Patients without resistance continued to receive the initial drug.

Scenario 4: Low-Resistance Profile Drug.

The same patient management strategy used in scenario 2 was applied. The annual probability of resistance developing in those receiving a low-resistance profile drug was much lower than that in scenario 2 and was set at 1% per year on the basis of a recent study that reported data after 4 years of follow-up.20 The treatment-related probability estimates are shown in Table 2.

Sensitivity Analysis

To study the robustness of our results, we performed a sensitivity analysis on the low and high ranges of the transition estimates in the natural history scenario (Table 1). First, a so-called best case scenario was assessed by the application of the high ranges of progression to spontaneous virological response and by the application of the low ranges to the estimates of disease progression. Second, a worst case scenario was assessed by the application of the low progression rates to spontaneous virological response and by the application of the high ranges to the disease progression estimates.

Our assumption that disease progression to decompensated cirrhosis is higher in patients with cirrhosis who develop resistance versus patients who progress according to the natural history might underestimate the efficacy of the high-resistance profile drug. To judge the impact of this possible underestimation, we calculated liver-related mortality under the assumption that progression from cirrhosis to decompensated cirrhosis in the case of resistance equals the progression in natural history.

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Cohorts and Natural History

Table 3 shows the total population of the Netherlands in 2005 with the age-specific prevalence of HBsAg. Around 64,000 individuals (0.4% of the total population) were estimated to be HBsAg carriers, with 10,802 (17%) of them having HBeAg-positive CHB and 53,046 (83%) having HBeAg-negative CHB. The total number of patients with active CHB was 6521 or 10% of the total HBsAg-positive cohort, 26% of the HBeAg-positives, and 7% of the HBeAg-negatives. The proportion of cirrhosis increased by age: from 2% to 34% among HBeAg-positive CHB patients and from 5% to 56% among HBeAg-negative CHB patients.

Table 3. Age Group–Specific Distribution of Chronic Hepatitis B in the Netherlands by HBeAg and Stage of Liver Disease
Age Group (Years)PopulationHBsAg+ (%)HBeAg+HBeAg−Active CHBCirrhosisChronic Hepatitis (No Cirrhosis)
HBeAg+HBeAg−HBeAg+ (%)HBeAg− (%)HBeAg+HBeAg−
  1. Abbreviations: CHB, chronic hepatitis B; HBeAg, hepatitis B e antigen; HBsAg, hepatitis B surface antigen.

<153,009,0002,708 (0.09)8121,8962111334 (2)7 (5)207126
15-241,948,00014,415 (0.74)4,32510,0911,12470622 (2)35 (5)1,102671
25-342,185,00010,051 (0.46)2,0108,04152356331 (6)39 (7)491524
35-442,622,00016,519 (0.63)2,64313,87668797148 (7)146 (15)639825
45-542,315,00016,437 (0.71)82215,6152141,09353 (25)306 (28)160787
55-641,938,0002,713 (0.14)1902,5234917716 (33)90 (51)3387
65+2,288,0001,005 (0.08)01,0050700 (0)39 (56)031
Total16,305,00063,848 (0.39)10,80253,0462,8083,713176 (6)663 (18)2,6333,051
Natural History of the Active CHB Cohort.

The estimated burden of active CHB infection in 20 years of follow-up is shown in Fig. 1 for the natural history scenario. If the active cohort of 6521 individuals remains untreated, 1725 (26%) will die because of liver-related complications. Within 20 years, there will be 1283 (20%) morbidity events, with 575 decompensation events (9%) and 670 HCC events (10%), and 38 cases will undergo liver transplantation (0.6%). At entry into the cohort in the year 2005, 836 cases (13%) are already in the cirrhotic stage (Table 3). By the year 2025, another 1671 (29%) of 5685 cases will have developed cirrhosis, and this will have led to a cumulative number of 2507 patients with cirrhosis (38%) in the eligible cohort.

thumbnail image

Figure 1. Liver-related mortality and morbidity of the hypothetical Dutch cohort with active CHB (2005-2025) by four different scenarios: (A) mortality of the active CHB cohort (n = 6521), (B) mortality of the noncirrhotic group (n = 5685), (C) mortality of the cirrhotic subgroup (n = 836), (D) cumulative hepatocellular carcinomas in the active CHB cohort (n = 6521), (E) cumulative decompensated cirrhosis in the cohort with high viremia (n = 6521), and (F) cumulative liver transplants in the cohort with high viremia (n = 6521). Abbreviations: CHB, chronic hepatitis B; HRD, high-resistance profile drug; LRD, low-resistance profile drug; NH, natural history; SRx, salvage therapy.

