Burden and Trends of Liver-Related Cancers, 1990–2021: A Comparative Analysis of China, Korea, Japan,the United Kingdom , and the United States

Burden and Trends of Liver-Related Cancers, 1990–2021: A Comparative Analysis of China, Korea, Japan,the United Kingdom , and the United States | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Burden and Trends of Liver-Related Cancers, 1990–2021: A Comparative Analysis of China, Korea, Japan,the United Kingdom , and the United States Shuang Zhang, Yaxin Hu, Dawei Guo, Xiaobo Li, Jiuzhang Men, Yuming Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7432498/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The burden of common cancer diseases of the liver-related cancers, including liver cancer (LC),pancreatic cancer (PC) and gallbladder and biliary tract cancer (GC). With its high prevalence and mortality rates, it has a serious impact on quality of life and increases the burden on the healthcare system. Despite the high disease burden of liver-related cancers, they remain under-recognized in global health policy. This study examined epidemiologic trends in liver-related cancers in China, Korea, Japan, the United States, and the United Kingdom from 1990 to 2021, highlighting regional differences and projecting future burdens. Methods This study used the 2021 Global Burden of Disease (GBD) data to analyze the incidence, prevalence, and years lived with disability (YLD) of liver-related cancers. A Bayesian age–period–cohort (BAPC) model was applied to project future trends through 2050. In addition, country-specific variance analysis and sensitivity analysis were performed to test the robustness of the model to input data quality. Results In 2021, China reported the highest number of new cases for GC (1,119), LC (11,860), and PC (2,821), with males affected more than females. The United States, Japan, South Korea, and the United Kingdom followed. GC and PC incidence rose in China but fell in Japan and Korea; LC decreased in China but increased markedly in the U.S. Projections from 2022 to 2025 suggest China will continue to have the highest absolute burden, the U.S. will report high DALYs due to its population size, Japan and Korea will maintain moderate yet significant age-standardized rates (ASRs), and the U.K. will see a slight rise in deaths. Conclusion Hepatobiliary cancers remain a major public health issue in all five countries, with burden influenced by age, gender, and demographic structure. China faces high incidence and absolute burden, the U.S. carries substantial DALYs due to population size, Japan and Korea show intermediate ASRs with variable trends, and the U.K. experiences gradual increases in mortality. Locally adapted health policies and targeted interventions are essential. Future studies should incorporate socioeconomic, behavioral, and health system factors to improve cancer control strategies. Global burden of disease epidemiology disability age-period-cohort modeling time trends public health policy Five countries Figures Figure 1 Figure 2 Figure 3 Introduction the liver-related cancers occur mainly in the liver, gallbladder and bile ducts (bile ducts), and the three common types are cancer of the liver, pancreas, gallbladder and bile ducts( 1 , 2 ). the liver-related cancers continue to threaten human health globally, especially in China, Japan, Korea, the United Kingdom, and the United States of America( 3 ). Despite its relatively small share in the global cancer spectrum, the high mortality rate poses a serious threat to human health, causing severe disease burden and social stress, especially in the Asia-Pacific region. According to the GBD study, men, the elderly, people with low socioeconomic status, and people living in Low- and Middle-Income Countries (LMICs) are the main victims of liver ( 4 ). High-risk groups include mainly men, the elderly, and patients with chronic liver disease or metabolic syndrome( 5 ). The high prevalence of hepatocellular carcinoma in China, Korea and Japan is closely related to the prevalence of hepatitis B and C viruses ( 6 ), Whereas in Europe and the United States, such as the United Kingdom and the United States, nonalcoholic fatty liver disease (NAFLD), alcohol-related liver disease, and obesity-related metabolic disease have emerged as major risk factors ( 7 ). Pancreatic cancer, on the other hand, is on the rise in high-income countries and is closely related to factors such as population ageing, smoking and diabetes( 8 ). In addition, gallbladder and biliary tract cancers are also associated with endemic diseases such as gallstones and hepatic schistosomiasis in some regions, showing obvious regional differences. liver-related cancers have a profound impact on the socio-economic and health care systems( 9 ). liver-related cancers often lead to prolonged hospitalization, repeated treatments and even income disruption, increasing the financial burden on families. In areas where effective health insurance coverage is lacking, many families fall into “poverty due to illness” because they cannot afford expensive targeted drugs and treatments. Even in high-income countries, these cancers place a significant strain on health care finances, and GBD studies have shown that these cancers result in significantly more premature deaths (YLLs) and disability-adjusted life years (DALYs) than most common cancers( 10 ). Especially in low- and middle-income countries, the economic impact far exceeds the average level of social spending on health care. According to data from the GBD study, there is significant geographic heterogeneity in the incidence patterns, mortality rates, and burden of disease for this group of cancers. This heterogeneity is closely related to the Socio-demographic Index (SDI), which quantifies regional development by combining indicators such as income level, educational attainment and total fertility rate( 11 , 12 ). SDI stratification analysis shows that age-standardized mortality rates for the liver-related cancers in high SDI regions (e.g., North America, Western Europe) are trending downward, whereas the burden continues to increase in low and medium SDI regions (e.g., East Asia, South Asia) due to delayed diagnosis, insufficient therapeutic resources, and differences in risk factor exposure. In the case of liver, for example, the mortality rate in low SDI regions is 2.3 times higher than that in high SDI regions, and 80% of liver is already in advanced stages when diagnosed( 4 , 13 ). The 5-year survival rate for pancreatic cancer is less than 10% in low SDI areas, significantly lower than the 13% in high SDI areas, highlighting the unequal distribution of healthcare resources( 8 , 14 ). The distribution of gallbladder and biliary tract cancers (GBTC) is more polarized. Of these, 73% were concentrated in low SDI areas, reflecting the synergistic effect of geographic-specific risk factors (e.g., biliary parasitic infections) and health system weaknesses( 15 ). Notably, early-onset (< 40 years of age) biliary tract cancers are on the rise in parts of Asia and may be associated with genetic mutations and environmental exposures( 16 ). SDI differences are also reflected in the burden of risk factor attribution. High BMI was responsible for 25% of liver cancer deaths in high SDI areas compared to 8% in low SDI areas; conversely, alcohol use was responsible for 31% of liver cancer deaths in low SDI areas, significantly higher than the 12% in high SDI areas( 16 ). The smoking-attributable burden of pancreatic cancer continues to rise in low and intermediate SDI regions at an annual rate of 1.7%, highlighting the consequences of the lack of tobacco control policies. Existing studies emphasize that liver-related cancers show significant heterogeneous patterns in different age and gender populations. The persistently high incidence and mortality rates of hepatocellular carcinoma in middle-aged and elderly men in China and Korea may be closely related to hepatitis B virus (HBV) infection, alcohol abuse, and lifestyle factors( 1 , 17 ). In contrast, the higher burden of biliary tract cancer in middle-aged and elderly Japanese women may be related to genetic susceptibility and environmental exposure( 18 , 19 ). However, quantitative studies of key drivers influencing temporal trends in the liver-related cancers are still lacking( 20 ). However, the westernization of lifestyle and the rise of metabolic diseases (e.g., obesity, diabetes mellitus) during urbanization in China may push up the burden of non-viral liver in the future, complicating the comparison of trends between countries( 1 ). Similarly, there are significant shortcomings in the prediction of future disease burdens( 6 ). Particularly in Asian countries, such as China and Korea, where increasing population ageing is intertwined with the prevalence of metabolic syndrome( 21 ).There is an urgent need to construct a dynamic, multifactorial participatory modeling framework to more accurately reflect the future evolutionary trajectory of cancers of the hepatobiliary system( 22 ). Although previous studies have explored the epidemiology of hepatobiliary cancers (liver, pancreas, gallbladder, and biliary tract) in different countries, comparative analyses between countries with different SDI trajectories remain scarce. This study filled a major gap by ( 1 ) quantifying regional differences liver burden through age-standardized metrics; ( 2 ) utilizing the Bayesian Age-Period-Cohort (BAPC) model to project and analyze predictions of future trends; and ( 3 ) evaluating the impact of temporal and epidemiological trends through a ratio of the mean annual percentage change. Focusing on the United States, the United Kingdom, China, Japan, and South Korea, we analyzed the incidence, prevalence, and incidence of liver, pancreatic, gallbladder, and biliary tract cancers for the period 1990 to 2021 using GBD 2021 data. ASRs ensured fairness in comparisons, while the mean annual percentage change ratio determined time trends, and the BAPC model projected future burden to 2050. By elucidating regional disparities and their determinants, this work aims to inform tailored public health strategies and address key gaps in the management of cancers of the hepatobiliary system in different socio-demographic populations, with a particular emphasis on how socio-developmental index drivers influence the dynamics of hepatobiliary cancers. Methods Overall This study utilized the Bayesian Age-Period-Cohort (BAPC) model to project and analyze the burden of three liver-related cancers—liver cancer (LC), pancreatic cancer (PC), and gallbladder and biliary tract cancer (GC)—across five countries (China, Japan, Republic of Korea, United Kingdom, and United States of America) for 2022 and 2025. Input data were sourced from the GBD database, national cancer registries, and population-based surveys, harmonized using standardized case definitions and demographic adjustments. ASRs per 100,000 population and absolute numerical estimates were computed for incidence, prevalence, deaths, and DALYs, stratified by sex (Both, Female, Male). Uncertainty intervals (95% UIs) were generated through 1,000 Monte Carlo simulations to quantify variability in projections. Burden Description The burden assessment focused on 2022 baseline estimates and 2025 projections, quantifying LC, PC, and GC through incident cases, prevalent cases, deaths, and DALYs. Country-specific disparities were analyzed by comparing ASRs and absolute values, with stratification by sex to highlight male-female differences. For example, China’s high absolute burden was contextualized against its large population size, while the United States’ elevated DALYs were linked to demographic aging. Metrics were standardized using the World Health Organization (WHO) global population structure to enable cross-country comparisons. Trend Analysis Temporal trends were evaluated using Average Annual Percentage Changes (AAPCs) derived from historical data (2010–2022) to contextualize future projections. The BAPC model incorporated age, period, and cohort effects to disentangle underlying drivers of trends, such as aging populations or shifts in risk factors. AAPCs were calculated for ASRs of incidence, mortality, and DALYs, with sensitivity analyses testing model robustness to input data quality. For instance, Japan’s declining LC mortality (-2.89% AAPC) was linked to improved screening programs, while the United Kingdom’s rising LC incidence (+ 4.31% AAPC) reflected increasing alcohol-related risks. Projection Based on Bayesian Age-Period-Cohort Model The BAPC model projected cancer burden from 2022 to 2025, integrating demographic projections (e.g., population growth, aging) and historical trend trajectories. Model parameters included country-specific fertility, mortality, and migration rates from the United Nations Population Division. Sex-stratified projections were generated to capture disparities, such as higher LC incidence among males in China (3.52 ASR vs. 0.59 for females). Uncertainty intervals accounted for stochastic variation in demographic and epidemiological assumptions. For GC, the model highlighted diverging trajectories, with China’s rising incidence (+ 1.12% AAPC) contrasting with Japan’s declines (-2.02% AAPC). Validation tests compared projected 2022 estimates against observed data to ensure model accuracy. Ethical Considerations No ethical approval was required as the study used aggregated, anonymized secondary data. All analyses adhered to GBD collaboration guidelines for transparency and reproducibility. Results Burden of Liver-Related Cancers Burden by Country and Sex For GC, China reported the highest absolute burden, with 1,119 incident cases (95% UI: 689-1,456) and 28,214 DALYs (17,901 − 36,519) among both sexes. Males in China exhibited significantly higher incidence rates (0.27 per 100,000, 0.14–0.37) and DALYs (6.73, 3.68–9.07) compared to females (incidence rate: 0.12; DALYs: 3.18). The United States recorded 185 incident cases (175–196) and 2,135 DALYs (2,037 − 2,238), while the United Kingdom showed the lowest mortality rate (0.03 per 100,000) and DALYs (373, 358–388). Japan and the Republic of Korea reported moderate burdens, with Japan’s mortality rate at 0.07 (0.07–0.07) and Korea’s DALYs at 967 (690-1,423) ( Table 1 ) . Table 1 Burden of liver-related cancers among five countries in 2021 location sex Incidence Prevalence Deaths DALYs Number (95% UI) ASR (95% UI, per 100,000) Number (95% UI) ASR (95% UI, per 100,000) Number (95% UI) ASR (95% UI, per 100,000) Number (95% UI) ASR (95% UI, per 100,000) Gallbladder and Biliary Tract Cancer China Both 1119 (689–1456) 0.2 (0.12–0.26) 2519 (1525–3284) 0.44 (0.27–0.57) 501 (317–647) 0.09 (0.06–0.11) 28214 (17901–36519) 5.01 (3.19–6.5) Female 316 (193–468) 0.12 (0.07–0.17) 684 (414–1006) 0.25 (0.15–0.37) 149 (92–221) 0.06 (0.03–0.08) 8431 (5221–12501) 3.18 (1.97–4.72) Male 803 (427–1089) 0.27 (0.14–0.37) 1835 (971–2501) 0.62 (0.33–0.84) 352 (192–474) 0.12 (0.06–0.16) 19783 (10793–26630) 6.73 (3.68–9.07) Japan Both 54 (49–60) 0.14 (0.13–0.16) 112 (100–128) 0.3 (0.26–0.34) 26 ( 26 – 27 ) 0.07 (0.07–0.07) 1487 (1444–1537) 3.98 (3.86–4.11) Female 27 ( 24 – 32 ) 0.15 (0.13–0.17) 56 (48–68) 0.3 (0.26–0.36) 13 ( 13 – 14 ) 0.07 (0.07–0.08) 754 (725–785) 4.12 (3.96–4.29) Male 27 ( 24 – 31 ) 0.14 (0.12–0.16) 56 (47–65) 0.29 (0.24–0.34) 13 ( 13 – 14 ) 0.07 (0.07–0.07) 733 (702–767) 3.85 (3.68–4.03) Republic of Korea Both 35 (24–52) 0.18 (0.13–0.27) 72 (50–108) 0.38 (0.26–0.56) 17 ( 12 – 25 ) 0.09 (0.06–0.13) 967 (690–1423) 5.12 (3.65–7.52) Female 17 ( 11 – 28 ) 0.19 (0.12–0.31) 35 (22–57) 0.39 (0.25–0.63) 9 ( 6 – 14 ) 0.1 (0.06–0.16) 479 (310–790) 5.4 (3.5–8.9) Male 18 ( 10 – 30 ) 0.18 (0.1–0.3) 37 (21–62) 0.37 (0.2–0.62) 9 ( 5 – 14 ) 0.09 (0.05–0.14) 488 (284–795) 4.86 (2.82–7.93) United Kingdom Both 33 ( 31 – 35 ) 0.13 (0.13–0.14) 107 (101–112) 0.43 (0.41–0.46) 7 ( 6 – 7 ) 0.03 (0.03–0.03) 373 (358–388) 1.52 (1.46–1.58) Female 15 ( 14 – 16 ) 0.12 (0.11–0.13) 45 (41–49) 0.36 (0.33–0.39) 4 ( 3 – 4 ) 0.03 (0.03–0.03) 202 (192–212) 1.61 (1.53–1.69) Male 18 ( 17 – 19 ) 0.15 (0.14–0.16) 61 (57–65) 0.51 (0.48–0.55) 3 ( 3 – 3 ) 0.02 (0.02–0.03) 172 (162–181) 1.43 (1.35–1.51) United States of America Both 185 (175–196) 0.15 (0.15–0.16) 585 (553–619) 0.49 (0.46–0.52) 37 (36–39) 0.03 (0.03–0.03) 2135 (2037–2238) 1.79 (1.71–1.88) Female 87 (80–94) 0.14 (0.13–0.16) 263 (242–286) 0.44 (0.4–0.48) 20 ( 19 – 21 ) 0.03 (0.03–0.04) 1137 (1073–1208) 1.91 (1.8–2.02) Male 98 (92–105) 0.16 (0.15–0.18) 322 (300–344) 0.54 (0.5–0.58) 17 ( 16 – 18 ) 0.03 (0.03–0.03) 998 (947–1050) 1.68 (1.59–1.76) Liver Cancer China Both 11860 (9150–15390) 2.1 (1.62–2.72) 23940 (18566–30989) 4.26 (3.3–5.5) 8653 (6666–11215) 1.54 (1.19–1.99) 488461 (376620–632830) 87.71 (67.62-113.54) Female 1540 (1121–2084) 0.59 (0.43–0.79) 3354 (2440–4530) 1.28 (0.93–1.72) 1092 (795–1486) 0.42 (0.31–0.57) 62668 (45600–85179) 24.47 (17.81–33.14) Male 10320 (7753–13777) 3.52 (2.64–4.7) 20586 (15530–27457) 7.04 (5.3–9.38) 7561 (5670–10102) 2.59 (1.94–3.46) 425793 (319437–569130) 146.73 (109.93–196.2) Japan Both 120 (107–134) 0.32 (0.29–0.36) 344 (297–395) 0.94 (0.81–1.08) 60 (58–62) 0.16 (0.16–0.17) 3418 (3291–3550) 9.42 (9.06–9.78) Female 39 (33–46) 0.22 (0.18–0.26) 123 (97–152) 0.7 (0.55–0.87) 18 ( 17 – 18 ) 0.1 (0.09–0.1) 1020 (972–1068) 5.83 (5.55–6.1) Male 80 (70–92) 0.42 (0.37–0.48) 221 (187–259) 1.17 (0.99–1.38) 42 (40–44) 0.22 (0.21–0.23) 2398 (2282–2523) 12.87 (12.25–13.55) Republic of Korea Both 270 (182–393) 1.42 (0.95–2.06) 709 (478–1030) 3.74 (2.52–5.43) 141 (96–206) 0.74 (0.5–1.08) 7825 (5329–11438) 41.51 (28.28–60.58) Female 69 (42–108) 0.79 (0.48–1.24) 202 (117–321) 2.32 (1.34–3.7) 32 (20–48) 0.37 (0.23–0.55) 1818 (1154–2727) 21.16 (13.35–31.88) Male 201 (120–320) 1.97 (1.18–3.14) 507 (301–823) 5 (2.96–8.11) 109 (67–172) 1.07 (0.66–1.69) 6007 (3694–9512) 59.65 (36.6-94.52) United Kingdom Both 161 (153–170) 0.68 (0.64–0.72) 450 (424–476) 1.9 (1.79–2.01) 88 (84–92) 0.37 (0.36–0.39) 5115 (4908–5340) 21.83 (20.96–22.78) Female 56 (53–60) 0.47 (0.44–0.5) 142 (132–152) 1.18 (1.09–1.26) 35 (33–37) 0.29 (0.28–0.3) 2034 (1950–2126) 17.18 (16.47–17.96) Male 105 (98–113) 0.9 (0.84–0.97) 308 (286–334) 2.65 (2.46–2.87) 53 (50–57) 0.46 (0.43–0.49) 3081 (2913–3284) 26.7 (25.25–28.44) United States of America Both 561 (531–592) 0.48 (0.45–0.51) 1407 (1327–1488) 1.2 (1.14–1.27) 