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. Author manuscript; available in PMC: 2022 Dec 19.
Published in final edited form as: Cell Metab. 2022 Jun 3;34(7):969–977.e2. doi: 10.1016/j.cmet.2022.05.003

Changing global epidemiology of liver cancer from 2010 to 2019: NASH is the fastest growing cause of liver cancer

Daniel Q Huang 1,2,3, Amit G Singal 4, Yuko Kono 5, Darren JH Tan 2, Hashem B El-Serag 6,7,8, Rohit Loomba 1,9,10,*
PMCID: PMC9762323  NIHMSID: NIHMS1852434  PMID: 35793659

SUMMARY

Liver cancer epidemiology is changing due to increasing alcohol consumption, rising prevalence of obesity, and advances in hepatitis B virus (HBV) and hepatitis C virus (HCV) treatment. However, the impact of these changes on global liver cancer burden remains unclear. We estimated global and regional temporal trends in the burden of liver cancer and the contributions of various liver disease etiologies using the methodology framework of the Global Burden of Disease study. Between 2010 and 2019, there was a 25% increase in liver cancer deaths. Age-standardized death rates (ASDRs) increased only in the Americas and remained stable or fell in all other regions. Between 2010 and 2019, non-alcoholic steatohepatitis (NASH) and alcohol had the fastest growing ASDRs, while HCV and HBV declined. Urgent measures are required at a global level to tackle underlying metabolic risk factors and slow the growing burden of NASH-associated liver cancer, especially in the Americas.

In brief

Huang et al. estimate global and regional trends in the burden of liver cancer and the contributions of various liver disease etiologies from 2010 to 2019. They determined that NASH was the fastest growing cause of age-adjusted liver cancer deaths globally, while age-adjusted deaths from hepatitis B and C declined.

Graphical Abstract

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INTRODUCTION

Liver cancer is the third leading cause of cancer death worldwide (Sung et al., 2021). The major etiologies for liver cancer are hepatitis B virus (HBV), hepatitis C virus (HCV), alcohol, and non-alcoholic steatohepatitis (NASH) (Global Burden of Disease Liver Cancer Collaboration et al., 2017). Over the past decade, there have been changes in the burden and etiology of liver diseases (Asrani et al., 2019).

Increasing vaccination coverage for HBV, coupled with the widespread availability of antiviral therapy, has reduced HBV-associated liver cancer burden worldwide (Huang et al., 2021b; Huang and Lim, 2018, 2020; Lok et al., 2016; Thomas, 2019). Safe and effective oral antivirals have been available for HCV since 2014, which can similarly significantly reduce hepatocellular carcinoma (HCC) risk, although the impact of HCV treatment on global liver cancer burden remains unclear (Singal and El-Serag, 2015). Increasing economic wealth has fueled an increase in global alcohol-per-capita consumption, which may have increased the burden of alcohol-associated liver cancer (El-Serag et al., 2020; Seitz et al., 2018). Finally, the prevalence of NASH has also risen in parallel with obesity and diabetes, leading to demonstrated rises in NASH-associated liver cancer in the United States, Europe, and Asia; however, recent global data are still lacking (Dyson et al., 2014; El-Serag et al., 2020; Huang et al., 2021a; Le et al., 2021; Loomba et al., 2021; Loomba and Sanyal, 2013).

Previous studies on liver cancer epidemiology have largely focused on country-, region-, or etiology-specific data. Updated data from a global perspective are limited. Herein, we report temporal trends in liver cancer incidence, mortality, and disability-adjusted life-years (DALYs) and the contributions of various liver disease etiologies across 204 countries and territories from 2010 to 2019.

RESULTS

Global burden of liver cancer in 2019

Globally, in 2019, there were 534,364 incident cases (95% uncertainty interval [UI] 486,550–588,639), 484,577 deaths (95% UI 444,091–525,798), and 12.5 million (95% UI 11.4–13.7 million) DALYs due to liver cancer (Tables 1, 2, and S4; Figure 1A). In 2019, the estimated age-standardized incident rate (ASIR), age-standardized death rate (ASDR), and age-standardized DALYs (ASDALYs) of liver cancer were 6.51 per 100,000 (95% UI 5.95–7.16), 5.95 per 100,000 (95% UI 5.44–6.44), and 151.08 per 100,000 (95% UI 137.53–167.82), respectively. Between 2010 and 2019, there was a 27% increase in the frequency of incident liver cancer cases, a 25% increase in liver cancer deaths, and 21% increase in DALYs. Over this period, the estimated annual percentage changes (APCs) of the ASIR and ASDR were stable, with APCs of 0.03% (95% CI −0.01 to 0.05) and −0.10% (95% CI −0.25 to 0.06), respectively, whereas ASDALYs decreased (APC −0.27%, 95% CI −0.34 to −0.21).

Table 1.

