陳建仁臺灣大學：流行病學研究所楊懷壹Yang, Hwai-IHwai-IYang2007-11-272018-06-292007-11-272018-06-292006http://ntur.lib.ntu.edu.tw//handle/246246/56209本論文以下列五個子研究探討B型肝炎病毒因子與肝癌及肝硬化危險性之相關。 研究一：B型肝炎病毒e抗原與肝細胞癌之長期追蹤研究 背景 B型肝炎病毒e抗原陽性是人體內B型肝炎病毒的複製活躍的指標之一，本研究乃利用前瞻性的長期追蹤世代研究釐清此指標對於肝細胞癌發生風險之重要性。 方法 本研究於1991至1992年間，針對台灣七個鄉鎮市區30至65歲共11,893名無肝癌既往史之男性居民，進行收案追蹤研究。每名研究個案於進入研究時，均被採集血液以放射免疫法進行B型肝炎表面抗原及e抗原的檢測。研究世代並與癌症登記檔及死亡檔進行資料連結以確認肝癌的發生。 結果 截至2000年9月30日止，總共追蹤92,359人年，其中有111名個案新發生肝細胞癌。根據收案時的血清標記來分析，B型肝炎表面抗原及e抗原皆呈陰性、表面抗原陽性但e抗原陰性及兩者皆呈陽性的個案，肝細胞癌的發生率分別為每十萬人年39.1、324.3及1169.4。在調整年齡、C型肝炎病毒血清抗體狀態、抽煙及喝酒習慣等危險因子的干擾作用後，表面抗原陽性但e抗原陰性的個案，發生肝細胞癌的相對危險性，是兩種抗原皆陰性者的9.6倍（95%信賴區間：6.0-15.2）；兩種抗原皆陽性的個案發生肝細胞癌的相對危險性更高達60.2倍（95%信賴區間：35.5-102.1）。 結論 B型肝炎病毒e抗原血清標記可預測肝細胞癌的發生風險，B型肝炎病毒的持續活躍複製，是造成肝癌的主要原因。 研究二：血中B型肝炎病毒量與罹患肝細胞癌之風險 背景 血中B型肝炎病毒量是慢性B型肝炎患者病毒複製與抗病毒治療效益的指標，本世代追蹤研究旨在探討血中B型肝炎病毒量與肝細胞癌風險的相關。 方法 本研究係以3,653名B型肝炎表面抗原陽性、C型肝炎抗體陰性之世代成員為研究個案，利用Roche COBAS Amplicor檢驗試劑進行血中B型肝炎病毒量之檢測，肝癌的確認乃經由追蹤檢查以及與癌症登記檔和死亡檔之資料連結。 結果 經由41,779人年（平均每人11.4年）之追蹤，共有164名個案新發生肝細胞癌。研究個案進入研究時血液中B型肝炎病毒量與肝癌發生率呈現劑量效應關係，由病毒量<300 copies/mL的每十萬人年108升高到病毒量³106 copies/mL的每十萬人年1150。調整了性別、年齡、抽煙、喝酒、B型肝炎e抗原、血中丙胺酸轉胺脢以及進入研究時的肝硬化狀態，此劑量效應關係仍然存在。血液中B型肝炎病毒量與肝癌風險的劑量效應關係在e抗原陰性、血中丙胺酸轉胺脢正常且進入研究時無肝硬化的個案最為顯著。在追蹤過程中維持血中B型肝炎高病毒量的個案有最高的肝細胞癌危險性。 結論 血液中帶有高的B型肝炎病毒量（³10,000 copies/mL）是一個獨立於B型肝炎e抗原、血中丙胺酸轉胺脢以及肝硬化的肝細胞癌重要預測因子。 研究三：以血中B型肝炎病毒量預測肝硬化之發生風險 背景 慢性B型肝炎患者的肝硬化源自於肝臟的發炎及纖維化，本研究乃以世代研究法探討血中B型肝炎病毒量與肝硬化的相關。 方法 本研究以3,582名未經過抗病毒藥物治療之長期追蹤世代成員為研究個案，進行進入研究時血液中B型肝炎病毒量之檢測，並以腹部超音波診斷肝硬化。 結果 3,582名研究個案共追蹤了40,038人年，期間共有365名個案被診斷出肝硬化。發生肝硬化的累積危險性在血中病毒量為<300 copies/mL及³106 copies/mL的個案分別為4.5%及36.2% (P<0.001)。調整了B型肝炎e抗原、血中丙胺酸轉胺脢以及其他變項之後，B型肝炎病毒量為最重要的肝硬化預測因子，以B型肝炎病毒量<300 copies/mL為參考組，病毒量為³104-<105；³105-<106；³106 copies/mL的個案，其相對危險性（95%信賴區間）分別為2.5 (1.6-3.8)；5.6 (3.7-8.5)；及6.5 (4.1-10.2)。 結論 本研究顯示慢性B型肝炎患者之B型肝炎病毒量與進展至肝硬化的風險有很強的相關，B型肝炎病毒量較高者有較高的肝硬化危險性。 研究四：B型肝炎病毒基因型和突變體與肝細胞癌危險性之相關 背景 B型肝炎病毒基因型和突變體在肝細胞致癌機轉中扮演的角色尚待釐清，本研究乃利用世代研究法評估B型肝炎病毒基因型、precore stop codon突變（G1896A）以及basal core promoter突變（A1762T/G1764A）對肝細胞癌發生危險性造成的影響。 方法 本研究以3,644名B型肝炎表面抗原陽性、C型肝炎抗體陰性之世代成員為研究個案，檢測了進入研究時的血中B型肝炎病毒量（以real-time PCR方法）和基因型，1,526名進入研究時病毒量為³104 copies/mL的個案則另外檢測B型肝炎病毒的G1896A與A1762T/G1764A突變。 結果 截至2004年6月30日止，共追蹤了41,695人年，期間共有162名肝細胞癌個案新發生。B型肝炎病毒B與C基因型之肝癌發生率（每十萬人年）分別為305.6及785.8；帶有G1896A突變體及其野生型的發生率為269.4及955.5；而帶有A1762T/G1764A突變體及其野生型的發生率則分別為1149.2與358.7。調整了性別、年齡、B型肝炎病毒量、抽煙與喝酒後，基因型C相對於基因型B發生肝癌的相對危險性為2.7（95%信賴區間：1.9-3.7）；帶有G1896A突變體相對其野生型的相對危險性為0.2（95%信賴區間：0.1-0.4）；而帶有A1762T/G1764A突變體相對其野生型的相對危險性為2.7（95%信賴區間：1.8-4.1）。 結論 本研究顯示B型肝炎病毒C基因型及A1762T/G1764A突變體是肝癌的危險因子，而G1896A突變體的出現對肝癌的發生具有保護作用，此保護作用在B型肝炎e抗原陰性的個案中特別顯著。 研究五：慢性B型肝炎患者罹患肝細胞癌的預測模式 背景 目前尚無預測個別慢性B型肝炎患者未來發生肝細胞癌機率的統計模式可資使用，本研究乃根據目前可得的臨床資料來發展預測個人肝癌發生機率的模式。 方法 本研究使用與研究四相同的資料檔，總共有11個候選危險因子可納入統計模式。我們使用Cox氏比例危害複迴歸方法根據不同的危險因子集合來發展模式，將得到的迴歸係數轉換為整數的風險計分，然後預測各種風險計分下5年及10年內發生肝癌的機率，並將計分系統及其預測的肝癌發生機率轉成列線圖（Nomogram）以利使用。模式的預測準確性以兩個面向來評估，包括：鑑別能力（Discrimination ability）以ROC曲線及曲線下面積來估算；及校準能力（Calibration ability）以校準圖（Calibration chart）來量測。