290 (276–304) 0.25 (0.24–0.26) 17016 (16181–17855) 14.68 (13.96–15.41) Female 191 (178–204) 0.33 (0.31–0.35) 455 (423–487) 0.79 (0.73–0.84) 107 (101–113) 0.19 (0.18–0.2) 6312 (5973–6664) 11 (10.4-11.61) Male 370 (345–395) 0.63 (0.59–0.67) 952 (885–1021) 1.62 (1.51–1.74) 183 (172–194) 0.31 (0.29–0.33) 10704 (10061–11394) 18.35 (17.25–19.54) Pancreatic Cancer China Both 2821 (2231–3466) 0.5 (0.39–0.61) 5278 (4179–6457) 0.92 (0.73–1.13) 2349 (1855–2889) 0.41 (0.33–0.51) 131458 (103859–161638) 23.39 (18.47–28.8) Female 601 (433–807) 0.22 (0.16–0.3) 1183 (855–1590) 0.44 (0.32–0.59) 491 (351–659) 0.18 (0.13–0.25) 27718 (19839–37237) 10.5 (7.52–14.1) Male 2220 (1726–2810) 0.75 (0.58–0.95) 4095 (3181–5173) 1.38 (1.07–1.74) 1859 (1442–2337) 0.63 (0.49–0.79) 103741 (80483–130406) 35.47 (27.5-44.64) Japan Both 115 (111–119) 0.3 (0.29–0.32) 280 (259–303) 0.75 (0.69–0.81) 87 (85–90) 0.23 (0.22–0.24) 4877 (4732–5029) 13.06 (12.66–13.47) Female 52 (49–55) 0.28 (0.27–0.3) 134 (118–153) 0.74 (0.65–0.84) 39 (37–40) 0.21 (0.2–0.22) 2172 (2088–2255) 11.98 (11.51–12.44) Male 63 (60–66) 0.32 (0.31–0.34) 146 (132–161) 0.76 (0.69–0.84) 49 (47–51) 0.25 (0.24–0.26) 2704 (2596–2820) 14.1 (13.52–14.72) Republic of Korea Both 49 (38–65) 0.26 (0.2–0.34) 113 (85–147) 0.6 (0.45–0.78) 38 (29–50) 0.2 (0.15–0.26) 2116 (1608–2771) 11.24 (8.5-14.77) Female 21 ( 15 – 30 ) 0.23 (0.17–0.34) 51 (35–72) 0.57 (0.4–0.83) 16 ( 11 – 22 ) 0.18 (0.12–0.25) 880 (619–1249) 10.04 (7.03–14.27) Male 28 (19–40) 0.28 (0.19–0.4) 62 (42–90) 0.62 (0.41–0.9) 22 ( 15 – 32 ) 0.22 (0.15–0.32) 1236 (829–1774) 12.3 (8.23–17.74) United Kingdom Both 73 (70–75) 0.3 (0.29–0.31) 176 (168–182) 0.72 (0.69–0.75) 56 (53–57) 0.23 (0.22–0.23) 3108 (2989–3207) 12.76 (12.28–13.17) Female 29 ( 28 – 31 ) 0.24 (0.23–0.24) 71 (67–75) 0.57 (0.54–0.6) 22 ( 21 – 23 ) 0.18 (0.17–0.19) 1252 (1200–1304) 10.1 (9.68–10.53) Male 43 (41–45) 0.36 (0.34–0.38) 105 (99–110) 0.88 (0.82–0.92) 33 ( 31 – 35 ) 0.28 (0.26–0.29) 1856 (1760–1937) 15.56 (14.76–16.25) United States of America Both 398 (381–414) 0.33 (0.32–0.35) 1081 (1030–1132) 0.9 (0.86–0.95) 271 (260–282) 0.23 (0.22–0.24) 15190 (14560–15811) 12.74 (12.21–13.27) Female 159 (150–169) 0.27 (0.25–0.28) 501 (466–538) 0.84 (0.78–0.9) 105 (99–112) 0.18 (0.17–0.19) 5917 (5581–6283) 9.95 (9.38–10.57) Male 239 (227–250) 0.4 (0.38–0.42) 581 (548–611) 0.97 (0.92–1.02) 166 (158–174) 0.28 (0.26–0.29) 9272 (8807–9723) 15.55 (14.77–16.31) LC burden was overwhelmingly concentrated in China, with 11,860 incident cases (9,150 − 15,390), 8,653 deaths (6,666 − 11,215), and 488,461 DALYs (376,620–632,830) among both sexes. Male-specific disparities were stark: males in China had an incidence rate of 3.52 (2.64–4.7) and DALYs of 146.73 (109.93–196.2), nearly five times higher than females. The United States reported 561 incident cases (531–592) and 17,016 DALYs (16,181 − 17,855), while the United Kingdom observed lower mortality rates (0.37 per 100,000) but substantial DALYs (5,115, 4,908-5,340). Japan and Korea showed intermediate burdens, with Korea’s DALYs (7,825, 5,329 − 11,438) exceeding Japan’s (3,418, 3,291-3,550) ( Table 1 ) . PC burden varied widely across countries. China dominated in absolute numbers, with 2,821 incident cases (2,231-3,466), 2,349 deaths (1,855-2,889), and 131,458 DALYs (103,859 − 161,638) among both sexes. Males in China faced higher rates (incidence: 0.75; DALYs: 35.47) than females (incidence: 0.22; DALYs: 10.5). The United States reported 398 incident cases (381–414) and 15,190 DALYs (14,560 − 15,811), with males showing elevated mortality rates (0.28 per 100,000) compared to females (0.18). Japan and the United Kingdom exhibited lower burdens, with Japan’s DALYs at 4,877 (4,732-5,029) and the U.K.’s mortality rate at 0.23 (0.22–0.23). The Republic of Korea reported the lowest PC incidence (49 cases, 38–65) but notable sex disparities in DALYs (males: 12.3; females: 10.04). These findings underscore significant geographical and sex-based variations in the burden of liver-related cancers ( Table 1 and Fig. 1 ) . Trends in Liver-Related Cancers Burden by Country and Sex For GC, China exhibited rising incidence trends among both sexes (AAPC: 1.12% for Both, 1.88% for males), while Japan and the Republic of Korea reported declining incidence (Japan: -2.02% for Both; Korea: -1.58% for Both). Mortality rates decreased modestly across most countries, with China showing a slight decline (-0.87% for Both) and the United Kingdom recording the lowest mortality trends (-0.23% for Both). DALYs demonstrated mixed patterns, with the United States observing a marginal increase (1.15% for Both) compared to declines in Japan (-2.53% for Both) ( Table 2 and Fig. 2 ) . Table 2 Trends of liver-related cancers among five countries from 1990 to 2021 location sex inaapc_gc praapc_gc deaapc_gc daaapc_gc Gallbladder and Biliary Tract Cancer China Both 1.12 (1.01 to 1.23) 2.87 (2.78 to 2.96) -0.87 (-0.98 to -0.77) -0.84 (-0.95 to -0.74) China Female -0.25 (-0.38 to -0.12) 1.49 (1.42 to 1.57) -2.05 (-2.15 to -1.91) -2.01 (-2.1 to -1.88) China Male 1.88 (1.73 to 2.01) 3.7 (3.57 to 3.82) -0.19 (-0.3 to -0.08) -0.15 (-0.28 to -0.04) Japan Both -2.02 (-2.36 to -1.77) -1.52 (-1.81 to -1.37) -2.53 (-2.7 to -2.36) -2.5 (-2.66 to -2.34) Japan Female -2.07 (-2.43 to -1.69) -1.48 (-1.81 to -1.1) -2.43 (-2.85 to -2.12) -2.4 (-2.79 to -2.11) Japan Male -2 (-2.33 to -1.82) -1.52 (-1.85 to -1.33) -2.36 (-2.58 to -2.18) -2.32 (-2.54 to -2.14) Republic of Korea Both -1.58 (-2.03 to -1.27) -0.15 (-0.35 to 0.07) -3.1 (-3.29 to -2.88) -3.08 (-3.27 to -2.86) Republic of Korea Female -1.15 (-1.41 to -0.95) 0.36 (0.05 to 0.6) -2.79 (-3.02 to -2.61) -2.8 (-3.07 to -2.6) Republic of Korea Male -1.71 (-1.89 to -1.52) -0.37 (-0.52 to -0.23) -3.37 (-3.52 to -3.22) -3.35 (-3.5 to -3.21) United Kingdom Both 1.69 (1.32 to 1.93) 2.35 (2.01 to 2.55) -0.23 (-0.57 to 0) -0.13 (-0.43 to 0.08) United Kingdom Female 1.84 (1.58 to 2.02) 2.58 (2.35 to 2.75) -0.14 (-0.41 to 0.02) -0.13 (-0.38 to 0.04) United Kingdom Male 1.58 (1.13 to 1.93) 2.19 (1.78 to 2.47) -0.14 (-0.68 to 0.32) -0.11 (-0.63 to 0.33) United States of America Both 1 (0.67 to 1.31) 1.11 (0.85 to 1.3) -0.47 (-0.85 to -0.22) -0.43 (-0.81 to -0.18) United States of America Female 0.74 (0.3 to 1.17) 1.15 (0.87 to 1.44) -0.33 (-0.69 to 0.02) -0.3 (-0.65 to 0.05) United States of America Male 0.82 (0.36 to 1.29) 1.17 (0.71 to 1.63) 0.01 (-0.28 to 0.27) 0.06 (-0.21 to 0.3) Liver Cancer China Both -0.57 (-0.68 to -0.46) -0.31 (-0.42 to -0.2) -1.16 (-1.36 to -0.96) -1.17 (-1.37 to -0.96) China Female -1.71 (-1.97 to -1.55) -1.26 (-1.51 to -1.1) -2.32 (-2.55 to -2.09) -2.33 (-2.57 to -2.08) China Male -0.32 (-0.47 to -0.22) -0.12 (-0.24 to -0.02) -0.93 (-1.11 to -0.73) -0.85 (-1.03 to -0.66) Japan Both -2.09 (-2.37 to -1.92) -1.46 (-1.73 to -1.29) -2.89 (-3.07 to -2.71) -2.82 (-2.99 to -2.65) Japan Female -0.73 (-0.83 to -0.63) -0.42 (-0.52 to -0.32) -1.39 (-1.57 to -1.2) -1.38 (-1.56 to -1.17) Japan Male -2.64 (-2.85 to -2.49) -1.93 (-2.17 to -1.77) -3.43 (-3.63 to -3.23) -3.36 (-3.57 to -3.15) Republic of Korea Both -2.41 (-2.53 to -2.28) -1.26 (-1.4 to -1.18) -3.94 (-4.16 to -3.72) -3.93 (-4.15 to -3.71) Republic of Korea Female -1.31 (-1.39 to -1.23) 0.03 (-0.13 to 0.16) -3.22 (-3.44 to -3.03) -3.23 (-3.41 to -3.08) Republic of Korea Male -2.82 (-2.96 to -2.69) -1.82 (-1.91 to -1.74) -4.23 (-4.55 to -3.94) -4.27 (-4.59 to -3.99) United Kingdom Both 4.31 (4.22 to 4.38) 4.97 (4.89 to 5.03) 3.45 (3.2 to 3.67) 3.43 (3.18 to 3.66) United Kingdom Female 3.9 (3.71 to 4.04) 4.34 (4.23 to 4.41) 3.24 (3.04 to 3.42) 3.21 (3 to 3.4) United Kingdom Male 4.58 (4.52 to 4.64) 5.32 (5.23 to 5.39) 3.5 (3.24 to 3.76) 3.48 (3.23 to 3.73) United States of America Both 1.83 (1.76 to 1.88) 2.33 (2.22 to 2.38) 1.15 (0.93 to 1.31) 1.19 (0.95 to 1.34) United States of America Female 1.89 (1.83 to 1.93) 2.29 (2.24 to 2.32) 1.36 (1.07 to 1.54) 1.35 (1.02 to 1.52) United States of America Male 1.77 (1.67 to 1.84) 2.32 (2.2 to 2.39) 1.15 (0.79 to 1.42) 1.2 (0.91 to 1.43) Pancreatic Cancer China Both 0.44 (0.33 to 0.57) 0.78 (0.6 to 0.94) 0.22 (0.12 to 0.35) 0.22 (0.12 to 0.34) China Female -0.72 (-0.82 to -0.62) -0.35 (-0.48 to -0.25) -1 (-1.1 to -0.89) -1.02 (-1.12 to -0.92) China Male 0.85 (0.65 to 1.02) 1.17 (0.95 to 1.36) 0.68 (0.52 to 0.82) 0.69 (0.51 to 0.84) Japan Both -0.08 (-0.28 to 0.11) 0.29 (-0.02 to 0.52) -0.26 (-0.49 to 0) -0.21 (-0.44 to 0.04) Japan Female 0.38 (0.04 to 0.66) 0.93 (0.54 to 1.23) 0.09 (-0.17 to 0.36) 0.13 (-0.12 to 0.4) Japan Male -0.52 (-0.74 to -0.31) -0.43 (-0.73 to -0.08) -0.76 (-0.96 to -0.55) -0.74 (-0.96 to -0.52) Republic of Korea Both -1.72 (-1.88 to -1.53) -0.8 (-0.94 to -0.69) -2.12 (-2.3 to -1.91) -2.16 (-2.32 to -1.97) Republic of Korea Female -0.32 (-0.47 to -0.19) 0.69 (0.47 to 0.86) -0.83 (-1 to -0.69) -0.86 (-1.03 to -0.72) Republic of Korea Male -2.42 (-2.56 to -2.26) -1.65 (-1.83 to -1.5) -2.76 (-2.91 to -2.59) -2.76 (-2.91 to -2.6) United Kingdom Both 0.29 (0.07 to 0.45) 0.82 (0.55 to 1) 0.11 (-0.13 to 0.27) 0.1 (-0.15 to 0.26) United Kingdom Female 0.17 (-0.03 to 0.28) 0.55 (0.35 to 0.69) -0.02 (-0.21 to 0.1) -0.05 (-0.25 to 0.08) United Kingdom Male 0.51 (0.17 to 0.73) 0.91 (0.59 to 1.12) 0.21 (-0.08 to 0.41) 0.2 (-0.09 to 0.4) United States of America Both 0.16 (0 to 0.28) 0.59 (0.37 to 0.74) -0.12 (-0.27 to -0.01) -0.11 (-0.25 to 0.01) United States of America Female 0.39 (-0.15 to 0.69) 1.06 (0.75 to 1.33) -0.01 (-0.19 to 0.17) 0.01 (-0.18 to 0.19) United States of America Male 0.03 (-0.2 to 0.22) 0.54 (0.37 to 0.7) -0.25 (-0.48 to -0.07) -0.22 (-0.47 to -0.05) LC burden varied significantly by region. China reported moderate declines in incidence (-0.57% for Both) and mortality (-1.16% for Both), while the United Kingdom experienced sharp increases in incidence (4.31% for Both) and DALYs (3.45% for Both). Japan and Korea showed consistent reductions across metrics, particularly in mortality (Japan: -2.89% for Both; Korea: -3.94% for Both). The United States displayed stable incidence trends (1.83% for Both) but rising DALYs (1.15% for Both). Sex-specific disparities were notable, with female populations in China and Japan experiencing steeper mortality declines than males ( Table 2 and Fig. 2 ) . For PC, China demonstrated rising incidence (0.44% for Both) and mortality (0.22% for Both), contrasting with declines in Korea (-1.72% for Both) and Japan (-0.08% for Both). The United Kingdom and United States reported mixed trends, with the U.K. showing modest incidence growth (0.29% for Both) and the U.S. stabilizing mortality (-0.12% for Both). Female populations in China and Korea faced sharper mortality reductions (-1.02% and − 0.86%, respectively) compared to males. Overall, DALYs remained stable or declined slightly in high-income nations, while China’s DALYs increased marginally (0.22% for Both). These trends highlight heterogeneous patterns in liver-related cancer burdens, influenced by regional and sex-specific factors ( Table 2 and Fig. 2 ) . Projected Burden of Three Liver-Related Cancers in Five Countries (2022–2025) This study employs the BAPC model to project the future burden of three liver-related cancers—LC, PC, and GC—across five countries (China, Japan, Republic of Korea, United Kingdom, and United States of America) for 2022 and 2025, integrating both ASR (ASRs) and absolute numerical estimates for incidence, prevalence, deaths, and DALY (DALYs), along with their uncertainty intervals ( Fig. 3 ) . For LC, China dominates in both ASRs and absolute burden. The age-standardized incidence rate rises from 2.23 per 100,000 (95% UI: 1.87–2.59) in 2022 to 2.28 (1.49–3.07) in 2025, while absolute incident cases increase from 12,999.62 (10,923.09-15,076.15) to 13,417.95 (8,814.41-18,021.50) over the same period. China’s DALYs remain disproportionately high, with ASRs at 94.39 (75.37-113.41) in 2022 and 96.12 (58.30-133.94) in 2025, translating to absolute DALYs of 544,622.75 (435,038.57–654,206.93) and 555,296.56 (337,127.53–773,465.60), respectively. The United States, though exhibiting lower ASRs, reports substantial absolute DALYs (18,493.22 to 18,618.73) due to its larger population. Japan and the Republic of Korea show moderate ASRs but notable burdens in prevalence (Japan: 300.37 to 265.36; Korea: 638.69 to 608.17), while the United Kingdom faces gradual increases in deaths (93.92 to 103.23) ( Fig. 3 ) . PC projections highlight rising trends in China, with ASR incidence increasing from 0.52 (0.45–0.59) to 0.55 (0.44–0.65) and absolute cases surging from 3,046.60 (2,637.31-3,455.89) to 3,278.79 (2,673.09-3,884.48). Corresponding DALYs escalate from 26.02 to 27.82 (ASR) and 151,549.86 to 164,465.17 (absolute). The United States reports the highest absolute PC deaths (294.35 to 302.74), despite stable ASR mortality (~ 0.24), while Japan and Korea exhibit uncertain mortality trends (Japan: 0.23–0.24 ASR; 81.02–79.73 absolute deaths). The United Kingdom’s DALYs decline marginally (2,899.27 to 2,561.58) ( Fig. 3 ) . GC projections reveal disparities: China’s ASR mortality remains stable (~ 0.11) but absolute deaths grow from 519.04 (386.97–651.10) to 522.85 (365.83-679.87), with DALYs persistently elevated (ASR: 6.50–6.45; absolute: 29,332.95-29,138.40). The United States reports higher absolute mortality (41.81 to 45.31) compared to the United Kingdom’s low ASR (0.03) and absolute deaths (6.26 to 6.48). Japan and Korea face uncertainty in ASR deaths (Japan: 0.09 in 2025, UI: 0.01–0.19; Korea: 0.09–0.09) and absolute trends (Japan: 25.09–23.16; Korea: 14.00-12.29) ( Fig. 3 ) . Discussion Differences in the burden and drivers of GC, with China leading the world in the number of morbidity and mortality cases of GC( 23 ). as the country with the largest burden. This is associated with China's large population base and geographic exposure differences. Gender differences are evident, with the age-standardized incidence rate (ASIR) for men in China being 1.8 times higher than that for women( 24 ). This was associated with a higher prevalence of smoking (attributable risk 24.1%) and occupational exposure (e.g., chemical industry) in men( 25 ). In a regional trend analysis of gallbladder and biliary tract cancers (GC), China's ASIR continued to rise (0.8% annual increase), but age-standardized mortality rate (ASMR) declined due to the prevalence of surgery( 15 , 23 ). Japan and Korea are both on a downward trend( 26 ). Attributed to early screening (> 70% ultrasound prevalence in Japan) and standardization of cholecystectomy. The UK has the lowest ASMR ( 30). There are two underlying drivers, one of which is intervenable risk, with approximately 31% of GBTC deaths globally associated with high BMI and diabetes, with a higher attribution in East Asia (37.2% in China)( 27 ). The second is diagnostic and treatment disparities, with inadequate coverage of endoscopic technology in primary care in China (< 30% of county hospitals)( 23 ). In Japan, the early diagnosis rate is over 50%. Extreme regional polarization of the burden of LC, with China leading the global burden, accounting for 46.3% of global liver cancer deaths( 28 ). Significant difference in sex ratio, Chinese male ASIR is 4.5 times higher than that of females( 28 ). Mainly attributed to significantly higher rates of HBV infection (8.3%) and alcohol consumption (48%) in men( 29 ). Trend reversal in Europe and the US, China: decline in ASIR due to hepatitis B vaccination (coverage > 95%)( 22 ). ASIR in the UK has risen 42% in the last decade( 30 ). Associated with NAFLD (prevalence 25%) and late diagnosis. Changes in etiologic contribution, HBV remains dominant in China (68.4% of attributable deaths), but metabolic risk is growing fast (12% increase in attributable DALYs from 2010–2019)( 31 ). HCV contribution declines in Japan and Korea (antiviral treatment coverage > 80% in Japan), but alcohol-related liver cancer rises in Korean men( 32 ). Trend-differentiated characteristics of PC, ASIR continued increase in China (1.1% per year), urbanization-associated obesity (25.7% obesity rate in urban males) as the main cause( 33 ). Decline in ASIR in Japan and Korea, associated with tobacco control (< 25% male smoking in Japan). Sex differences in mortality rates, with both Chinese and American males having higher ASMR than females (U.S. M:F = 1.4:1). In China, ASMR declined more rapidly in women (1.1% per year vs. 0.6% in men)( 34 ). Key risk-driven evidence, with significant attribution to smoking: in Korea, smoking contributes 31.2% of PC deaths (37.4% in men). The role of metabolic syndrome, about 19% of PC deaths globally are associated with hyperglycemia, with 28.4% of deaths in China attributed to hyperglycemia( 34 ). Deeper motivations for regional differences, infection control determines liver cancer burden, and HBV vaccination in China reduces childhood infection rate to 1%( 28 ). However, stockpiled infections in the elderly population continue to drive up mortality (> 65 years accounts for 68% of deaths)( 35 ). Differences in health systems affect GBTC outcomes; 5-year survival rate for gallbladder cancer in China is only 19%, much lower than in Japan (40%)( 23 ). Reflecting differences in early screening and treatment standardization. “Westernization” of Diet and Metabolic Risk: Processed Meat Intake Increases 80% in 30 Years in China and South Korea, Pushing PC Risk Higher( 34 ). Conclusion Priority areas of intervention, China Strengthening hepatitis B antiviral treatment continuity and investment in GBTC screening equipment at the grassroots level.Japan and Korea Expand HCV screening and alcohol control policies (e.g., 30% tax increase in Korea)( 36 ). UK and US Develop community intervention guidelines for NAFLD. Gender-differentiated prevention and control Promote early detection of HCC for East Asian men and design metabolic risk interventions for women (e.g., China Diabetes Screening Program)( 12 ). Declarations Acknowledgments The authors are deeply grateful to the Institute for Health Metrics and Evaluation (IHME) at the University of Washington for generously providing access to the data that supported this research. We also extend our sincere appreciation to the reviewers and editors for their insightful comments and rigorous evaluation, which greatly contributed to the improvement of this manuscript. Author contributions Shuang Zhang(First author)：Writing – original draft、Formal analysis、Investigation、Software;Yaxin Hu(Second author)：Writing – review & editing、Data curation、Methodology/Validation; Dawei Guo(Third author): Writing – review & editing、Conceptualization、Resources、Validation;Xiaobo Li(Corresponding author): Writing – review & editing、Funding acquisition、Resources、Supervision;Jiuzhang Men(Corresponding author): Writing – review & editing、Funding acquisition、Methodology、Project administration;Yuming Zhang(Corresponding author): Writing – review & editing、Formal analysis、Validation;Jilong Guo(Corresponding author): Writing – review & editing、Conceptualization、Resources Funding This study was supported by the research project of Shanxi Provincial Association for Science and Technology, “Research on high-quality development of traditional Chinese medicine business in Shanxi”, the Fund of Clinical Basic Disciplines of Traditional Chinese Medicine of Shanxi University of Traditional Chinese Medicine, and the lateral project of North Central University (No. 202102130501011). Data availability statement The raw data presented in this study are included in the body of the article/supplementary material, and further data needs can be addressed to the first author for consultation. Ethics approval and consent to participate Not applicable. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. Author details 1. Shanxi University of Traditional Chinese Medicine, School of Basic Medical Sciences 2. The Fourth Clinical College of Shanxi University of Traditional Chinese Medicine References Tan DJH, Setiawan VW, Ng CH, Lim WH, Muthiah MD, Tan EX, et al. Global burden of liver cancer in males and females: Changing etiological basis and the growing contribution of NASH. Hepatology. 2022;77(4):1150-63. Kocarnik JM, May M, Acheson A, Bhangdia K, Compton K, Dean F, et al. The global burden of primary liver cancer and underlying etiologies from 1990 to 2021. Journal of Clinical Oncology. 2024;42:10573-. Teng Y, Xia C, Li H, Cao M, Yang F, Yan X, et al. Cancer statistics for young adults aged 20 to 49 years in China from 2000 to 2017: a population-based registry study. Sci China Life Sci. 2024;67(4):711-9. Jiang Z, Zeng G, Dai H, Bian Y, Wang L, Cao W, et al. Global, regional and national burden of liver cancer 1990-2021: a systematic analysis of the global burden of disease study 2021. BMC public health. 2025. Chutian W, Giovanni T, D BC, Yilei M, To CT, Yusuf Y, et al. Global, regional, and national burden of primary liver cancer attributable to metabolic risks: an analysis of the Global Burden of Disease Study 1990-2021. American Journal of Gastroenterology. 2025. Kocarnik JM, May M, Acheson A, Bhangdia K, Compton K, Dean F, et al. The global burden of primary liver cancer and underlying etiologies from 1990 to 2021. Journal of Clinical Oncology. 2024. Danpanichkul P, Pang Y, Díaz LA, White TM, Sirimangklanurak S, Auttapracha T, et al. Alcohol-Attributable Cancer: Update From the Global Burden of Disease 2021 Study. Alimentary Pharmacology & Therapeutics. 2025. Ilic I, Ilic M. Global Burden of Pancreatic Cancer Attributable to High Body-Mass Index in 204 Countries and Territories, 1990–2019. Cancers. 2024;16(4):719. Danpanichkul P, Auttapracha T, Sukphutanan B, Ng CH, Wattanachayakul P, Kongarin S, et al. The Burden of Overweight and Obesity-Associated Gastrointestinal Cancers in Low and Lower-Middle-Income Countries: A Global Burden of Disease 2019 Analysis. American Journal of Gastroenterology. 2024;119(6):1177-80. Danpanichkul P, Suparan K, Tothanarungroj P, Dejvajara D, Rakwong K, Pang Y, et al. Epidemiology of gastrointestinal cancers: a systematic analysis from the Global Burden of Disease Study 2021. Gut. 2024;74(1):26-34. Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020. Kocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, Harvey JD, et al. Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019. JAMA Oncol. 2022. Calderaro J, Žigutytė L, Truhn D, Jaffe A, Kather JN. Artificial intelligence in liver cancer — new tools for research and patient management. Nature Reviews Gastroenterology & Hepatology. 2024;21(8):585-99. Xia Z, Han W, Niu H, Dong H. Global Burden of Pancreatic Cancer Among Individuals Aged 15–59 Years in 204 Countries and Territories, 1990–2021: A Systematic Analysis for the GBD 2021 and Projections to 2045. Cancers. 2025;17(11):1757. Bao W, Qiao L, Li M, Shi G, Liu L. Trends and cross-country inequalities in the global, regional, and national burden of gallbladder and biliary tract cancer from 1990 to 2021, along with the predictions for 2035. Cancer Epidemiology. 2025;96:102802. Danpanichkul P, Ng CH, Tan DJH, Muthiah MD, Kongarin S, Srisurapanont K, et al. The Global Burden of Early-Onset Biliary Tract Cancer: Insight From the Global Burden of Disease Study 2019. Journal of Clinical and Experimental Hepatology. 2024;14(2):101320. Sheena BS, Hiebert L, Han H, Ippolito H, Abbasi-Kangevari M, Abbasi-Kangevari Z, et al. Global, regional, and national burden of hepatitis B, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Gastroenterology & Hepatology. 2022;7(9):796-829. Eluri M, Hatia R, Javle MM, Hassan M. The association of family history of primary liver cancer with cholangiocarcinoma: USA case-control study. Journal of Clinical Oncology. 2022;40:403-. Chotiprasidhi P, Sato-Espinoza AK, Wangensteen KJ. Germline Genetic Associations for Hepatobiliary Cancers. Cellular and Molecular Gastroenterology and Hepatology. 2024;17(4):623-38. Calderaro J, Žigutytė L, Truhn D, Jaffe A, Kather JN. Artificial intelligence in liver cancer — new tools for research and patient management. Nature Reviews Gastroenterology & Hepatology. 2024. Pang Y, Lv J, Kartsonaki C, Yu C, Guo Y, Chen Y, et al. Genetic and healthy lifestyle factors in relation to the incidence and prognosis of severe liver disease in the Chinese population. Chinese Medical Journal. 2023;136(16):1929-36. Han J, Chen C, Tang T, Liu W, Chen R, Li S, et al. Burden of Liver Cancer in China from 1990 to 2019 and projections to 2044: Findings from the Global Burden of Disease Study. 2023. Chen S, Han K, Song Y, Liu S, Li X, Wang S, et al. Current status, trends, and predictions in the burden of gallbladder and biliary tract cancer in China from 1990 to 2019. Chinese Medical Journal. 2022;135(14):1697-706. Dutta P, Danpanichkul P, Suparan K, Pang Y, Rakwong K, Fine MR, et al. Sex disparities in global burden of gallbladder and biliary tract cancer: analysis of Global Burden of Disease study from 2010 to 2019. Journal of Gastroenterology and Hepatology. 2024;39(12):2863-71. Wu S, Zhao R, Zhuang Q, Li MT, Qian YQ, Ye X, et al. Disease burden of primary gallbladder and biliary tract cancers associated with body mass index in 195 countries and territories, 1990‐2017: A systematic analysis for the Global Burden of Disease Study 2017. Journal of Digestive Diseases. 2022;23(3):157-65. Jung K-W, Kang MJ, Park EH, Yun EH, Kim H-J, Kim J-E, et al. Prediction of Cancer Incidence and Mortality in Korea, 2024. Cancer Research and Treatment. 2024;56(2):372-9. Xie D, Liu F, Zhou D, Zhu Q, Xiao F, Zhang K. Global burden and cross-country inequalities in gallbladder and biliary tract cancer (1990–2021) with projections to 2050: insights from the global burden of disease study 2021. Front Med. 2025;12. Li Q, Ding C, Cao M, Yang F, Yan X, He S, et al. Global epidemiology of liver cancer 2022: An emphasis on geographic disparities. Chinese Medical Journal. 2024;137(19):2334-42. Lin L, Yan L, Liu Y, Qu C, Ni J, Li H. The Burden and Trends of Primary Liver Cancer Caused by Specific Etiologies from 1990 to 2017 at the Global, Regional, National, Age, and Sex Level Results from the Global Burden of Disease Study 2017. Liver Cancer. 2020;9(5):563-82. Qiu H, Cao S, Xu R. Cancer incidence, mortality, and burden in China: a time‐trend analysis and comparison with the United States and United Kingdom based on the global epidemiological data released in 2020. Cancer Communications. 2021;41(10):1037-48. Cao M, Xia C, Cao M, Yang F, Yan X, He S, et al. Attributable liver cancer deaths and disability-adjusted life years in China and worldwide: profiles and changing trends. Cancer Biology & Medicine. 2024:1-13. Yang S, Deng Y, Zheng Y, Zhang J, He D, Dai Z, et al. Burden, trends, and predictions of liver cancer in China, Japan, and South Korea: analysis based on the Global Burden of Disease Study 2021. Hepatology International. 2025;19(2):441-59. Yan F, Yu L, Liu Z, Qi J, Wang L, Zhou M, et al. Subnational trend and driving factors for pancreatic cancer burden in China, 1990–2021: an analysis based on the Global Burden of Disease Study 2021. Annals of Medicine. 2025;57(1). Chen Y, Chen T, Fang J-Y. Burden of gastrointestinal cancers in China from 1990 to 2019 and projection through 2029. Cancer Letters. 2023;560:216127. Ding C, Fu X, Zhou Y, Liu X, Wu J, Huang C, et al. Disease burden of liver cancer in China from 1997 to 2016: an observational study based on the Global Burden of Diseases. BMJ Open. 2019;9(4). Katanoda K, Ito Y, Sobue T. International comparison of trends in cancer mortality: Japan has fallen behind in screening-related cancers. Japanese Journal of Clinical Oncology. 2021;51(11):1680-6. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7432498","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":525364791,"identity":"910dd157-77dc-4ac1-8eea-0c0761e9edc2","order_by":0,"name":"Shuang Zhang","email":"","orcid":"","institution":"Shanxi University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Shuang","middleName":"","lastName":"Zhang","suffix":""},{"id":525364792,"identity":"f59e714c-99f2-4d24-a60c-28da5e075f6a","order_by":1,"name":"Yaxin Hu","email":"","orcid":"","institution":"Shanxi University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yaxin","middleName":"","lastName":"Hu","suffix":""},{"id":525364793,"identity":"b89d322f-466c-4baf-94f0-8c2c4ec13ec2","order_by":2,"name":"Dawei Guo","email":"","orcid":"","institution":"Shanxi University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Dawei","middleName":"","lastName":"Guo","suffix":""},{"id":525364794,"identity":"4b6481e7-c9c1-4a32-9d01-18e6fb619768","order_by":3,"name":"Xiaobo Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYBACPmYGhgMgJM/ffODAhwoitLDBtBjOOJZ4cMYZYrRAKJCuHOPDvC3EaGHnMTzwo+KOHGPDmQ8HeBuADhQ7QMhhbAkHe848M2Zn7t1wQHIHg+HM2QmEtDAfOMDbdjixseHshgOGZxgSDG4T1MLYcPAvUEvDgZwHBxLbiNLCfOAwL0QLw4GDxGlhSzgsA/QLMJANDjackSDsF37+M8Yf3wBDDBiVjz//qbCR55cmoAUdSJCmfBSMglEwCkYBdgAA3o5MvyFg5GAAAAAASUVORK5CYII=","orcid":"","institution":"Shanxi University of Traditional Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Xiaobo","middleName":"","lastName":"Li","suffix":""},{"id":525364795,"identity":"7f6057f9-abcf-435a-99f8-8708818b4aeb","order_by":4,"name":"Jiuzhang Men","email":"","orcid":"","institution":"Shanxi University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiuzhang","middleName":"","lastName":"Men","suffix":""},{"id":525364796,"identity":"20d32318-39e8-42be-92ef-6ac8322736c1","order_by":5,"name":"Yuming Zhang","email":"","orcid":"","institution":"Shanxi University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuming","middleName":"","lastName":"Zhang","suffix":""},{"id":525364797,"identity":"65be68fb-1605-4eaa-93b0-03a7dc056831","order_by":6,"name":"Jilong Guo","email":"","orcid":"","institution":"The Fourth Clinical College of Shanxi University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jilong","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2025-08-22 08:38:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7432498/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7432498/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93240768,"identity":"7e148020-1959-4cb2-86ff-9566ca795d24","added_by":"auto","created_at":"2025-10-10 14:47:42","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4061526,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/5093a9f8b97b4672165a5b1f.jpg"},{"id":93239836,"identity":"7d63e13a-5ee8-4fde-88e6-07f13caa4bc7","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1038362,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/00e2f6318484572871d4633b.jpg"},{"id":93239840,"identity":"38d89ab5-9a12-40c6-b267-57dda8b7be74","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1966275,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptBMC2revisedmanuscript.docx","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/6582511a6633620ceb4fa638.docx"},{"id":93239835,"identity":"33e4dc16-980b-41a3-91a4-3f7590730cad","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2196531,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/c769e261a10bbc3eeecd1e3a.jpg"},{"id":93240765,"identity":"eb27c02e-3924-4f62-9df9-b8bc6322fce7","added_by":"auto","created_at":"2025-10-10 14:47:42","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38131,"visible":true,"origin":"","legend":"","description":"","filename":"Table1d1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/41fa49d21161a317ccaaf421.docx"},{"id":93240766,"identity":"d7025036-da14-49b5-96d2-f4ec70c70143","added_by":"auto","created_at":"2025-10-10 14:47:42","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":26437,"visible":true,"origin":"","legend":"","description":"","filename":"Table2d1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/edbd097b00c95e3c876a0c91.docx"},{"id":93239837,"identity":"46ba703a-96fa-424f-a959-e6feef20cf98","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"json","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9344,"visible":true,"origin":"","legend":"","description":"","filename":"01daebe0ec90448d84bb123a9af906d2.json","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/35f69ee70c0a22049bf02189.json"},{"id":93239842,"identity":"70004dd0-81d9-4a27-8327-e2a9c8448fd0","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38131,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/885d790192d8b6cc2dab3b09.docx"},{"id":93242966,"identity":"68ea31ff-9a6e-433e-af83-2e43b34d859c","added_by":"auto","created_at":"2025-10-10 14:55:42","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":26437,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/5545ac5767df59bcd47c65b7.docx"},{"id":93239844,"identity":"d7cda770-a203-49da-a8dc-33d987e06cd0","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":261950,"visible":true,"origin":"","legend":"","description":"","filename":"01daebe0ec90448d84bb123a9af906d21enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/f39a982e97217a097f1849df.xml"},{"id":93240769,"identity":"9350fc6e-c60f-4075-98e3-47302a25d010","added_by":"auto","created_at":"2025-10-10 14:47:42","extension":"jpg","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":4061526,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/cb05b6de07cb107173f31895.jpg"},{"id":93242967,"identity":"dea81a42-6ea6-42eb-ba11-f79cafa794ed","added_by":"auto","created_at":"2025-10-10 14:55:42","extension":"jpg","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1038362,"visible":true,"origin":"","legend":"","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/d65b0e0a215332671416dc48.jpg"},{"id":93239846,"identity":"96b40f79-bfd3-4085-b48d-214af68abe0e","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpg","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2196531,"visible":true,"origin":"","legend":"","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/7abe7da85bc5e8caf11b802b.jpg"},{"id":93239847,"identity":"e50223ab-e90b-4369-a917-7acfff6365d6","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpeg","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":739718,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/162025fb05f43ce5da194d44.jpeg"},{"id":93240771,"identity":"32734411-24c8-4070-8a79-1424dc3ffb72","added_by":"auto","created_at":"2025-10-10 14:47:43","extension":"jpeg","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":462696,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/39c7ac3c050d10f71641a988.jpeg"},{"id":93242968,"identity":"d10c4e8e-c60c-493e-a64e-a2132a5a7c6b","added_by":"auto","created_at":"2025-10-10 14:55:43","extension":"jpeg","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1486072,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/91c3069c101ce6b1b49d0940.jpeg"},{"id":93239857,"identity":"57371cab-9965-463d-aef9-583e24b907b8","added_by":"auto","created_at":"2025-10-10 14:39:43","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2386739,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/fce9012d3ef7fd8b9f305419.png"},{"id":93239852,"identity":"787d98c7-056d-465b-bacb-8cef16759509","added_by":"auto","created_at":"2025-10-10 14:39:43","extension":"png","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":426626,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/45713e0eb8187521489cec7b.png"},{"id":93239848,"identity":"a028acc2-2432-4b53-b566-a2e7a64943ed","added_by":"auto","created_at":"2025-10-10 14:39:43","extension":"png","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1260003,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/0713ef7d99ec12c7ea91d1c4.png"},{"id":93240773,"identity":"cb0bdc11-b6ab-4491-9a7b-9802f19cbcc8","added_by":"auto","created_at":"2025-10-10 14:47:43","extension":"png","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":197307,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/3fcc32c2ee3bb969fc89dde8.png"},{"id":93240772,"identity":"fe8c445e-8905-4a9e-bb53-e1e3c44cbe42","added_by":"auto","created_at":"2025-10-10 14:47:43","extension":"png","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":103286,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/96c29b3da65285eba0adcb67.png"},{"id":93239850,"identity":"a4e65362-dbd9-4bcf-b892-90765cbed298","added_by":"auto","created_at":"2025-10-10 14:39:43","extension":"png","order_by":21,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":302252,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/400f0feac459f9efeacc1e13.png"},{"id":93239856,"identity":"cbb86869-5a54-4446-b46a-d4cbbea493b2","added_by":"auto","created_at":"2025-10-10 14:39:43","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":264033,"visible":true,"origin":"","legend":"","description":"","filename":"01daebe0ec90448d84bb123a9af906d21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/4e256d180b45b563d9e3ae2b.xml"},{"id":93239853,"identity":"25e884b7-b4e1-41c1-bf7e-188dfde3b386","added_by":"auto","created_at":"2025-10-10 