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Subgroups: Noncirrhosis Versus Cirrhosis.

At entry, 5685 (87%) of 6521 cases had no signs of cirrhosis, with 47% being HBeAg-positive and 53% being HBeAg-negative. If these noncirrhotic cases are left untreated, 1106 (19%) of the 5685 cases will die because of liver-related complications within 20 years. This proportion differs by HBeAg status and is 9% for HBeAg-positives and 28% for HBeAg-negatives. About 1671 (29%) of the noncirrhotic cases will develop cirrhosis (12% and 44% for HBeAg-positives and HBeAg-negatives, respectively), 360 (6%) will develop decompensated cirrhosis (4% and 9% for HBeAg-positives and HBeAg-negatives, respectively), 481 (8%) will develop HCC (4% and 13% for HBeAg-positives and HBeAg-negatives, respectively), and 30 (0.5%) will undergo liver transplantation (0.3% and 0.7% for HBeAg-positives and HBeAg-negatives, respectively).

Thirteen percent of the cohort had cirrhosis at entry (836/6521), with 21% being HBeAg-positive and 79% being HBeAg-negative. If left untreated, 619 (74%) of the 836 members of the cirrhotic cohort will die because of liver-related complications. This proportion does not differ by HBeAg status. The morbidity in this cohort will be 412 (50%) of 836 (again the same for HBeAg-positives and HBeAg-negatives); 215 (26%) cases will develop decompensated cirrhosis (32% and 24% for HBeAg-positives and HBeAg-negatives, respectively), 189 (23%) will develop HCC (10% and 26% for HBeAg-positives and HBeAg-negatives, respectively), and 8 (1%) will undergo liver transplantation (1% and 1% for HBeAg-positives and HBeAg-negatives, respectively). Table 4 and Fig. 1 show the different outcomes in all scenarios for the noncirrhotic and cirrhotic subgroups.

Table 4. Morbidity and Mortality of Active Chronic Hepatitis B by HBeAg Status in the Natural History Scenario
CHB Stage at EntrynOutcome
Cirrhosis (%)Decompensated Cirrhosis (%)HCC (%)Liver Transplant (%)Death (%)
  1. Abbreviations: CHB, chronic hepatitis B; HBeAg, hepatitis B e antigen; HCC, hepatocellular carcinoma.

No cirrhosis      
 HBeAg+2634317 (12)94 (4)93 (4)8 (0.3)248 (9)
 HBeAg−30511354 (44)266 (9)388 (13)22 (0.7)858 (28)
 All no cirrhosis56851671 (29)360 (6)481 (8)30 (0.5)1106 (19)
Cirrhosis      
 HBeAg+174174 (100)55 (32)17 (10)2 (1.1)127 (73)
 HBeAg−662662 (100)160 (24)172 (26)6 (0.9)492 (74)
 All cirrhosis836836 (100)215 (26)189 (23)8 (1.0)619 (74)
Total65212507 (38)575 (9)670 (10)38 (0.6)1725 (26)

If the active CHB cohort is not treated, 138 individuals (3%) of the 0 to 24 age group (n = 2174) and 1661 (38%) of the 25 to 65+ age group (n = 4345) will die because of liver-related complications within a 20-year period. The morbidity will be 34 cases (2%) in the 0 to 24 age group and 1249 (29%) in the 25 to 65+ age group.

Impact of Treatment

A reduction of hepatitis B–related mortality and morbidity was observed in model projections when treatment was applied. Treating the cohort with a high-resistance profile antiviral drug will decrease the mortality to 971 cases (15%; Fig. 1) and the number of morbidity events to fewer than 822 (13%). Treating the same patients with a low-resistance profile drug will further decrease the mortality to 339 liver-related deaths (5%) and the morbidity events to around 229 (3%).

Eight hundred sixty-one (15%) new cases of cirrhosis are to be expected if the active CHB cohort is treated with a high-resistance profile drug, whereas treatment with a low-resistance profile drug will yield only 112 (2%) new cases of cirrhosis after 20 years of follow-up.

When salvage therapy is applied without delay to the cases that become resistant, mortality and morbidity will be 333 (5%) and 386 (6%), respectively.