計分與模式預測風險的比較則以散佈圖來闡明。 結果 我們總計發展了8個風險預測模式及列線圖，這些模式具有良好的鑑別及校準能力，所有模式的ROC曲線下面積都大於80%，且校準圖顯示所預測的5年及10年肝癌風險皆相當接近實際的風險。計分系統的預測結果與模式所預測的風險有很高的相關。 結論 本研究所發展的模式及列線圖可幫助臨床醫師評估及解釋慢性B型肝炎患者的肝癌發生風險，並可用來協助討論抗病毒治療的可能效益。This thesis consists of five component studies to investigate hepatitis B virus (HBV) related factors and the risk of liver cirrhosis and hepatocellular carcinoma (HCC). Study 1: Hepatitis B e antigen (HBeAg) and the risk of HCC Background The presence of HBeAg in serum indicates active viral replication in hepatocytes. HBeAg is thus a surrogate marker for the presence of HBV DNA. We conducted a prospective study to determine the relation between positivity for hepatitis B surface antigen (HBsAg) and HBeAg and the development of HCC. Methods In 1991 and 1992, we enrolled 11,893 men without evidence of HCC (age range, 30-65 years) from seven townships in Taiwan. Serum samples obtained at the time of enrollment were tested for HBsAg and HBeAg by radioimmunoassay. The diagnosis of HCC was ascertained through data linkage with the computerized National Cancer Registry in Taiwan and with death certificates. We performed a multiple regression analysis to determine the hazard ratio of HCC among men who were positive for HBsAg alone or for HBsAg and HBeAg, as compared with those who were negative for both. Results There were 111 cases of newly diagnosed HCC during 92,359 person-years of follow-up. The incidence rate of HCC was 1169 cases per 100,000 person-years among men who were positive for both HBsAg and HBeAg, 324 per 100,000 person-years for those who were positive for HBsAg only, and 39 per 100,000 person-years for those who were negative for both. After adjustment for age, the presence or absence of antibodies against hepatitis C virus (anti-HCV), cigarette-smoking status, and use or nonuse of alcohol, the hazard ratio of HCC was 9.6 (95% CI, 6.0 to 15.2) among men who were positive for HBsAg alone and 60.2 (95% CI, 35.5 to 102.1) among those who were positive for both HBsAg and HBeAg, as compared with men who were negative for both. Conclusions Positivity for HBeAg is associated with an increased risk of HCC. Study 2: Risk of HCC across a biological gradient of serum HBV DNA level Background Serum HBV DNA level is a marker of viral replication and efficacy of antiviral treatment in individuals with chronic hepatitis B. This study aimed to evaluate the relationship between serum HBV DNA level and risk of HCC. Methods This is a prospective cohort study of 3,653 participants (aged 30-65 years), who were seropositive for HBsAg and seronegative for anti-HCV, recruited to a community-based cancer screening program in Taiwan between 1991 and 1992. The main outcome measure was incidence of HCC during follow-up examination and by data linkage with the national cancer registry and the death certification systems. Results There were 164 incident cases of HCC and 346 deaths during a mean follow-up of 11.4 