14:39:43","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":274604,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/95107b95662786118bb77416.html"},{"id":93239831,"identity":"c432772d-6144-4e53-91a6-f4c0b552ef61","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":547604,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/5c148b5626e19b75eaffc897.jpg"},{"id":93239833,"identity":"e3f0740e-308b-4e36-b8c1-8779d0d8d3ae","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":323512,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/bfb9efc891ed604873019984.jpg"},{"id":93239832,"identity":"968da8d8-b00b-4290-a584-65671cbb3788","added_by":"auto","created_at":"2025-10-10 14:39:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":438413,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/b0b7fccc080cc89577c08dc9.jpg"},{"id":96452968,"identity":"21f0afb7-f7b0-46a0-a7b1-b95e11a90403","added_by":"auto","created_at":"2025-11-21 09:56:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3008244,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7432498/v1/705d4725-615d-4c6e-bd3c-30f312667f9c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burden and Trends of Liver-Related Cancers, 1990–2021: A Comparative Analysis of China, Korea, Japan,the United Kingdom , and the United States","fulltext":[{"header":"Introduction","content":"\u003cp\u003ethe liver-related cancers occur mainly in the liver, gallbladder and bile ducts (bile ducts), and the three common types are cancer of the liver, pancreas, gallbladder and bile ducts(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). the liver-related cancers continue to threaten human health globally, especially in China, Japan, Korea, the United Kingdom, and the United States of America(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Despite its relatively small share in the global cancer spectrum, the high mortality rate poses a serious threat to human health, causing severe disease burden and social stress, especially in the Asia-Pacific region. According to the GBD study, men, the elderly, people with low socioeconomic status, and people living in Low- and Middle-Income Countries (LMICs) are the main victims of liver (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). High-risk groups include mainly men, the elderly, and patients with chronic liver disease or metabolic syndrome(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). The high prevalence of hepatocellular carcinoma in China, Korea and Japan is closely related to the prevalence of hepatitis B and C viruses (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), Whereas in Europe and the United States, such as the United Kingdom and the United States, nonalcoholic fatty liver disease (NAFLD), alcohol-related liver disease, and obesity-related metabolic disease have emerged as major risk factors (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Pancreatic cancer, on the other hand, is on the rise in high-income countries and is closely related to factors such as population ageing, smoking and diabetes(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In addition, gallbladder and biliary tract cancers are also associated with endemic diseases such as gallstones and hepatic schistosomiasis in some regions, showing obvious regional differences. liver-related cancers have a profound impact on the socio-economic and health care systems(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). liver-related cancers often lead to prolonged hospitalization, repeated treatments and even income disruption, increasing the financial burden on families. In areas where effective health insurance coverage is lacking, many families fall into \u0026ldquo;poverty due to illness\u0026rdquo; because they cannot afford expensive targeted drugs and treatments. Even in high-income countries, these cancers place a significant strain on health care finances, and GBD studies have shown that these cancers result in significantly more premature deaths (YLLs) and disability-adjusted life years (DALYs) than most common cancers(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Especially in low- and middle-income countries, the economic impact far exceeds the average level of social spending on health care. According to data from the GBD study, there is significant geographic heterogeneity in the incidence patterns, mortality rates, and burden of disease for this group of cancers. This heterogeneity is closely related to the Socio-demographic Index (SDI), which quantifies regional development by combining indicators such as income level, educational attainment and total fertility rate(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). SDI stratification analysis shows that age-standardized mortality rates for the liver-related cancers in high SDI regions (e.g., North America, Western Europe) are trending downward, whereas the burden continues to increase in low and medium SDI regions (e.g., East Asia, South Asia) due to delayed diagnosis, insufficient therapeutic resources, and differences in risk factor exposure. In the case of liver, for example, the mortality rate in low SDI regions is 2.3 times higher than that in high SDI regions, and 80% of liver is already in advanced stages when diagnosed(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). The 5-year survival rate for pancreatic cancer is less than 10% in low SDI areas, significantly lower than the 13% in high SDI areas, highlighting the unequal distribution of healthcare resources(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The distribution of gallbladder and biliary tract cancers (GBTC) is more polarized. Of these, 73% were concentrated in low SDI areas, reflecting the synergistic effect of geographic-specific risk factors (e.g., biliary parasitic infections) and health system weaknesses(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Notably, early-onset (\u0026lt;\u0026thinsp;40 years of age) biliary tract cancers are on the rise in parts of Asia and may be associated with genetic mutations and environmental exposures(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). SDI differences are also reflected in the burden of risk factor attribution. High BMI was responsible for 25% of liver cancer deaths in high SDI areas compared to 8% in low SDI areas; conversely, alcohol use was responsible for 31% of liver cancer deaths in low SDI areas, significantly higher than the 12% in high SDI areas(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The smoking-attributable burden of pancreatic cancer continues to rise in low and intermediate SDI regions at an annual rate of 1.7%, highlighting the consequences of the lack of tobacco control policies.\u003c/p\u003e\u003cp\u003eExisting studies emphasize that liver-related cancers show significant heterogeneous patterns in different age and gender populations. The persistently high incidence and mortality rates of hepatocellular carcinoma in middle-aged and elderly men in China and Korea may be closely related to hepatitis B virus (HBV) infection, alcohol abuse, and lifestyle factors(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In contrast, the higher burden of biliary tract cancer in middle-aged and elderly Japanese women may be related to genetic susceptibility and environmental exposure(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). However, quantitative studies of key drivers influencing temporal trends in the liver-related cancers are still lacking(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). However, the westernization of lifestyle and the rise of metabolic diseases (e.g., obesity, diabetes mellitus) during urbanization in China may push up the burden of non-viral liver in the future, complicating the comparison of trends between countries(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Similarly, there are significant shortcomings in the prediction of future disease burdens(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Particularly in Asian countries, such as China and Korea, where increasing population ageing is intertwined with the prevalence of metabolic syndrome(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).There is an urgent need to construct a dynamic, multifactorial participatory modeling framework to more accurately reflect the future evolutionary trajectory of cancers of the hepatobiliary system(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough previous studies have explored the epidemiology of hepatobiliary cancers (liver, pancreas, gallbladder, and biliary tract) in different countries, comparative analyses between countries with different SDI trajectories remain scarce. This study filled a major gap by (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) quantifying regional differences liver burden through age-standardized metrics; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) utilizing the Bayesian Age-Period-Cohort (BAPC) model to project and analyze predictions of future trends; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) evaluating the impact of temporal and epidemiological trends through a ratio of the mean annual percentage change. Focusing on the United States, the United Kingdom, China, Japan, and South Korea, we analyzed the incidence, prevalence, and incidence of liver, pancreatic, gallbladder, and biliary tract cancers for the period 1990 to 2021 using GBD 2021 data. ASRs ensured fairness in comparisons, while the mean annual percentage change ratio determined time trends, and the BAPC model projected future burden to 2050. By elucidating regional disparities and their determinants, this work aims to inform tailored public health strategies and address key gaps in the management of cancers of the hepatobiliary system in different socio-demographic populations, with a particular emphasis on how socio-developmental index drivers influence the dynamics of hepatobiliary cancers.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eOverall\u003c/h2\u003e\u003cp\u003eThis study utilized the Bayesian Age-Period-Cohort (BAPC) model to project and analyze the burden of three liver-related cancers\u0026mdash;liver cancer (LC), pancreatic cancer (PC), and gallbladder and biliary tract cancer (GC)\u0026mdash;across five countries (China, Japan, Republic of Korea, United Kingdom, and United States of America) for 2022 and 2025. Input data were sourced from the GBD database, national cancer registries, and population-based surveys, harmonized using standardized case definitions and demographic adjustments. ASRs per 100,000 population and absolute numerical estimates were computed for incidence, prevalence, deaths, and DALYs, stratified by sex (Both, Female, Male). Uncertainty intervals (95% UIs) were generated through 1,000 Monte Carlo simulations to quantify variability in projections.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eBurden Description\u003c/h3\u003e\n\u003cp\u003eThe burden assessment focused on 2022 baseline estimates and 2025 projections, quantifying LC, PC, and GC through incident cases, prevalent cases, deaths, and DALYs. Country-specific disparities were analyzed by comparing ASRs and absolute values, with stratification by sex to highlight male-female differences. For example, China\u0026rsquo;s high absolute burden was contextualized against its large population size, while the United States\u0026rsquo; elevated DALYs were linked to demographic aging. Metrics were standardized using the World Health Organization (WHO) global population structure to enable cross-country comparisons.\u003c/p\u003e\n\u003ch3\u003eTrend Analysis\u003c/h3\u003e\n\u003cp\u003eTemporal trends were evaluated using Average Annual Percentage Changes (AAPCs) derived from historical data (2010\u0026ndash;2022) to contextualize future projections. The BAPC model incorporated age, period, and cohort effects to disentangle underlying drivers of trends, such as aging populations or shifts in risk factors. AAPCs were calculated for ASRs of incidence, mortality, and DALYs, with sensitivity analyses testing model robustness to input data quality. For instance, Japan\u0026rsquo;s declining LC mortality (-2.89% AAPC) was linked to improved screening programs, while the United Kingdom\u0026rsquo;s rising LC incidence (+\u0026thinsp;4.31% AAPC) reflected increasing alcohol-related risks.\u003c/p\u003e\n\u003ch3\u003eProjection Based on Bayesian Age-Period-Cohort Model\u003c/h3\u003e\n\u003cp\u003eThe BAPC model projected cancer burden from 2022 to 2025, integrating demographic projections (e.g., population growth, aging) and historical trend trajectories. Model parameters included country-specific fertility, mortality, and migration rates from the United Nations Population Division. Sex-stratified projections were generated to capture disparities, such as higher LC incidence among males in China (3.52 ASR vs. 0.59 for females). Uncertainty intervals accounted for stochastic variation in demographic and epidemiological assumptions. For GC, the model highlighted diverging trajectories, with China\u0026rsquo;s rising incidence (+\u0026thinsp;1.12% AAPC) contrasting with Japan\u0026rsquo;s declines (-2.02% AAPC). Validation tests compared projected 2022 estimates against observed data to ensure model accuracy.\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eNo ethical approval was required as the study used aggregated, anonymized secondary data. All analyses adhered to GBD collaboration guidelines for transparency and reproducibility.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eBurden of Liver-Related Cancers Burden by Country and Sex\u003c/h2\u003e\u003cp\u003eFor GC, China reported the highest absolute burden, with 1,119 incident cases (95% UI: 689-1,456) and 28,214 DALYs (17,901\u0026thinsp;\u0026minus;\u0026thinsp;36,519) among both sexes. Males in China exhibited significantly higher incidence rates (0.27 per 100,000, 0.14\u0026ndash;0.37) and DALYs (6.73, 3.68\u0026ndash;9.07) compared to females (incidence rate: 0.12; DALYs: 3.18). The United States recorded 185 incident cases (175\u0026ndash;196) and 2,135 DALYs (2,037\u0026thinsp;\u0026minus;\u0026thinsp;2,238), while the United Kingdom showed the lowest mortality rate (0.03 per 100,000) and DALYs (373, 358\u0026ndash;388). Japan and the Republic of Korea reported moderate burdens, with Japan\u0026rsquo;s mortality rate at 0.07 (0.07\u0026ndash;0.07) and Korea\u0026rsquo;s DALYs at 967 (690-1,423) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBurden of liver-related cancers among five countries in 2021\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003elocation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003esex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eIncidence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003ePrevalence\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eDeaths\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u003cp\u003eDALYs\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003cp\u003e(95% UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eASR (95% UI, per 100,000)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003cp\u003e(95% UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eASR (95% UI, per 100,000)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003cp\u003e(95% UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eASR (95% UI, per 100,000)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003cp\u003e(95% UI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eASR (95% UI, per 100,000)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e\u003cp\u003eGallbladder and Biliary Tract Cancer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1119\u003c/p\u003e\u003cp\u003e(689\u0026ndash;1456)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003cp\u003e(0.12\u0026ndash;0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2519\u003c/p\u003e\u003cp\u003e(1525\u0026ndash;3284)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003cp\u003e(0.27\u0026ndash;0.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e501\u003c/p\u003e\u003cp\u003e(317\u0026ndash;647)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003cp\u003e(0.06\u0026ndash;0.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e28214\u003c/p\u003e\u003cp\u003e(17901\u0026ndash;36519)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e5.01\u003c/p\u003e\u003cp\u003e(3.19\u0026ndash;6.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e316\u003c/p\u003e\u003cp\u003e(193\u0026ndash;468)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003cp\u003e(0.07\u0026ndash;0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e684\u003c/p\u003e\u003cp\u003e(414\u0026ndash;1006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003cp\u003e(0.15\u0026ndash;0.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e149\u003c/p\u003e\u003cp\u003e(92\u0026ndash;221)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003cp\u003e(0.03\u0026ndash;0.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e8431\u003c/p\u003e\u003cp\u003e(5221\u0026ndash;12501)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3.18\u003c/p\u003e\u003cp\u003e(1.97\u0026ndash;4.72)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e803\u003c/p\u003e\u003cp\u003e(427\u0026ndash;1089)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003cp\u003e(0.14\u0026ndash;0.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1835\u003c/p\u003e\u003cp\u003e(971\u0026ndash;2501)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003cp\u003e(0.33\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e352\u003c/p\u003e\u003cp\u003e(192\u0026ndash;474)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003cp\u003e(0.06\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e19783\u003c/p\u003e\u003cp\u003e(10793\u0026ndash;26630)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e6.73\u003c/p\u003e\u003cp\u003e(3.68\u0026ndash;9.07)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003cp\u003e(49\u0026ndash;60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003cp\u003e(0.13\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e112\u003c/p\u003e\u003cp\u003e(100\u0026ndash;128)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003cp\u003e(0.26\u0026ndash;0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003cp\u003e(0.07\u0026ndash;0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1487\u003c/p\u003e\u003cp\u003e(1444\u0026ndash;1537)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3.98\u003c/p\u003e\u003cp\u003e(3.86\u0026ndash;4.