Comparing the four scenarios, we find that a low-resistance profile drug will prevent 1386 cases (80%) of liver-related death, whereas an antiviral with a high incidence of resistance will prevent only 754 cases (44%) of CHB-related deaths. Applying salvage therapy without delay to the cases who become resistant will prevent 1339 cases (77%) of CHB-related death. The burden of antiviral resistance in this model is 632 deaths (36% of the total number of liver-related deaths).

Comparing the scenarios in terms of morbidity, we find that a low-resistance profile drug will prevent 1054 cases (82%) from proceeding to complications, whereas an antiviral drug with high-resistance will prevent 461 cases (36%) from proceeding to CHB-related complications. The burden of antiviral resistance in terms of morbidity is 593 cases (46%). If salvage therapy is applied, this scenario will prevent 950 cases (74%) from proceeding to liver-related complications.

Sensitivity Analysis

The sensitivity analysis for the natural history scenario shows that, in comparison with the base case, in which the mortality of the active CHB cohort is 26%, the mortality ranges from 13% in the best case scenario to 39% in the worst case scenario. When assessed by subgroups, in the best and worst case scenarios, mortality ranges from 3% to 26% for HBeAg-positive chronic hepatitis, from 8% to 36% for HBeAg-negative chronic hepatitis, and from 60% to 91% for cirrhosis independent of HBeAg status.

Combining these ranges with the treatment-related outcomes indicates that a low-resistance profile drug can prevent 59% of liver-related deaths in the best case scenario for natural history and 87% in the worst case scenario with its high disease progression rate.

The sensitivity analysis regarding progression from cirrhosis to decompensated cirrhosis in the case of resistance shows that mortality in the high-resistance profile drug scenario decreases from 15% to 13% when the rate of progression in resistance is changed from higher than that in natural history to equal to that in natural history.

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

If all patients with high viremia and elevated ALT from the total cohort of CHB patients are fully treated with a low-resistance profile drug, liver-related mortality can be reduced by 80% (sensitivity analysis range, 59%-87%). Because liver-related mortality is approximately 26% (sensitivity analysis range, 13%-39%), a high relative reduction in mortality will also translate into a high absolute number of cases in which mortality can be prevented.

Treating the cohort with a high-resistance profile drug will reduce the liver-related mortality and morbidity by only 47%. The burden of antiviral resistance if no salvage therapy is applied is considerable: about 42% of the potential benefit of antiviral therapy is lost by resistance. In the Netherlands, in which reimbursement of salvage therapy is without restraint, adding a second antiviral agent in the case of resistance appears as good as starting with a low-resistance profile drug. In the model, the efficacy of salvage therapy might be overestimated because the start of salvage therapy is programmed at the time of occurrence of resistance. In practice, the start of salvage therapy will often be delayed. In addition, current evidence shows that salvage therapy can become ineffective in the long run.31

The beneficial effect of antiviral therapy is due to both the reduction in complications of cirrhosis and the prevention of the development of cirrhosis. Liaw et al.5 documented the beneficial effect of long-term nucleoside analogue therapy on clinical outcome in patients with cirrhosis. Our study underlines the potential efficacy of long-term antiviral therapy in patients with potentially progressive disease who are still in the noncirrhosis stage.

The aforementioned findings are related only to the subgroup of CHB patients with potentially progressive disease, that is, those with high viremia and elevated ALT. In a low endemic country such as the Netherlands, 10% of newly diagnosed CHB cases fall into this category, with about equal numbers of HBeAg-positives and HBeAg-negatives.

The active CHB cohort was constructed in a way that captured relevant aspects related to disease progression and response to treatment, that is, age, HBe antigen status, HBV DNA and ALT levels, and presence of cirrhosis. In assessing the cohort's progression through the various health states, we used transition estimates that were based on extensive systematic reviews16, 17 and updated with recently available robust findings.5, 18–26 We performed the analyses by simulating the cohort separately for each age-specific group, HBe antigen status, and stage of liver disease, as these factors affect prognosis, thereby approaching the real-life situation as much as possible. For the treatment scenarios, the model simulated long-term treatment as it is now emerging in guidelines.13 We developed the model in such a way that with small adaptations it can be used to estimate the hepatitis B burden and impact of antiviral therapy in various countries or regions according to their profiles, such as prevalence by age-specific group, and treatment characteristics, such as the drug type chosen for initial therapy and percentage application of salvage therapy.