years and 41,779 person-years of follow-up. The incidence of HCC increased with serum HBV DNA level at study entry in a dose-response relationship ranging from 108 per 100,000 person-years for an HBV DNA level of <300 copies/mL to 1150 per 100,000 person-years for and HBV DNA level of ³1 million copies/mL. The corresponding cumulative incidence rates of HCC were 1.3% and 14.9%, respectively. The biological gradient of HCC by serum HBV DNA levels remained significant (P<0.001) after adjustment for sex, age, cigarette smoking, alcohol consumption, serostatus for HBeAg, serum alanine aminotransferase (ALT) level, and liver cirrhosis at study entry. The dose-response relationship was most prominent for participants who were seronegative for HBeAg with normal serum ALT levels and no liver cirrhosis at study entry. Participants with persistent elevation of serum HBV DNA level during follow-up had the highest HCC risk. Conclusion Elevated serum HBV DNA level (³10,000 copies/mL) is a strong risk predictor of HCC independent of HBeAg, serum ALT level and liver cirrhosis. Study 3: Predicting cirrhosis risk based on the level of circulating hepatitis B viral load Background Cirrhosis develops as a result of hepatic inflammation and subsequent fibrosis in chronic hepatitis B infection. We report on the relationship between hepatitis B viremia and progression to cirrhosis in chronic hepatitis B infection. Methods This was a population-based prospective cohort study of 3,582 untreated hepatitis B-infected patients established in Taiwan from 1991 to 1992. Serum samples were tested for HBV DNA on cohort entry serum samples and the diagnosis of cirrhosis was by ultrasound. Results During a mean follow-up time of 11 years, the 3,582 patients contributed 40,038 person-years of follow-up evaluation and 365 patients were newly diagnosed with cirrhosis. The cumulative incidence of cirrhosis increased with the HBV DNA level and ranged from 4.5% to 36.2% for patients with a hepatitis B viral load of <300 copies/mL and ³106 copies/mL, respectively (P<0.001). In a Cox proportional hazards model adjusting for HBeAg status and serum ALT level among other variables, hepatitis B viral load was the strongest predictor of progression to cirrhosis. Hazard ratio (95% CI) was 2.5 (1.6-3.8); 5.6 (3.7-8.5); and 6.5 (4.1-10.2) for HBV DNA levels ³104-<105; ³105-<106; ³106 copies/mL, respectively. Conclusions These data show that progression to cirrhosis in hepatitis B-infected persons is correlated strongly with the level of circulating virus. The risk of cirrhosis increases significantly with increasing HBV DNA levels and is independent of HBeAg status and serum ALT level. Study 4: Risk of HCC associated with genotypes and mutants of HBV Background The roles of genotypes and mutants of HBV in hepatocarcinogenesis remain to be elucidated. The specific aim of this study was to assess the risk of HCC associated with HBV genotypes, precore