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28 CR29 CR30 CR31\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003cp\u003e(0.13\u0026ndash;0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56\u003c/p\u003e\u003cp\u003e(48\u0026ndash;68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003cp\u003e(0.26\u0026ndash;0.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003cp\u003e(0.07\u0026ndash;0.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e754\u003c/p\u003e\u003cp\u003e(725\u0026ndash;785)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e4.12\u003c/p\u003e\u003cp\u003e(3.96\u0026ndash;4.29)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28 CR29 CR30\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003cp\u003e(0.12\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56\u003c/p\u003e\u003cp\u003e(47\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003cp\u003e(0.24\u0026ndash;0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003cp\u003e(0.07\u0026ndash;0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e733\u003c/p\u003e\u003cp\u003e(702\u0026ndash;767)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003cp\u003e(3.68\u0026ndash;4.03)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003cp\u003e(24\u0026ndash;52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003cp\u003e(0.13\u0026ndash;0.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e72\u003c/p\u003e\u003cp\u003e(50\u0026ndash;108)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003cp\u003e(0.26\u0026ndash;0.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003cp\u003e(0.06\u0026ndash;0.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e967\u003c/p\u003e\u003cp\u003e(690\u0026ndash;1423)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e5.12\u003c/p\u003e\u003cp\u003e(3.65\u0026ndash;7.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003cp\u003e(0.12\u0026ndash;0.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35\u003c/p\u003e\u003cp\u003e(22\u0026ndash;57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003cp\u003e(0.25\u0026ndash;0.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003cp\u003e(0.06\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e479\u003c/p\u003e\u003cp\u003e(310\u0026ndash;790)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e5.4\u003c/p\u003e\u003cp\u003e(3.5\u0026ndash;8.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003cp\u003e(0.1\u0026ndash;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37\u003c/p\u003e\u003cp\u003e(21\u0026ndash;62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003cp\u003e(0.2\u0026ndash;0.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003cp\u003e(0.05\u0026ndash;0.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e488\u003c/p\u003e\u003cp\u003e(284\u0026ndash;795)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e4.86\u003c/p\u003e\u003cp\u003e(2.82\u0026ndash;7.93)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003cp\u003e(0.13\u0026ndash;0.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e107\u003c/p\u003e\u003cp\u003e(101\u0026ndash;112)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.43\u003c/p\u003e\u003cp\u003e(0.41\u0026ndash;0.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e373\u003c/p\u003e\u003cp\u003e(358\u0026ndash;388)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.52\u003c/p\u003e\u003cp\u003e(1.46\u0026ndash;1.58)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003cp\u003e(0.11\u0026ndash;0.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e45\u003c/p\u003e\u003cp\u003e(41\u0026ndash;49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003cp\u003e(0.33\u0026ndash;0.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e202\u003c/p\u003e\u003cp\u003e(192\u0026ndash;212)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003cp\u003e(1.53\u0026ndash;1.69)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003cp\u003e(0.14\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61\u003c/p\u003e\u003cp\u003e(57\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003cp\u003e(0.48\u0026ndash;0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003cp\u003e(0.02\u0026ndash;0.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e172\u003c/p\u003e\u003cp\u003e(162\u0026ndash;181)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003cp\u003e(1.35\u0026ndash;1.51)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e185\u003c/p\u003e\u003cp\u003e(175\u0026ndash;196)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.15\u003c/p\u003e\u003cp\u003e(0.15\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e585\u003c/p\u003e\u003cp\u003e(553\u0026ndash;619)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003cp\u003e(0.46\u0026ndash;0.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37\u003c/p\u003e\u003cp\u003e(36\u0026ndash;39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2135\u003c/p\u003e\u003cp\u003e(2037\u0026ndash;2238)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003cp\u003e(1.71\u0026ndash;1.88)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87\u003c/p\u003e\u003cp\u003e(80\u0026ndash;94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003cp\u003e(0.13\u0026ndash;0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e263\u003c/p\u003e\u003cp\u003e(242\u0026ndash;286)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003cp\u003e(0.4\u0026ndash;0.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(0.03\u0026ndash;0.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1137\u003c/p\u003e\u003cp\u003e(1073\u0026ndash;1208)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003cp\u003e(1.8\u0026ndash;2.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98\u003c/p\u003e\u003cp\u003e(92\u0026ndash;105)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003cp\u003e(0.15\u0026ndash;0.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e322\u003c/p\u003e\u003cp\u003e(300\u0026ndash;344)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003cp\u003e(0.5\u0026ndash;0.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e17\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(0.03\u0026ndash;0.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e998\u003c/p\u003e\u003cp\u003e(947\u0026ndash;1050)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e1.68\u003c/p\u003e\u003cp\u003e(1.59\u0026ndash;1.76)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiver Cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11860\u003c/p\u003e\u003cp\u003e(9150\u0026ndash;15390)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003cp\u003e(1.62\u0026ndash;2.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23940\u003c/p\u003e\u003cp\u003e(18566\u0026ndash;30989)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.26\u003c/p\u003e\u003cp\u003e(3.3\u0026ndash;5.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8653\u003c/p\u003e\u003cp\u003e(6666\u0026ndash;11215)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.54\u003c/p\u003e\u003cp\u003e(1.19\u0026ndash;1.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e488461\u003c/p\u003e\u003cp\u003e(376620\u0026ndash;632830)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e87.71\u003c/p\u003e\u003cp\u003e(67.62-113.54)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1540\u003c/p\u003e\u003cp\u003e(1121\u0026ndash;2084)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003cp\u003e(0.43\u0026ndash;0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3354\u003c/p\u003e\u003cp\u003e(2440\u0026ndash;4530)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003cp\u003e(0.93\u0026ndash;1.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1092\u003c/p\u003e\u003cp\u003e(795\u0026ndash;1486)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003cp\u003e(0.31\u0026ndash;0.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e62668\u003c/p\u003e\u003cp\u003e(45600\u0026ndash;85179)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e24.47\u003c/p\u003e\u003cp\u003e(17.81\u0026ndash;33.14)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10320\u003c/p\u003e\u003cp\u003e(7753\u0026ndash;13777)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.52\u003c/p\u003e\u003cp\u003e(2.64\u0026ndash;4.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20586\u003c/p\u003e\u003cp\u003e(15530\u0026ndash;27457)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7.04\u003c/p\u003e\u003cp\u003e(5.3\u0026ndash;9.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7561\u003c/p\u003e\u003cp\u003e(5670\u0026ndash;10102)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.59\u003c/p\u003e\u003cp\u003e(1.94\u0026ndash;3.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e425793\u003c/p\u003e\u003cp\u003e(319437\u0026ndash;569130)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e146.73\u003c/p\u003e\u003cp\u003e(109.93\u0026ndash;196.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120\u003c/p\u003e\u003cp\u003e(107\u0026ndash;134)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003cp\u003e(0.29\u0026ndash;0.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e344\u003c/p\u003e\u003cp\u003e(297\u0026ndash;395)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003cp\u003e(0.81\u0026ndash;1.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e60\u003c/p\u003e\u003cp\u003e(58\u0026ndash;62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003cp\u003e(0.16\u0026ndash;0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3418\u003c/p\u003e\u003cp\u003e(3291\u0026ndash;3550)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e9.42\u003c/p\u003e\u003cp\u003e(9.06\u0026ndash;9.78)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003cp\u003e(33\u0026ndash;46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003cp\u003e(0.18\u0026ndash;0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e123\u003c/p\u003e\u003cp\u003e(97\u0026ndash;152)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003cp\u003e(0.55\u0026ndash;0.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e18\u003c/p\u003e\u003cp\u003e(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003cp\u003e(0.09\u0026ndash;0.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1020\u003c/p\u003e\u003cp\u003e(972\u0026ndash;1068)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e5.83\u003c/p\u003e\u003cp\u003e(5.55\u0026ndash;6.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003cp\u003e(70\u0026ndash;92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003cp\u003e(0.37\u0026ndash;0.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e221\u003c/p\u003e\u003cp\u003e(187\u0026ndash;259)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003cp\u003e(0.99\u0026ndash;1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42\u003c/p\u003e\u003cp\u003e(40\u0026ndash;44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003cp\u003e(0.21\u0026ndash;0.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2398\u003c/p\u003e\u003cp\u003e(2282\u0026ndash;2523)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e12.87\u003c/p\u003e\u003cp\u003e(12.25\u0026ndash;13.55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e270\u003c/p\u003e\u003cp\u003e(182\u0026ndash;393)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.42\u003c/p\u003e\u003cp\u003e(0.95\u0026ndash;2.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e709\u003c/p\u003e\u003cp\u003e(478\u0026ndash;1030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.74\u003c/p\u003e\u003cp\u003e(2.52\u0026ndash;5.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e141\u003c/p\u003e\u003cp\u003e(96\u0026ndash;206)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003cp\u003e(0.5\u0026ndash;1.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7825\u003c/p\u003e\u003cp\u003e(5329\u0026ndash;11438)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e41.51\u003c/p\u003e\u003cp\u003e(28.28\u0026ndash;60.58)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69\u003c/p\u003e\u003cp\u003e(42\u0026ndash;108)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003cp\u003e(0.48\u0026ndash;1.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e202\u003c/p\u003e\u003cp\u003e(117\u0026ndash;321)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.32\u003c/p\u003e\u003cp\u003e(1.34\u0026ndash;3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e32\u003c/p\u003e\u003cp\u003e(20\u0026ndash;48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003cp\u003e(0.23\u0026ndash;0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1818\u003c/p\u003e\u003cp\u003e(1154\u0026ndash;2727)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e21.16\u003c/p\u003e\u003cp\u003e(13.35\u0026ndash;31.88)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e201\u003c/p\u003e\u003cp\u003e(120\u0026ndash;320)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.97\u003c/p\u003e\u003cp\u003e(1.18\u0026ndash;3.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e507\u003c/p\u003e\u003cp\u003e(301\u0026ndash;823)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003cp\u003e(2.96\u0026ndash;8.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e109\u003c/p\u003e\u003cp\u003e(67\u0026ndash;172)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003cp\u003e(0.66\u0026ndash;1.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6007\u003c/p\u003e\u003cp\u003e(3694\u0026ndash;9512)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e59.65\u003c/p\u003e\u003cp\u003e(36.6-94.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e161\u003c/p\u003e\u003cp\u003e(153\u0026ndash;170)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003cp\u003e(0.64\u0026ndash;0.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e450\u003c/p\u003e\u003cp\u003e(424\u0026ndash;476)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.9\u003c/p\u003e\u003cp\u003e(1.79\u0026ndash;2.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e88\u003c/p\u003e\u003cp\u003e(84\u0026ndash;92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003cp\u003e(0.36\u0026ndash;0.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5115\u003c/p\u003e\u003cp\u003e(4908\u0026ndash;5340)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e21.83\u003c/p\u003e\u003cp\u003e(20.96\u0026ndash;22.78)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56\u003c/p\u003e\u003cp\u003e(53\u0026ndash;60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003cp\u003e(0.44\u0026ndash;0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e142\u003c/p\u003e\u003cp\u003e(132\u0026ndash;152)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003cp\u003e(1.09\u0026ndash;1.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35\u003c/p\u003e\u003cp\u003e(33\u0026ndash;37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003cp\u003e(0.28\u0026ndash;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2034\u003c/p\u003e\u003cp\u003e(1950\u0026ndash;2126)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e17.18\u003c/p\u003e\u003cp\u003e(16.47\u0026ndash;17.96)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e105\u003c/p\u003e\u003cp\u003e(98\u0026ndash;113)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003cp\u003e(0.84\u0026ndash;0.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e308\u003c/p\u003e\u003cp\u003e(286\u0026ndash;334)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.65\u003c/p\u003e\u003cp\u003e(2.46\u0026ndash;2.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e53\u003c/p\u003e\u003cp\u003e(50\u0026ndash;57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003cp\u003e(0.43\u0026ndash;0.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3081\u003c/p\u003e\u003cp\u003e(2913\u0026ndash;3284)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e26.7\u003c/p\u003e\u003cp\u003e(25.25\u0026ndash;28.44)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e561\u003c/p\u003e\u003cp\u003e(531\u0026ndash;592)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003cp\u003e(0.45\u0026ndash;0.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1407\u003c/p\u003e\u003cp\u003e(1327\u0026ndash;1488)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003cp\u003e(1.14\u0026ndash;1.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e290\u003c/p\u003e\u003cp\u003e(276\u0026ndash;304)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003cp\u003e(0.24\u0026ndash;0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e17016\u003c/p\u003e\u003cp\u003e(16181\u0026ndash;17855)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e14.68\u003c/p\u003e\u003cp\u003e(13.96\u0026ndash;15.41)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191\u003c/p\u003e\u003cp\u003e(178\u0026ndash;204)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003cp\u003e(0.31\u0026ndash;0.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e455\u003c/p\u003e\u003cp\u003e(423\u0026ndash;487)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003cp\u003e(0.73\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e107\u003c/p\u003e\u003cp\u003e(101\u0026ndash;113)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003cp\u003e(0.18\u0026ndash;0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6312\u003c/p\u003e\u003cp\u003e(5973\u0026ndash;6664)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e11\u003c/p\u003e\u003cp\u003e(10.4-11.61)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e370\u003c/p\u003e\u003cp\u003e(345\u0026ndash;395)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003cp\u003e(0.59\u0026ndash;0.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e952\u003c/p\u003e\u003cp\u003e(885\u0026ndash;1021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003cp\u003e(1.51\u0026ndash;1.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e183\u003c/p\u003e\u003cp\u003e(172\u0026ndash;194)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003cp\u003e(0.29\u0026ndash;0.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e10704\u003c/p\u003e\u003cp\u003e(10061\u0026ndash;11394)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e18.35\u003c/p\u003e\u003cp\u003e(17.25\u0026ndash;19.54)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePancreatic Cancer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2821\u003c/p\u003e\u003cp\u003e(2231\u0026ndash;3466)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003cp\u003e(0.39\u0026ndash;0.