We chose to apply the simulation to the specific cohort of high-viremia patients with elevated ALT because our main goal was to define the impact of antiviral drugs on clinical outcome and these patients would qualify for treatment according to recent guidelines.12, 13 Patients with high viremia and ALT levels within the normal range were not included in the cohort as these patients are often in the immune-tolerant phase of their infection and treatment is currently not recommended for this group. However, the context of how antiviral therapy should be used remains a difficult question, particularly with respect to which patients with CHB should be treated and what ALT level (abnormal, twice normal, or greater then 5 times normal) should be used for the criteria.32 The transition estimates for disease progression in our natural history model were taken from various international studies. Although the patients included in these studies were mainly patients with active CHB (i.e., with elevated ALT levels), some studies were based on a mixed population of CHB patients and also included patients with normal ALT levels. For this reason, the progression rates used in the natural history model might underestimate the morbidity and mortality of a strict cohort of active CHB patients with a high viral load and elevated ALT levels in natural history, and this implies an even higher impact of treatment.

In a future study, the outcome of patients with low viremia and those with high viremia but normal ALT will be assessed as well as the effect of antiviral therapy in specific subgroups such as noncirrhotic and cirrhotic patients, with transition estimates specifically applicable to these patients that are in different disease phases.

A limitation of our study is that we used simplified assumptions (e.g., we did not consider coinfection with other viruses or toxins such as alcohol that will accelerate progression), and we assumed the cohort to be static, so there were no new cases added to the cohort. Assuming that the development of resistance with a low-resistance profile drug for the coming 20 years will stay at 1% per year likely underestimates what will happen as longer term data are collected.

The proportion of patients without cirrhosis in our cohort at baseline is comparable to that found in a recent Italian longitudinal cohort study of untreated adult Caucasian patients with CHB, 87% of whom presented without cirrhosis at diagnosis.33 In the Italian study, 27% of the CHB patients developed cirrhosis during the follow-up period, and this is similar to our study, in which 29% of CHB cases develop cirrhosis over a period of 20 years. At the end of 20 years of follow-up, 26% of patients in the active CHB cohort will die of CHB-related causes, whereas this was 16% in the Italian cohort. However, the Italian cohort consisted of only 70 patients, and the 16% mortality rate fell within the sensitivity range of our mortality estimate. A possible explanation for the difference in mortality between our study and the Italian cohort study is that our cohort consists of patients with high viremia and ALT > 2 times the upper limit of normal, whereas the Italian study used HBeAg status as an indicator of high viremia. HBeAg-negative patients were not included in the Italian study, and these patients have a higher progression rate to cirrhosis.

Even the most precise mathematical modeling is only an estimate of the real-life situation.34 However, in the case of CHB, modeling might reflect real life better than official mortality data because epidemiological data based on death certificates have been shown to be extremely unreliable in estimating mortality from CHB.35, 36

This study, like a preliminary one in Spain,37 focused on quantifying the impact of therapy and antiviral resistance at the population level. Other studies of hepatitis B have used mathematical modeling to compare cost effectiveness among various antiviral drugs16, 17 and to predict the impact of vaccination programs in preventing HBV-related death.38 These studies mainly give an economic message, whereas we focused our study on the health aspect of the burden of disease. Apparently, CHB is not only a problem of less developed countries with high HBV endemicity but also a problem of countries with a low endemicity because there is a high absolute number of preventable liver-related deaths in a 20-year period.

The important clinical benefits described in this study can be obtained only if the full subgroup of active CHB patients is detected and treated for many years with high compliance. Currently, most of the eligible individuals are not treated because of limited screening activities to identify eligible cases. There are also major shortcomings in referral to specialist care,39 where treatment can be started and monitored.

On the basis of this study, public health organizations should turn their attention, means, and actions increasingly to CHB and take responsibility for identifying CHB and selecting those patients with potentially progressive disease for referral to treatment centers.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

The construction of the Dutch cohort with CHB was done in cooperation with T. Marschall and M. Kretzschmar of the University of Bielefeld (Germany), for which the authors are very thankful. The authors thank Dr. Ken Redekop of the Institute for Medical Technology Assessment for his help with the sensitivity analyses.

References

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information
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HEP_23061_sm_SuppInfo.pdf504KChinese Version.

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