stop codon mutant (G1896A) and basal core promoter mutant (A1762T/G1764A). Methods A cohort of 3,644 adult residents who were HBsAg-seropositive and anti-HCV-seronegative was enrolled from seven townships in Taiwan between 1991 and 1992. Blood samples at cohort entry were tested for HBV viral load and genotype. Baseline blood samples of 1,526 participants with a serum HBV DNA level ³104 copies/mL were further tested for HBV mutants of G1896A and A1762T/G1764A. Newly developed HCC was ascertained through follow-up health examinations and computerized data linkage to national cancer registry and death certification profiles. Results By June 30 2004, there were 162 HCC cases occurred during 41,695 person-years of follow-up. The incidence rate per 100,000 person-years were 305.6 and 785.8, respectively, for participants infected with HBV genotype B and C; 269.4 and 955.5, respectively, for participants infected with G1896A mutant and wild-typed HBV; as well as 1149.2 and 358.7, respectively, for participants infected with A1762T/G1764A mutants and wild-typed HBV. The hazard ratio of HCC after adjustment for gender, age, HBV viral load, cigarette smoking, and alcohol drinking was 2.7 (95% CI, 1.9-3.7) for HBV genotype C compared with genotype B, 0.2 (95% CI, 0.1-0.4) for G1896A mutant compared with its wild type, and 2.7 (95% CI, 1.8-4.1) for A1762T/G1764A mutants compared with their wild types. Conclusions Our data suggest that HBV genotype C and A1762T/G1764A mutants were independent risk factors for HCC. While the emergence of G1896A mutant conferred a protective effect on HCC, especially in HBeAg-seronegative participants. Study 5: Model to predict HCC in patients with chronic hepatitis B infection Background The risk of developing HCC for a particular individual with chronic hepatitis B over a specific period remained to be determined. The objective of this study was to develop models that can be used to predict HCC risk in an individual based on readily available clinical information. Methods Information of 3,644 subjects as described in Study 4 was used in this analysis. Eleven baseline variables had a priori plausibility as risk factors were available in the dataset. Cox proportional hazards models were used to train models, for different sets of profiles selected from candidate risk factors, with HCC development and person-year of follow-up as outcomes. The regression coefficients derived from the Cox models were converted into integer risk scores and the predicted risks of HCC within 5 or 10 years were calculated for various risk scores. The score system and the predicted 5- and 10-year HCC risks were further translated into nomograms. The predictive accuracy was evaluated in terms of discrimination and calibration abilities with the use of Receiver Operator Characteristic (ROC) curve and area under the ROC curve; and the calibration chart. The comparison of predicted HCC risk by score