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5278\u003c/p\u003e\u003cp\u003e(4179\u0026ndash;6457)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003cp\u003e(0.73\u0026ndash;1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2349\u003c/p\u003e\u003cp\u003e(1855\u0026ndash;2889)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003cp\u003e(0.33\u0026ndash;0.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e131458\u003c/p\u003e\u003cp\u003e(103859\u0026ndash;161638)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e23.39\u003c/p\u003e\u003cp\u003e(18.47\u0026ndash;28.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e601\u003c/p\u003e\u003cp\u003e(433\u0026ndash;807)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003cp\u003e(0.16\u0026ndash;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1183\u003c/p\u003e\u003cp\u003e(855\u0026ndash;1590)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003cp\u003e(0.32\u0026ndash;0.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e491\u003c/p\u003e\u003cp\u003e(351\u0026ndash;659)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003cp\u003e(0.13\u0026ndash;0.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e27718\u003c/p\u003e\u003cp\u003e(19839\u0026ndash;37237)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e10.5\u003c/p\u003e\u003cp\u003e(7.52\u0026ndash;14.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2220\u003c/p\u003e\u003cp\u003e(1726\u0026ndash;2810)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003cp\u003e(0.58\u0026ndash;0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4095\u003c/p\u003e\u003cp\u003e(3181\u0026ndash;5173)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.38\u003c/p\u003e\u003cp\u003e(1.07\u0026ndash;1.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1859\u003c/p\u003e\u003cp\u003e(1442\u0026ndash;2337)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003cp\u003e(0.49\u0026ndash;0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e103741\u003c/p\u003e\u003cp\u003e(80483\u0026ndash;130406)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e35.47\u003c/p\u003e\u003cp\u003e(27.5-44.64)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003cp\u003e(111\u0026ndash;119)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003cp\u003e(0.29\u0026ndash;0.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e280\u003c/p\u003e\u003cp\u003e(259\u0026ndash;303)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003cp\u003e(0.69\u0026ndash;0.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e87\u003c/p\u003e\u003cp\u003e(85\u0026ndash;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003cp\u003e(0.22\u0026ndash;0.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4877\u003c/p\u003e\u003cp\u003e(4732\u0026ndash;5029)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e13.06\u003c/p\u003e\u003cp\u003e(12.66\u0026ndash;13.47)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52\u003c/p\u003e\u003cp\u003e(49\u0026ndash;55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003cp\u003e(0.27\u0026ndash;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e134\u003c/p\u003e\u003cp\u003e(118\u0026ndash;153)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003cp\u003e(0.65\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e39\u003c/p\u003e\u003cp\u003e(37\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003cp\u003e(0.2\u0026ndash;0.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2172\u003c/p\u003e\u003cp\u003e(2088\u0026ndash;2255)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e11.98\u003c/p\u003e\u003cp\u003e(11.51\u0026ndash;12.44)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003cp\u003e(60\u0026ndash;66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003cp\u003e(0.31\u0026ndash;0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e146\u003c/p\u003e\u003cp\u003e(132\u0026ndash;161)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003cp\u003e(0.69\u0026ndash;0.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e49\u003c/p\u003e\u003cp\u003e(47\u0026ndash;51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003cp\u003e(0.24\u0026ndash;0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2704\u003c/p\u003e\u003cp\u003e(2596\u0026ndash;2820)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e14.1\u003c/p\u003e\u003cp\u003e(13.52\u0026ndash;14.72)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49\u003c/p\u003e\u003cp\u003e(38\u0026ndash;65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.26\u003c/p\u003e\u003cp\u003e(0.2\u0026ndash;0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e113\u003c/p\u003e\u003cp\u003e(85\u0026ndash;147)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003cp\u003e(0.45\u0026ndash;0.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e38\u003c/p\u003e\u003cp\u003e(29\u0026ndash;50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003cp\u003e(0.15\u0026ndash;0.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2116\u003c/p\u003e\u003cp\u003e(1608\u0026ndash;2771)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e11.24\u003c/p\u003e\u003cp\u003e(8.5-14.77)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003cp\u003e(0.17\u0026ndash;0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51\u003c/p\u003e\u003cp\u003e(35\u0026ndash;72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003cp\u003e(0.4\u0026ndash;0.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003cp\u003e(0.12\u0026ndash;0.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e880\u003c/p\u003e\u003cp\u003e(619\u0026ndash;1249)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e10.04\u003c/p\u003e\u003cp\u003e(7.03\u0026ndash;14.27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003cp\u003e(19\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003cp\u003e(0.19\u0026ndash;0.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62\u003c/p\u003e\u003cp\u003e(42\u0026ndash;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.62\u003c/p\u003e\u003cp\u003e(0.41\u0026ndash;0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003cp\u003e(0.15\u0026ndash;0.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1236\u003c/p\u003e\u003cp\u003e(829\u0026ndash;1774)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e12.3\u003c/p\u003e\u003cp\u003e(8.23\u0026ndash;17.74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73\u003c/p\u003e\u003cp\u003e(70\u0026ndash;75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003cp\u003e(0.29\u0026ndash;0.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e176\u003c/p\u003e\u003cp\u003e(168\u0026ndash;182)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003cp\u003e(0.69\u0026ndash;0.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56\u003c/p\u003e\u003cp\u003e(53\u0026ndash;57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003cp\u003e(0.22\u0026ndash;0.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e3108\u003c/p\u003e\u003cp\u003e(2989\u0026ndash;3207)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e12.76\u003c/p\u003e\u003cp\u003e(12.28\u0026ndash;13.17)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003cp\u003e(0.23\u0026ndash;0.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e71\u003c/p\u003e\u003cp\u003e(67\u0026ndash;75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003cp\u003e(0.54\u0026ndash;0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003cp\u003e(0.17\u0026ndash;0.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1252\u003c/p\u003e\u003cp\u003e(1200\u0026ndash;1304)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e10.1\u003c/p\u003e\u003cp\u003e(9.68\u0026ndash;10.53)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003cp\u003e(41\u0026ndash;45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003cp\u003e(0.34\u0026ndash;0.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e105\u003c/p\u003e\u003cp\u003e(99\u0026ndash;110)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003cp\u003e(0.82\u0026ndash;0.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e33\u003c/p\u003e\u003cp\u003e(\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003cp\u003e(0.26\u0026ndash;0.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1856\u003c/p\u003e\u003cp\u003e(1760\u0026ndash;1937)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e15.56\u003c/p\u003e\u003cp\u003e(14.76\u0026ndash;16.25)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e398\u003c/p\u003e\u003cp\u003e(381\u0026ndash;414)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003cp\u003e(0.32\u0026ndash;0.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1081\u003c/p\u003e\u003cp\u003e(1030\u0026ndash;1132)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003cp\u003e(0.86\u0026ndash;0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e271\u003c/p\u003e\u003cp\u003e(260\u0026ndash;282)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003cp\u003e(0.22\u0026ndash;0.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e15190\u003c/p\u003e\u003cp\u003e(14560\u0026ndash;15811)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e12.74\u003c/p\u003e\u003cp\u003e(12.21\u0026ndash;13.27)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e159\u003c/p\u003e\u003cp\u003e(150\u0026ndash;169)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003cp\u003e(0.25\u0026ndash;0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e501\u003c/p\u003e\u003cp\u003e(466\u0026ndash;538)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003cp\u003e(0.78\u0026ndash;0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e105\u003c/p\u003e\u003cp\u003e(99\u0026ndash;112)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003cp\u003e(0.17\u0026ndash;0.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e5917\u003c/p\u003e\u003cp\u003e(5581\u0026ndash;6283)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e9.95\u003c/p\u003e\u003cp\u003e(9.38\u0026ndash;10.57)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e239\u003c/p\u003e\u003cp\u003e(227\u0026ndash;250)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003cp\u003e(0.38\u0026ndash;0.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e581\u003c/p\u003e\u003cp\u003e(548\u0026ndash;611)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003cp\u003e(0.92\u0026ndash;1.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e166\u003c/p\u003e\u003cp\u003e(158\u0026ndash;174)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003cp\u003e(0.26\u0026ndash;0.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9272\u003c/p\u003e\u003cp\u003e(8807\u0026ndash;9723)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e15.55\u003c/p\u003e\u003cp\u003e(14.77\u0026ndash;16.31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eLC burden was overwhelmingly concentrated in China, with 11,860 incident cases (9,150\u0026thinsp;\u0026minus;\u0026thinsp;15,390), 8,653 deaths (6,666\u0026thinsp;\u0026minus;\u0026thinsp;11,215), and 488,461 DALYs (376,620\u0026ndash;632,830) among both sexes. Male-specific disparities were stark: males in China had an incidence rate of 3.52 (2.64\u0026ndash;4.7) and DALYs of 146.73 (109.93\u0026ndash;196.2), nearly five times higher than females. The United States reported 561 incident cases (531\u0026ndash;592) and 17,016 DALYs (16,181\u0026thinsp;\u0026minus;\u0026thinsp;17,855), while the United Kingdom observed lower mortality rates (0.37 per 100,000) but substantial DALYs (5,115, 4,908-5,340). Japan and Korea showed intermediate burdens, with Korea\u0026rsquo;s DALYs (7,825, 5,329\u0026thinsp;\u0026minus;\u0026thinsp;11,438) exceeding Japan\u0026rsquo;s (3,418, 3,291-3,550) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003ePC burden varied widely across countries. China dominated in absolute numbers, with 2,821 incident cases (2,231-3,466), 2,349 deaths (1,855-2,889), and 131,458 DALYs (103,859\u0026thinsp;\u0026minus;\u0026thinsp;161,638) among both sexes. Males in China faced higher rates (incidence: 0.75; DALYs: 35.47) than females (incidence: 0.22; DALYs: 10.5). The United States reported 398 incident cases (381\u0026ndash;414) and 15,190 DALYs (14,560\u0026thinsp;\u0026minus;\u0026thinsp;15,811), with males showing elevated mortality rates (0.28 per 100,000) compared to females (0.18). Japan and the United Kingdom exhibited lower burdens, with Japan\u0026rsquo;s DALYs at 4,877 (4,732-5,029) and the U.K.\u0026rsquo;s mortality rate at 0.23 (0.22\u0026ndash;0.23). The Republic of Korea reported the lowest PC incidence (49 cases, 38\u0026ndash;65) but notable sex disparities in DALYs (males: 12.3; females: 10.04). These findings underscore significant geographical and sex-based variations in the burden of liver-related cancers \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTrends in Liver-Related Cancers Burden by Country and Sex\u003c/h3\u003e\n\u003cp\u003eFor GC, China exhibited rising incidence trends among both sexes (AAPC: 1.12% for Both, 1.88% for males), while Japan and the Republic of Korea reported declining incidence (Japan: -2.02% for Both; Korea: -1.58% for Both). Mortality rates decreased modestly across most countries, with China showing a slight decline (-0.87% for Both) and the United Kingdom recording the lowest mortality trends (-0.23% for Both). DALYs demonstrated mixed patterns, with the United States observing a marginal increase (1.15% for Both) compared to declines in Japan (-2.53% for Both) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eTrends of liver-related cancers among five countries from 1990 to 2021\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003elocation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003esex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003einaapc_gc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003epraapc_gc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003edeaapc_gc\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003edaaapc_gc\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eGallbladder and Biliary Tract Cancer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003cp\u003e(1.01 to 1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.87\u003c/p\u003e\u003cp\u003e(2.78 to 2.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.87\u003c/p\u003e\u003cp\u003e(-0.98 to -0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.84\u003c/p\u003e\u003cp\u003e(-0.95 to -0.74)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.25\u003c/p\u003e\u003cp\u003e(-0.38 to -0.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003cp\u003e(1.42 to 1.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.05\u003c/p\u003e\u003cp\u003e(-2.15 to -1.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.01\u003c/p\u003e\u003cp\u003e(-2.1 to -1.88)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003cp\u003e(1.73 to 2.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.7\u003c/p\u003e\u003cp\u003e(3.57 to 3.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.19\u003c/p\u003e\u003cp\u003e(-0.3 to -0.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.15\u003c/p\u003e\u003cp\u003e(-0.28 to -0.04)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.02\u003c/p\u003e\u003cp\u003e(-2.36 to -1.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.52\u003c/p\u003e\u003cp\u003e(-1.81 to -1.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.53\u003c/p\u003e\u003cp\u003e(-2.7 to -2.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.5\u003c/p\u003e\u003cp\u003e(-2.66 to -2.34)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.07\u003c/p\u003e\u003cp\u003e(-2.43 to -1.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.48\u003c/p\u003e\u003cp\u003e(-1.81 to -1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.43\u003c/p\u003e\u003cp\u003e(-2.85 to -2.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.4\u003c/p\u003e\u003cp\u003e(-2.79 to -2.11)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2\u003c/p\u003e\u003cp\u003e(-2.33 to -1.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.52\u003c/p\u003e\u003cp\u003e(-1.85 to -1.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.36\u003c/p\u003e\u003cp\u003e(-2.58 to -2.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.32\u003c/p\u003e\u003cp\u003e(-2.54 to -2.14)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.58\u003c/p\u003e\u003cp\u003e(-2.03 to -1.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.15\u003c/p\u003e\u003cp\u003e(-0.35 to 0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.1\u003c/p\u003e\u003cp\u003e(-3.29 to -2.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.08\u003c/p\u003e\u003cp\u003e(-3.27 to -2.86)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.15\u003c/p\u003e\u003cp\u003e(-1.41 to -0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003cp\u003e(0.05 to 0.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.79\u003c/p\u003e\u003cp\u003e(-3.02 to -2.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.8\u003c/p\u003e\u003cp\u003e(-3.07 to -2.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.71\u003c/p\u003e\u003cp\u003e(-1.89 to -1.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.37\u003c/p\u003e\u003cp\u003e(-0.52 to -0.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.37\u003c/p\u003e\u003cp\u003e(-3.52 to -3.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.35\u003c/p\u003e\u003cp\u003e(-3.5 to -3.21)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003cp\u003e(1.32 to 1.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.35\u003c/p\u003e\u003cp\u003e(2.01 to 2.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.23\u003c/p\u003e\u003cp\u003e(-0.57 to 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003cp\u003e(-0.43 to 0.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.84\u003c/p\u003e\u003cp\u003e(1.58 to 2.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.58\u003c/p\u003e\u003cp\u003e(2.35 to 2.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.14\u003c/p\u003e\u003cp\u003e(-0.41 to 0.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.13\u003c/p\u003e\u003cp\u003e(-0.38 to 0.04)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.58\u003c/p\u003e\u003cp\u003e(1.13 to 1.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.19\u003c/p\u003e\u003cp\u003e(1.78 to 2.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.14\u003c/p\u003e\u003cp\u003e(-0.68 to 0.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003cp\u003e(-0.63 to 0.33)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003cp\u003e(0.67 to 1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003cp\u003e(0.85 to 1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.47\u003c/p\u003e\u003cp\u003e(-0.85 to -0.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.43\u003c/p\u003e\u003cp\u003e(-0.81 to -0.18)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003cp\u003e(0.3 to 1.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003cp\u003e(0.87 to 1.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.33\u003c/p\u003e\u003cp\u003e(-0.69 to 0.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.3\u003c/p\u003e\u003cp\u003e(-0.65 to 0.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003cp\u003e(0.36 to 1.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003cp\u003e(0.71 to 1.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003cp\u003e(-0.28 to 0.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003cp\u003e(-0.21 to 0.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eLiver Cancer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.57\u003c/p\u003e\u003cp\u003e(-0.68 to -0.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.31\u003c/p\u003e\u003cp\u003e(-0.42 to -0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.16\u003c/p\u003e\u003cp\u003e(-1.36 to -0.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.17\u003c/p\u003e\u003cp\u003e(-1.37 to -0.96)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.71\u003c/p\u003e\u003cp\u003e(-1.97 to -1.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.26\u003c/p\u003e\u003cp\u003e(-1.51 to -1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.32\u003c/p\u003e\u003cp\u003e(-2.55 to -2.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.33\u003c/p\u003e\u003cp\u003e(-2.57 to -2.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.32\u003c/p\u003e\u003cp\u003e(-0.47 to -0.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003cp\u003e(-0.24 to -0.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.93\u003c/p\u003e\u003cp\u003e(-1.11 to -0.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.85\u003c/p\u003e\u003cp\u003e(-1.03 to -0.66)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.09\u003c/p\u003e\u003cp\u003e(-2.37 to -1.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.46\u003c/p\u003e\u003cp\u003e(-1.73 to -1.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.89\u003c/p\u003e\u003cp\u003e(-3.07 to -2.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.82\u003c/p\u003e\u003cp\u003e(-2.99 to -2.65)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.73\u003c/p\u003e\u003cp\u003e(-0.83 to -0.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.42\u003c/p\u003e\u003cp\u003e(-0.52 to -0.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.39\u003c/p\u003e\u003cp\u003e(-1.57 to -1.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.38\u003c/p\u003e\u003cp\u003e(-1.56 to -1.17)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.64\u003c/p\u003e\u003cp\u003e(-2.85 to -2.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.93\u003c/p\u003e\u003cp\u003e(-2.17 to -1.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.43\u003c/p\u003e\u003cp\u003e(-3.63 to -3.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.36\u003c/p\u003e\u003cp\u003e(-3.57 to -3.15)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.41\u003c/p\u003e\u003cp\u003e(-2.53 to -2.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.26\u003c/p\u003e\u003cp\u003e(-1.4 to -1.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.94\u003c/p\u003e\u003cp\u003e(-4.16 to -3.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.93\u003c/p\u003e\u003cp\u003e(-4.15 to -3.71)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.31\u003c/p\u003e\u003cp\u003e(-1.39 to -1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(-0.13 to 0.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-3.22\u003c/p\u003e\u003cp\u003e(-3.44 to -3.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.23\u003c/p\u003e\u003cp\u003e(-3.41 to -3.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.82\u003c/p\u003e\u003cp\u003e(-2.96 to -2.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.82\u003c/p\u003e\u003cp\u003e(-1.91 to -1.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-4.23\u003c/p\u003e\u003cp\u003e(-4.55 to -3.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-4.27\u003c/p\u003e\u003cp\u003e(-4.59 to -3.99)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.31\u003c/p\u003e\u003cp\u003e(4.22 to 4.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.97\u003c/p\u003e\u003cp\u003e(4.89 to 5.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.45\u003c/p\u003e\u003cp\u003e(3.2 to 3.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.43\u003c/p\u003e\u003cp\u003e(3.18 to 3.66)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003cp\u003e(3.71 to 4.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.34\u003c/p\u003e\u003cp\u003e(4.23 to 4.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.24\u003c/p\u003e\u003cp\u003e(3.04 to 3.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.21\u003c/p\u003e\u003cp\u003e(3 to 3.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.58\u003c/p\u003e\u003cp\u003e(4.52 to 4.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.32\u003c/p\u003e\u003cp\u003e(5.23 to 5.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003cp\u003e(3.24 to 3.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.48\u003c/p\u003e\u003cp\u003e(3.23 to 3.73)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003cp\u003e(1.76 to 1.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.33\u003c/p\u003e\u003cp\u003e(2.22 to 2.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003cp\u003e(0.93 to 1.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003cp\u003e(0.95 to 1.34)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003cp\u003e(1.83 to 1.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.29\u003c/p\u003e\u003cp\u003e(2.24 to 2.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003cp\u003e(1.07 to 1.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003cp\u003e(1.02 to 1.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.77\u003c/p\u003e\u003cp\u003e(1.67 to 1.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.32\u003c/p\u003e\u003cp\u003e(2.2 to 2.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003cp\u003e(0.79 to 1.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003cp\u003e(0.91 to 1.43)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePancreatic Cancer\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003cp\u003e(0.33 to 0.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003cp\u003e(0.6 to 0.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003cp\u003e(0.12 to 0.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003cp\u003e(0.12 to 0.34)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.72\u003c/p\u003e\u003cp\u003e(-0.82 to -0.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.35\u003c/p\u003e\u003cp\u003e(-0.48 to -0.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1\u003c/p\u003e\u003cp\u003e(-1.1 to -0.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-1.02\u003c/p\u003e\u003cp\u003e(-1.12 to -0.92)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003cp\u003e(0.65 to 1.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003cp\u003e(0.95 to 1.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003cp\u003e(0.52 to 0.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003cp\u003e(0.51 to 0.84)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003cp\u003e(-0.28 to 0.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003cp\u003e(-0.02 to 0.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.26\u003c/p\u003e\u003cp\u003e(-0.49 to 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.21\u003c/p\u003e\u003cp\u003e(-0.44 to 0.04)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003cp\u003e(0.04 to 0.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003cp\u003e(0.54 to 1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003cp\u003e(-0.17 to 0.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003cp\u003e(-0.12 to 0.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.52\u003c/p\u003e\u003cp\u003e(-0.74 to -0.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.43\u003c/p\u003e\u003cp\u003e(-0.73 to -0.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.76\u003c/p\u003e\u003cp\u003e(-0.96 to -0.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.74\u003c/p\u003e\u003cp\u003e(-0.96 to -0.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.72\u003c/p\u003e\u003cp\u003e(-1.88 to -1.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.8\u003c/p\u003e\u003cp\u003e(-0.94 to -0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.12\u003c/p\u003e\u003cp\u003e(-2.3 to -1.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.16\u003c/p\u003e\u003cp\u003e(-2.32 to -1.97)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.32\u003c/p\u003e\u003cp\u003e(-0.47 to -0.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.69\u003c/p\u003e\u003cp\u003e(0.47 to 0.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.83\u003c/p\u003e\u003cp\u003e(-1 to -0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.86\u003c/p\u003e\u003cp\u003e(-1.03 to -0.72)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRepublic of Korea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.42\u003c/p\u003e\u003cp\u003e(-2.56 to -2.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.65\u003c/p\u003e\u003cp\u003e(-1.83 to -1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.76\u003c/p\u003e\u003cp\u003e(-2.91 to -2.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.76\u003c/p\u003e\u003cp\u003e(-2.91 to -2.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003cp\u003e(0.07 to 0.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003cp\u003e(0.55 to 1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003cp\u003e(-0.13 to 0.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003cp\u003e(-0.15 to 0.26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003cp\u003e(-0.03 to 0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003cp\u003e(0.35 to 0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003cp\u003e(-0.21 to 0.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003cp\u003e(-0.25 to 0.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited Kingdom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003cp\u003e(0.17 to 0.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003cp\u003e(0.59 to 1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003cp\u003e(-0.08 to 0.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003cp\u003e(-0.09 to 0.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBoth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.16\u003c/p\u003e\u003cp\u003e(0 to 0.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003cp\u003e(0.37 to 0.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.12\u003c/p\u003e\u003cp\u003e(-0.27 to -0.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.11\u003c/p\u003e\u003cp\u003e(-0.25 to 0.01)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003cp\u003e(-0.15 to 0.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003cp\u003e(0.75 to 1.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003cp\u003e(-0.19 to 0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003cp\u003e(-0.18 to 0.19)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003cp\u003e(-0.2 to 0.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003cp\u003e(0.37 to 0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.25\u003c/p\u003e\u003cp\u003e(-0.48 to -0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.22\u003c/p\u003e\u003cp\u003e(-0.47 to -0.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eLC burden varied significantly by region. China reported moderate declines in incidence (-0.57% for Both) and mortality (-1.16% for Both), while the United Kingdom experienced sharp increases in incidence (4.31% for Both) and DALYs (3.45% for Both). Japan and Korea showed consistent reductions across metrics, particularly in mortality (Japan: -2.89% for Both; Korea: -3.94% for Both). The United States displayed stable incidence trends (1.83% for Both) but rising DALYs (1.15% for Both). Sex-specific disparities were notable, with female populations in China and Japan experiencing steeper mortality declines than males \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eFor PC, China demonstrated rising incidence (0.44% for Both) and mortality (0.22% for Both), contrasting with declines in Korea (-1.72% for Both) and Japan (-0.08% for Both). The United Kingdom and United States reported mixed trends, with the U.K. showing modest incidence growth (0.29% for Both) and the U.S. stabilizing mortality (-0.12% for Both). Female populations in China and Korea faced sharper mortality reductions (-1.02% and \u0026minus;\u0026thinsp;0.86%, respectively) compared to males. Overall, DALYs remained stable or declined slightly in high-income nations, while China\u0026rsquo;s DALYs increased marginally (0.22% for Both). These trends highlight heterogeneous patterns in liver-related cancer burdens, influenced by regional and sex-specific factors \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eProjected Burden of Three Liver-Related Cancers in Five Countries (2022\u0026ndash;2025)\u003c/h2\u003e\u003cp\u003eThis study employs the BAPC model to project the future burden of three liver-related cancers\u0026mdash;LC, PC, and GC\u0026mdash;across five countries (China, Japan, Republic of Korea, United Kingdom, and United States of America) for 2022 and 2025, integrating both ASR (ASRs) and absolute numerical estimates for incidence, prevalence, deaths, and DALY (DALYs), along with their uncertainty intervals \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFor LC, China dominates in both ASRs and absolute burden. The age-standardized incidence rate rises from 2.23 per 100,000 (95% UI: 1.87\u0026ndash;2.59) in 2022 to 2.28 (1.49\u0026ndash;3.07) in 2025, while absolute incident cases increase from 12,999.62 (10,923.09-15,076.15) to 13,417.95 (8,814.41-18,021.50) over the same period. China\u0026rsquo;s DALYs remain disproportionately high, with ASRs at 94.39 (75.37-113.41) in 2022 and 96.12 (58.30-133.94) in 2025, translating to absolute DALYs of 544,622.75 (435,038.57\u0026ndash;654,206.93) and 555,296.56 (337,127.53\u0026ndash;773,465.60), respectively. The United States, though exhibiting lower ASRs, reports substantial absolute DALYs (18,493.22 to 18,618.73) due to its larger population. Japan and the Republic of Korea show moderate ASRs but notable burdens in prevalence (Japan: 300.37 to 265.36; Korea: 638.69 to 608.17), while the United Kingdom faces gradual increases in deaths (93.92 to 103.23) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003ePC projections highlight rising trends in China, with ASR incidence increasing from 0.52 (0.45\u0026ndash;0.59) to 0.55 (0.44\u0026ndash;0.65) and absolute cases surging from 3,046.60 (2,637.31-3,455.89) to 3,278.79 (2,673.09-3,884.48). Corresponding DALYs escalate from 26.02 to 27.82 (ASR) and 151,549.86 to 164,465.17 (absolute). The United States reports the highest absolute PC deaths (294.35 to 302.74), despite stable ASR mortality (~\u0026thinsp;0.24), while Japan and Korea exhibit uncertain mortality trends (Japan: 0.23\u0026ndash;0.24 ASR; 81.02\u0026ndash;79.73 absolute deaths). The United Kingdom\u0026rsquo;s DALYs decline marginally (2,899.27 to 2,561.58) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eGC projections reveal disparities: China\u0026rsquo;s ASR mortality remains stable (~\u0026thinsp;0.11) but absolute deaths grow from 519.04 (386.97\u0026ndash;651.10) to 522.85 (365.83-679.87), with DALYs persistently elevated (ASR: 6.50\u0026ndash;6.45; absolute: 29,332.95-29,138.40). The United States reports higher absolute mortality (41.81 to 45.31) compared to the United Kingdom\u0026rsquo;s low ASR (0.03) and absolute deaths (6.26 to 6.48). Japan and Korea face uncertainty in ASR deaths (Japan: 0.09 in 2025, UI: 0.01\u0026ndash;0.19; Korea: 0.09\u0026ndash;0.09) and absolute trends (Japan: 25.09\u0026ndash;23.16; Korea: 14.00-12.29) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDifferences in the burden and drivers of GC, with China leading the world in the number of morbidity and mortality cases of GC(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). as the country with the largest burden. This is associated with China's large population base and geographic exposure differences. Gender differences are evident, with the age-standardized incidence rate (ASIR) for men in China being 1.8 times higher than that for women(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This was associated with a higher prevalence of smoking (attributable risk 24.1%) and occupational exposure (e.g., chemical industry) in men(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In a regional trend analysis of gallbladder and biliary tract cancers (GC), China's ASIR continued to rise (0.8% annual increase), but age-standardized mortality rate (ASMR) declined due to the prevalence of surgery(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Japan and Korea are both on a downward trend(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Attributed to early screening (\u0026gt;\u0026thinsp;70% ultrasound prevalence in Japan) and standardization of cholecystectomy. The UK has the lowest ASMR (\u0026lt;\u0026thinsp;1/100,000), benefiting from optimization of gallstone treatment guidelines, while the US has seen a rise in ASIR due to obesity (42% of people with BMI\u0026thinsp;\u0026gt;\u0026thinsp;30). There are two underlying drivers, one of which is intervenable risk, with approximately 31% of GBTC deaths globally associated with high BMI and diabetes, with a higher attribution in East Asia (37.2% in China)(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The second is diagnostic and treatment disparities, with inadequate coverage of endoscopic technology in primary care in China (\u0026lt;\u0026thinsp;30% of county hospitals)(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In