and by model was illustrated using scatter plot. Results Eight risk prediction models and nomograms were generated. These models demonstrated nice discrimination and calibration abilities. All areas under the ROC curves were greater than 0.8 and the predicted 5- and 10-year risks approximated to the corresponding actual risks in calibration charts. The HCC risk predicted by score correlated well with the risk predicted by model. Conclusion The model and nomograms in this study may help clinicians in evaluating and explaining to patients their risk of HCC and may simplify the discussion of potential benefits from anti-viral therapies.CONTENTS LIST OF TABLES III LIST OF FIGURES V 中文摘要 VII ABSTRACT XI LIST OF ABBREVIATIONS XVI PREFACE 1 CHAPTER 1 Hepatitis B e Antigen and the Risk of HCC 4 1.1 Introduction 4 1.2 Methods 5 1.2.1 Study Cohort 5 1.2.2 Data Collection and Blood Tests 5 1.2.3 Follow-up for HCC 6 1.2.4 Statistical Analysis 7 1.3 Results 8 1.4 Discussion 9 CHAPTER 2 Risk of HCC Across a Biological Gradient of Serum HBV DNA Level 19 2.1 Introduction 19 2.2 Methods 21 2.2.1 Cohort Recruitment and Follow-up 21 2.2.2 Interview and Blood Collection 21 2.2.3 Laboratory Examinations 22 2.2.4 Ascertainment of Newly Developed HCC 22 2.2.5 Statistical Analysis 23 2.3 Results 24 2.3.1 Incidence Rates of HCC by Serum HBV DNA Level at Cohort Entry 24 2.3.2 Cumulative Incidence of HCC by Serum HBV DNA Level at Cohort Entry 25 2.3.3 Dose-response Relationship between HCC Risk and Serum HBV DNA Level at Cohort Entry 26 2.3.4 Biological Gradient of HCC Risk in Subgroups Analysis 27 2.3.5 Multivariate-adjusted Relative HCC Risk by Serum HBV DNA Levels at Both Cohort Entry and Follow-up Examinations 27 2.4 Discussion 28 CHAPTER 3 Predicting Cirrhosis Risk Based on the Level of Circulating Hepatitis B Viral Load 41 3.1 Introduction 41 3.2 Methods 42 3.2.1 Subject Selection for the Analysis on HBV DNA and Cirrhosis 43 3.2.2 Ascertainment of Cirrhosis 43 3.2.3 Statistical Analysis 43 3.3 Results 44 3.4 Discussion 46 CHAPTER 4 Risk of HCC Associated with Genotypes and Mutants of HBV 57 4.1 Introduction 57 4.2 Methods 59 4.2.1 Laboratory Tests 59 4.2.2 Statistical Analysis 61 4.3 Results 61 4.3.1 Gender and Age-Specific Prevalence of HBV Genotype and Mutants 62 4.3.2 Correlation Between HBV Markers 62 4.3.3 Incidence Rates 63 4.3.4 Multivariable-Adjusted Hazard Ratios 63 4.3.5 Subgroup Analysis 64 4.3.6 Combined Effect of Precore and BCP Mutations 65 4.3.7 Gender Difference 65 4.4 Discussion 66 CHAPTER 5 Model to Predict HCC in Patients with Chronic Hepatitis B Infection 86 5.1 Introduction 86 5.2 Methods 87 5.3 Results 88 5.4 Discussion 90 FUTURE PERSPECTIVES 119 REFERENCES 121 LIST OF TABLES Table 1-1. Prevalence of HBsAg and HBeAg in 11,893 Men in Taiwan 13 Table 1-2. Incidence of HCC during Follow-up 14 Table 1-3. Adjusted Hazard Ratio of HCC According to Various Risk Factors 15 Table 1-4. Adjusted Hazard Ratio