Japan, the early diagnosis rate is over 50%. Extreme regional polarization of the burden of LC, with China leading the global burden, accounting for 46.3% of global liver cancer deaths(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Significant difference in sex ratio, Chinese male ASIR is 4.5 times higher than that of females(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Mainly attributed to significantly higher rates of HBV infection (8.3%) and alcohol consumption (48%) in men(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Trend reversal in Europe and the US, China: decline in ASIR due to hepatitis B vaccination (coverage\u0026thinsp;\u0026gt;\u0026thinsp;95%)(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). ASIR in the UK has risen 42% in the last decade(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Associated with NAFLD (prevalence 25%) and late diagnosis. Changes in etiologic contribution, HBV remains dominant in China (68.4% of attributable deaths), but metabolic risk is growing fast (12% increase in attributable DALYs from 2010\u0026ndash;2019)(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). HCV contribution declines in Japan and Korea (antiviral treatment coverage\u0026thinsp;\u0026gt;\u0026thinsp;80% in Japan), but alcohol-related liver cancer rises in Korean men(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Trend-differentiated characteristics of PC, ASIR continued increase in China (1.1% per year), urbanization-associated obesity (25.7% obesity rate in urban males) as the main cause(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Decline in ASIR in Japan and Korea, associated with tobacco control (\u0026lt;\u0026thinsp;25% male smoking in Japan). Sex differences in mortality rates, with both Chinese and American males having higher ASMR than females (U.S. M:F\u0026thinsp;=\u0026thinsp;1.4:1). In China, ASMR declined more rapidly in women (1.1% per year vs. 0.6% in men)(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Key risk-driven evidence, with significant attribution to smoking: in Korea, smoking contributes 31.2% of PC deaths (37.4% in men). The role of metabolic syndrome, about 19% of PC deaths globally are associated with hyperglycemia, with 28.4% of deaths in China attributed to hyperglycemia(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Deeper motivations for regional differences, infection control determines liver cancer burden, and HBV vaccination in China reduces childhood infection rate to 1%(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHowever, stockpiled infections in the elderly population continue to drive up mortality (\u0026gt;\u0026thinsp;65 years accounts for 68% of deaths)(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Differences in health systems affect GBTC outcomes; 5-year survival rate for gallbladder cancer in China is only 19%, much lower than in Japan (40%)(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Reflecting differences in early screening and treatment standardization. \u0026ldquo;Westernization\u0026rdquo; of Diet and Metabolic Risk: Processed Meat Intake Increases 80% in 30 Years in China and South Korea, Pushing PC Risk Higher(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePriority areas of intervention, China Strengthening hepatitis B antiviral treatment continuity and investment in GBTC screening equipment at the grassroots level.Japan and Korea Expand HCV screening and alcohol control policies (e.g., 30% tax increase in Korea)(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). UK and US Develop community intervention guidelines for NAFLD. Gender-differentiated prevention and control Promote early detection of HCC for East Asian men and design metabolic risk interventions for women (e.g., China Diabetes Screening Program)(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are deeply grateful to the Institute for Health Metrics and Evaluation (IHME) at the University of Washington for generously providing access to the data that supported this research. We also extend our sincere appreciation to the reviewers and editors for their insightful comments and rigorous evaluation, which greatly contributed to the improvement of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShuang Zhang(First author)：Writing \u0026ndash; original draft、Formal analysis、Investigation、Software;Yaxin Hu(Second author)：Writing \u0026ndash; review \u0026amp; editing、Data curation、Methodology/Validation; Dawei Guo(Third author): Writing \u0026ndash; review \u0026amp; editing、Conceptualization、Resources、Validation;Xiaobo Li(Corresponding author): Writing \u0026ndash; review \u0026amp; editing、Funding acquisition、Resources、Supervision;Jiuzhang Men(Corresponding author): Writing \u0026ndash; review \u0026amp; editing、Funding acquisition、Methodology、Project administration;Yuming Zhang(Corresponding author): Writing \u0026ndash; review \u0026amp; editing、Formal analysis、Validation;Jilong Guo(Corresponding author): Writing \u0026ndash; review \u0026amp; editing、Conceptualization、Resources\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the research project of Shanxi Provincial Association for Science and Technology, \u0026ldquo;Research on high-quality development of traditional Chinese medicine business in Shanxi\u0026rdquo;, the Fund of Clinical Basic Disciplines of Traditional Chinese Medicine of Shanxi University of Traditional Chinese Medicine, and the lateral project of North Central University (No. 202102130501011).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data presented in this study are included in the body of the article/supplementary material, and further data needs can be addressed to the first author for consultation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1.\u0026nbsp;Shanxi University of Traditional Chinese Medicine, School of Basic Medical Sciences\u003c/p\u003e\n\u003cp\u003e2. The Fourth Clinical College of Shanxi University of Traditional Chinese Medicine\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTan DJH, Setiawan VW, Ng CH, Lim WH, Muthiah MD, Tan EX, et al. Global burden of liver cancer in males and females: Changing etiological basis and the growing contribution of NASH. Hepatology. 2022;77(4):1150-63.\u003c/li\u003e\n\u003cli\u003eKocarnik JM, May M, Acheson A, Bhangdia K, Compton K, Dean F, et al. The global burden of primary liver cancer and underlying etiologies from 1990 to 2021. Journal of Clinical Oncology. 2024;42:10573-.\u003c/li\u003e\n\u003cli\u003eTeng Y, Xia C, Li H, Cao M, Yang F, Yan X, et al. Cancer statistics for young adults aged 20 to 49 years in China from 2000 to 2017: a population-based registry study. Sci China Life Sci. 2024;67(4):711-9.\u003c/li\u003e\n\u003cli\u003eJiang Z, Zeng G, Dai H, Bian Y, Wang L, Cao W, et al. Global, regional and national burden of liver cancer 1990-2021: a systematic analysis of the global burden of disease study 2021. BMC public health. 2025.\u003c/li\u003e\n\u003cli\u003eChutian W, Giovanni T, D BC, Yilei M, To CT, Yusuf Y, et al. Global, regional, and national burden of primary liver cancer attributable to metabolic risks: an analysis of the Global Burden of Disease Study 1990-2021. American Journal of Gastroenterology. 2025.\u003c/li\u003e\n\u003cli\u003eKocarnik JM, May M, Acheson A, Bhangdia K, Compton K, Dean F, et al. The global burden of primary liver cancer and underlying etiologies from 1990 to 2021. Journal of Clinical Oncology. 2024.\u003c/li\u003e\n\u003cli\u003eDanpanichkul P, Pang Y, D\u0026iacute;az LA, White TM, Sirimangklanurak S, Auttapracha T, et al. Alcohol-Attributable Cancer: Update From the Global Burden of Disease 2021 Study. Alimentary Pharmacology \u0026amp; Therapeutics. 2025.\u003c/li\u003e\n\u003cli\u003eIlic I, Ilic M. Global Burden of Pancreatic Cancer Attributable to High Body-Mass Index in 204 Countries and Territories, 1990\u0026ndash;2019. Cancers. 2024;16(4):719.\u003c/li\u003e\n\u003cli\u003eDanpanichkul P, Auttapracha T, Sukphutanan B, Ng CH, Wattanachayakul P, Kongarin S, et al. The Burden of Overweight and Obesity-Associated Gastrointestinal Cancers in Low and Lower-Middle-Income Countries: A Global Burden of Disease 2019 Analysis. American Journal of Gastroenterology. 2024;119(6):1177-80.\u003c/li\u003e\n\u003cli\u003eDanpanichkul P, Suparan K, Tothanarungroj P, Dejvajara D, Rakwong K, Pang Y, et al. Epidemiology of gastrointestinal cancers: a systematic analysis from the Global Burden of Disease Study 2021. Gut. 2024;74(1):26-34.\u003c/li\u003e\n\u003cli\u003eVos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020.\u003c/li\u003e\n\u003cli\u003eKocarnik JM, Compton K, Dean FE, Fu W, Gaw BL, Harvey JD, et al. Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019. JAMA Oncol. 2022.\u003c/li\u003e\n\u003cli\u003eCalderaro J, Žigutytė L, Truhn D, Jaffe A, Kather JN. Artificial intelligence in liver cancer \u0026mdash; new tools for research and patient management. Nature Reviews Gastroenterology \u0026amp;amp; Hepatology. 2024;21(8):585-99.\u003c/li\u003e\n\u003cli\u003eXia Z, Han W, Niu H, Dong H. Global Burden of Pancreatic Cancer Among Individuals Aged 15\u0026ndash;59 Years in 204 Countries and Territories, 1990\u0026ndash;2021: A Systematic Analysis for the GBD 2021 and Projections to 2045. Cancers. 2025;17(11):1757.\u003c/li\u003e\n\u003cli\u003eBao W, Qiao L, Li M, Shi G, Liu L. Trends and cross-country inequalities in the global, regional, and national burden of gallbladder and biliary tract cancer from 1990 to 2021, along with the predictions for 2035. Cancer Epidemiology. 2025;96:102802.\u003c/li\u003e\n\u003cli\u003eDanpanichkul P, Ng CH, Tan DJH, Muthiah MD, Kongarin S, Srisurapanont K, et al. The Global Burden of Early-Onset Biliary Tract Cancer: Insight From the Global Burden of Disease Study 2019. Journal of Clinical and Experimental Hepatology. 2024;14(2):101320.\u003c/li\u003e\n\u003cli\u003eSheena BS, Hiebert L, Han H, Ippolito H, Abbasi-Kangevari M, Abbasi-Kangevari Z, et al. Global, regional, and national burden of hepatitis B, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet Gastroenterology \u0026amp;amp; Hepatology. 2022;7(9):796-829.\u003c/li\u003e\n\u003cli\u003eEluri M, Hatia R, Javle MM, Hassan M. The association of family history of primary liver cancer with cholangiocarcinoma: USA case-control study. Journal of Clinical Oncology. 2022;40:403-.\u003c/li\u003e\n\u003cli\u003eChotiprasidhi P, Sato-Espinoza AK, Wangensteen KJ. Germline Genetic Associations for Hepatobiliary Cancers. Cellular and Molecular Gastroenterology and Hepatology. 2024;17(4):623-38.\u003c/li\u003e\n\u003cli\u003eCalderaro J, Žigutytė L, Truhn D, Jaffe A, Kather JN. Artificial intelligence in liver cancer \u0026mdash; new tools for research and patient management. Nature Reviews Gastroenterology \u0026amp; Hepatology. 2024.\u003c/li\u003e\n\u003cli\u003ePang Y, Lv J, Kartsonaki C, Yu C, Guo Y, Chen Y, et al. Genetic and healthy lifestyle factors in relation to the incidence and prognosis of severe liver disease in the Chinese population. Chinese Medical Journal. 2023;136(16):1929-36.\u003c/li\u003e\n\u003cli\u003eHan J, Chen C, Tang T, Liu W, Chen R, Li S, et al. Burden of Liver Cancer in China from 1990 to 2019 and projections to 2044: Findings from the Global Burden of Disease Study. 2023.\u003c/li\u003e\n\u003cli\u003eChen S, Han K, Song Y, Liu S, Li X, Wang S, et al. Current status, trends, and predictions in the burden of gallbladder and biliary tract cancer in China from 1990 to 2019. Chinese Medical Journal. 2022;135(14):1697-706.\u003c/li\u003e\n\u003cli\u003eDutta P, Danpanichkul P, Suparan K, Pang Y, Rakwong K, Fine MR, et al. Sex disparities in global burden of gallbladder and biliary tract cancer: analysis of Global Burden of Disease study from 2010 to 2019. Journal of Gastroenterology and Hepatology. 2024;39(12):2863-71.\u003c/li\u003e\n\u003cli\u003eWu S, Zhao R, Zhuang Q, Li MT, Qian YQ, Ye X, et al. Disease burden of primary gallbladder and biliary tract cancers associated with body mass index in 195 countries and territories, 1990‐2017: A systematic analysis for the \u0026lt;scp\u0026gt;Global Burden of Disease Study\u0026lt;/scp\u0026gt; 2017. Journal of Digestive Diseases. 2022;23(3):157-65.\u003c/li\u003e\n\u003cli\u003eJung K-W, Kang MJ, Park EH, Yun EH, Kim H-J, Kim J-E, et al. Prediction of Cancer Incidence and Mortality in Korea, 2024. Cancer Research and Treatment. 2024;56(2):372-9.\u003c/li\u003e\n\u003cli\u003eXie D, Liu F, Zhou D, Zhu Q, Xiao F, Zhang K. Global burden and cross-country inequalities in gallbladder and biliary tract cancer (1990\u0026ndash;2021) with projections to 2050: insights from the global burden of disease study 2021. Front Med. 2025;12.\u003c/li\u003e\n\u003cli\u003eLi Q, Ding C, Cao M, Yang F, Yan X, He S, et al. Global epidemiology of liver cancer 2022: An emphasis on geographic disparities. Chinese Medical Journal. 2024;137(19):2334-42.\u003c/li\u003e\n\u003cli\u003eLin L, Yan L, Liu Y, Qu C, Ni J, Li H. The Burden and Trends of Primary Liver Cancer Caused by Specific Etiologies from 1990 to 2017 at the Global, Regional, National, Age, and Sex Level Results from the Global Burden of Disease Study 2017. Liver Cancer. 2020;9(5):563-82.\u003c/li\u003e\n\u003cli\u003eQiu H, Cao S, Xu R. Cancer incidence, mortality, and burden in China: a time‐trend analysis and comparison with the United States and United Kingdom based on the global epidemiological data released in 2020. Cancer Communications. 2021;41(10):1037-48.\u003c/li\u003e\n\u003cli\u003eCao M, Xia C, Cao M, Yang F, Yan X, He S, et al. Attributable liver cancer deaths and disability-adjusted life years in China and worldwide: profiles and changing trends. Cancer Biology \u0026amp;amp; Medicine. 2024:1-13.\u003c/li\u003e\n\u003cli\u003eYang S, Deng Y, Zheng Y, Zhang J, He D, Dai Z, et al. Burden, trends, and predictions of liver cancer in China, Japan, and South Korea: analysis based on the Global Burden of Disease Study 2021. Hepatology International. 2025;19(2):441-59.\u003c/li\u003e\n\u003cli\u003eYan F, Yu L, Liu Z, Qi J, Wang L, Zhou M, et al. Subnational trend and driving factors for pancreatic cancer burden in China, 1990\u0026ndash;2021: an analysis based on the Global Burden of Disease Study 2021. Annals of Medicine. 2025;57(1).\u003c/li\u003e\n\u003cli\u003eChen Y, Chen T, Fang J-Y. Burden of gastrointestinal cancers in China from 1990 to 2019 and projection through 2029. Cancer Letters. 2023;560:216127.\u003c/li\u003e\n\u003cli\u003eDing C, Fu X, Zhou Y, Liu X, Wu J, Huang C, et al. Disease burden of liver cancer in China from 1997 to 2016: an observational study based on the Global Burden of Diseases. BMJ Open. 2019;9(4).\u003c/li\u003e\n\u003cli\u003eKatanoda K, Ito Y, Sobue T. International comparison of trends in cancer mortality: Japan has fallen behind in screening-related cancers. Japanese Journal of Clinical Oncology. 2021;51(11):1680-6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Global burden of disease, epidemiology, disability, age-period-cohort modeling, time trends, public health policy, Five countries","lastPublishedDoi":"10.21203/rs.3.rs-7432498/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7432498/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe burden of common cancer diseases of the liver-related cancers, including liver cancer (LC),pancreatic cancer (PC) and gallbladder and biliary tract cancer (GC). With its high prevalence and mortality rates, it has a serious impact on quality of life and increases the burden on the healthcare system. Despite the high disease burden of liver-related cancers, they remain under-recognized in global health policy. This study examined epidemiologic trends in liver-related cancers in China, Korea, Japan, the United States, and the United Kingdom from 1990 to 2021, highlighting regional differences and projecting future burdens.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study used the 2021 Global Burden of Disease (GBD) data to analyze the incidence, prevalence, and years lived with disability (YLD) of liver-related cancers. A Bayesian age\u0026ndash;period\u0026ndash;cohort (BAPC) model was applied to project future trends through 2050. In addition, country-specific variance analysis and sensitivity analysis were performed to test the robustness of the model to input data quality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eIn 2021, China reported the highest number of new cases for GC (1,119), LC (11,860), and PC (2,821), with males affected more than females. The United States, Japan, South Korea, and the United Kingdom followed. GC and PC incidence rose in China but fell in Japan and Korea; LC decreased in China but increased markedly in the U.S. Projections from 2022 to 2025 suggest China will continue to have the highest absolute burden, the U.S. will report high DALYs due to its population size, Japan and Korea will maintain moderate yet significant age-standardized rates (ASRs), and the U.K. will see a slight rise in deaths.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eHepatobiliary cancers remain a major public health issue in all five countries, with burden influenced by age, gender, and demographic structure. China faces high incidence and absolute burden, the U.S. carries substantial DALYs due to population size, Japan and Korea show intermediate ASRs with variable trends, and the U.K. experiences gradual increases in mortality. Locally adapted health policies and targeted interventions are essential. Future studies should incorporate socioeconomic, behavioral, and health system factors to improve cancer control strategies.\u003c/p\u003e","manuscriptTitle":"Burden and Trends of Liver-Related Cancers, 1990–2021: A Comparative Analysis of China, Korea, Japan,the United Kingdom , and the United States","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-10 14:39:37","doi":"10.21203/rs.3.rs-7432498/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"682bdad9-3f6f-48f4-bd37-aaf23a2d2f23","owner":[],"postedDate":"October 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-19T14:09:08+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-10 14:39:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7432498","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7432498","identity":"rs-7432498","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}