of HCC, with Stratification According to Age, Cigarette-Smoking Status, and Use or Nonuse of Alcohol 16 Table 1-5. Level of HBV DNA in Men with HCC and Matched Controls Who Were Positive for HBsAg and Negative for HBeAg at Enrollment 17 Table 2-1. Serum Level of HBV DNA and HBeAg Serostatus at Study Entry 31 Table 2-2. Incidence Rate and Adjusted Hazard Ratio of HCC According to HBV DNA Level 32 Table 2-3. Cumulative Incidence of HCC by HBV DNA Level at Study Entry 33 Table 2-4. Regression Analysis of Risk Factors Associated With HCC 34 Table 2-5. HCC by Serum HBV DNA Levels at Study Entry and at Last Follow-up 35 Table 3-1. Demographic Characteristics of Different Subsets of the Study Population 50 Table 3-2. Incidence of Cirrhosis by HBV DNA Level (N=3582) 51 Table 3-3. Association Between HBV DNA Level and Cirrhosis Risk Stratified by Several Variables (N=3582) 52 Table 3-4. Multiple Cox Proportional Hazards Regression Analyses of Risk Facotrs Associated With Cirrhosis Among Those Chronically Infected With HBV and Negative for Anti-HCV (N=3582) 53 Table 3-5. Multiple Cox Proportional Hazards Regression Analyses of Risk Factors Associated With Cirrhosis Among Those Chronically Infected With HBV and Negative for Anti-HCV Excluding 100 Cirrhosis Cases Diagnosed on the Basis of 1 Ultrasound Test (N=3482) 54 Table 4-1. Basic Characteristics of the Study Cohort (N=3644) 71 Table 4-2. Distribution of Precore and BCP Mutants in Subjects with HBV DNA ≥104 copies/mL (N=1526) 72 Table 4-3. Gender and Age-Specific Prevalence of HBV Genotype, Precore 1896 and BCP 1762/1764 mutants 73 Table 4-4. Incidence Rate and Adjusted Hazard Ratio of HCC for HBV Genotype and Mutants 74 Table 4-5. Multivariable-Adjusted Cox’s Regression Analysis for Risk of HCC 75 Table 4-6. Multivariable-Adjusted Regression Analysis in Subjects with HBV DNA ≥104 Copies/mL at Baseline (N=1526) 76 Table 4-7. Subgroup Analysis of HCC Risk for HBV Genotype 77 Table 4-8. Subgroup Analyses of HCC Risk for HBV Genotype, Precore and BCP Mutants in Subjects with HBV DNA ≥104 Copies/mL at Baseline (N=1526) 78 Table 4-9. Combinations of Precore and BCP Mutants Stratified by Age 79 Table 4-10. Adjusted Hazard Ratio of HCC for the Combinations of Precore and BCP Mutants 80 Table 4-11. Incidence Rate and Adjusted Hazard Ratio of HCC for Gender Stratified by HBV DNA Level, Genotype, Precore and BCP Mutants 81 Table 4-12. Multivariable-adjusted Cox Regression Models for Female and Male Subjects 82 Table 5-1. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, and HBeAg (Model 1) 93 Table 5-2. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, HBeAg, and HBV DNA Level (Model 2) 94 Table 5-3. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, and the Combinations of HBeAg and HBV DNA Level (Model 3) 95 Table 5-4. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, HBeAg, and the Combinations of HBV DNA and Genotype (Model 4) 96 Table 5-5. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, HBeAg, and the Combinations of HBV DNA and Genotype (Model 5) 97 Table 5-6. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, HBeAg, and the Combinations of Genotype, HBV DNA and Precore Mutnats (Model 6) 98 Table 5-7. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, HBeAg, and the Combinations of Genotype, HBV DNA and BCP Mutnats (Model 7) 99 Table 5-8. Multiple Cox Proportional Hazards Model for Gender, Age, Alcohol Consumption, ALT, HBeAg, and the Combinations of Genotype, HBV DNA, Precore and BCP Mutnats (Model 8) 100 LIST OF FIGURES Figure 1-1. Cumulative Incidence of HCC during Follow-up among 11,893 Men in Taiwan, according to the Presence or Absence of HBsAg and HBeAg at enrollment. 18 Figure 2-1. Flow of Study Participants in the Study on Serum HBV DNA and HCC 36 Figure 2-2. Cumulative Incidence of HCC by Serum HBV DNA Level at Study Entry. (A) A Cohort of 3,653 Participants Who Were Seropositive on HBsAg and Seronegative on Anti-HCV; (B) A Sub-cohort of 2,925 Participants Who Were Seronegative on HBeAg With a Normal Serum Level of ALT and No Liver Cirrhosis 38 Figure 2-3. Multivariable-adjusted Hazard Ratio of HCC by Serum Level of HBV DNA at Cohort Entry examination Stratified by Gender, Age, and Habits of Cigarette Smoking and Alcohol Consumption. (A) A Cohort of 3,653 Participants Who Were Seropositive on HBsAg and Seronegative on Anti-HCV; (B) A Sub-cohort of 2,925 Participants Who Were Seronegative on HBeAg With a Normal Serum Level of ALT and No Liver Cirrhosis 40 Figure 3-1. Flow of Study Participants in the Study on Serum HBV DNA and Cirrhosis 55 Figure 3-2. Cumulative Incidence of Cirrhosis (N=3582) 56 Figure 4-1. Flow of participants in the study on genotype and mutants of HBV and risk of HCC 83 Figure 4-2. Inter-Correlation between HBV Markers: (A) Correlation between HBeAg Status and Genotype, Precore and BCP Mutants; (B) Correlation between Genotype and Precore and BCP Mutants; (C) Correlation between Precore Mutant and HBV DNA Level Stratified by Genotype; (D) Correlation between BCP Mutant and HBV DNA Level Stratified by Genotype 85 Figure 5-1. (A) to (H) HCC Risk Prediction Nomograms for Models 1 to 8 as Presented in Table 5-1 through Table 5-8 108 Figure 5-2. (A) ROC Curves for 5-Year HCC Risk; (B) ROC Curves for 10-year HCC Risk Predicted by Model 1 to Model 8 110 Figure 5-3. (A) to (H) Calibration Charts for Model 1 to Model 8 114 Figure 5-4. (A) to (H) HCC Risk Predicted by Score Versus by Model for Model 1 to Model 8 1181033198 bytesapplication/pdfen-USB型肝炎病毒病毒因子肝細胞癌肝硬化B型肝炎e抗原B型肝炎病毒DNAB型肝炎病毒量B型肝炎病毒基因型B型肝炎病毒突變PrecoreBasal Core Promoter風險預測模式Hepatitis B VirusVirus FactorLiver CirrhosisHepatocellular CarcinomaHepatitis B e Antigen, HBV DNAViral LoadHBV GenotypeHBV MutantsBasal Core PromotorRisk Prediction Model[SDGs]SDG3thesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/56209/1/ntu-95-F87842002-1.pdf