Incident cases and age-standardized incidence rates of liver cancer in 2010 and 2019 and the temporal trend of age-standardized incident rates from 2010 to 2019

2010 2019
No. incident cases (95% UI) ASIR per 100,000 (95% UI) No. incident cases (95% UI) ASIR per 100,000 (95% UI) Annual percentage change of ASIR (95% CI)
Global 420,196 (398,639–440,763) 6.50 (6.15–6.81) 534,364 (486,550–588,639) 6.51 (5.95–7.16) 0.03 (−0.01 to 0.05)
Sex
Male 292,049 (276,249–310,447) 9.54 (9.03–10.13) 376,483 (421,982–335,003) 9.71 (8.69–10.84) 0.21 (0.20–0.23)
Female 128,147 (119,003–134,959) 3.76 (3.49–3.96) 157,881 (140,436–176,052) 3.63 (3.23–4.05) −0.39 (−0.41 to −0.37)
Socio-demographic index
Low SDI 16,006 (14,421–17,603) 3.90 (3.53–4.28) 19,279 (16,951–21,648) 3.69 (3.27–4.11) −0.62 (−0.64 to −0.59)
Low-middle SDI 41,378 (38,129–44,607) 3.89 (3.55–4.20) 55,345 (50,136–61,558) 4.05 (3.67–4.51) 0.49 (0.42–0.55)
Middle SDI 152,103 (141,917–165,051) 7.85 (7.33–8.49) 185,567 (162,261–210,710) 8.28 (7.24–9.47) 0.68 (0.52–0.84)
High-middle SDI 89,077 (83,223–95,370) 5.46 (5.10–5.84) 106,792 (94,151–120,908) 5.34 (4.70–6.05) −0.25 (−0.40 to −0.10)
High SDI 121,477 (112,975–126,370) 8.01 (7.54–8.29) 140,145 (125,500–154,013) 7.61 (6.88–8.36) −0.58 (−0.74 to −0.42)
Region
Africa 17,073 (15,331–18,873) 4.43 (3.99–4.86) 21,024 (18,482–23,886) 4.08 (3.63–4.57) −0.89 (−0.91 to −0.87)
Eastern Mediterranean 21,819 (20,220–23,921) 6.76 (6.28–7.38) 28,024 (22,850–34,563) 6.45 (5.32–7.90) −0.50 (−0.53 to −0.47)
Europe 60,706 (58,037–62,220) 4.42 (4.25–4.53) 68,698 (61,389–76,767) 4.39 (3.94–4.90) −0.15 (−0.38 to 0.09)
Americas 35,370 (33,973–36,349) 3.56 (3.42–3.66) 49,708 (43,650–56,326) 3.92 (3.45–4.44) 1.11 (1.09–1.15)
Southeast Asia 53,133 (48,832–62,220) 4.16 (3.81–4.46) 69,181 (60,277–79,273) 4.04 (3.52–4.63) −0.34 (−0.39 to −0.28)
Western Pacific 230,265 (212,955–249,156) 11.02 (10.19–11.89) 295,484 (257,479–339,134) 11.02 (9.62–12.61) 0.02 (−0.05 to 0.09)
Etiology
Alcohol 74,377 (61,771–88,219) 1.16 (0.96–1.37) 98,463 (79,034–120,127) 1.19 (0.96–1.45) 0.34 (0.33–0.36)
Hepatitis B 172,897 (154,745–192,114) 2.57 (2.30–2.86) 218,855 (186,488–254,887) 2.62 (2.24–3.05) 0.23 (0.17–0.29)
Hepatitis C 123,598 (108,700–128,172) 2.00 (1.75–2.24) 152,225 (131,581–174,627) 1.90 (1.64–2.17) −0.60 (−0.67 to −0.54)
NASH 26,220 (21,628–31,705) 0.41 (0.34–0.50) 36,339 (29,494–44,855) 0.45 (0.37–0.55) 0.88 (0.79–0.98)
Other causes 23,104 (19,666–26,849) 0.35 (0.30–0.41) 28,482 (23,574–34,082) 0.35 (0.29–0.42) 0.12 (0.01–0.24)
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ASIR, age-standardized incidence rate; SDI, socio-demographic index; NASH, nonalcoholic steatohepatitis.

Table 2.

Deaths and age-standardized death rates of liver cancer in 2010 and 2019 and the temporal trend of age-standardized death rates from 2010 to 2019

2010 2019
No. deaths (95% UI) ASDR per 100,000 (95% UI) No. deaths (95% UI) ASDR per 100,000 (95% UI) Annual percentage change of ASDR (95% CI)
Global 386,342 (366,367–404,997) 6.05 (5.72–6.33) 484,577 (444,091–525,798) 5.95 (5.44–6.44) −0.10 (−0.25 to 0.06)
Sex
Male 263,323 (249,598–278,647) 8.78 (8.31–9.27) 333,673 (299,581–368,334) 8.73 (7.88–9.60) −0.06 (−0.17 to 0.05)
Female 123,018 (113,977–129,867) 3.63 (3.36–3.83) 150,904 (134,123–167,013) 3.46 (3.08–3.83) −0.50 (−0.65 to −0.35)
Socio-demographic index
Low SDI 16,435 (14,822–18,089) 4.17 (3.77–4.57) 20,756 (18,217–23,330) 3.93 (3.49–4.38) −0.66 (−0.72 to −0.61)
Low-middle SDI 42,132 (38,776–45,219) 4.09 (3.73–4.39) 57,241 (52,130–63,452) 4.23 (3.86–4.68) 0.40 (0.08–0.71)
Middle SDI 147,231 (137,694–158,985) 7.83 (7.32–8.41) 196,959 (172,833–223,210) 7.92 (6.97–8.93) 0.39 (0.11–0.67)
High-middle SDI 83,440 (78,200–88,646) 5.15 (4.83–5.46) 97,189 (87,228–108,111) 4.83 (4.34–5.38) −0.69 (−0.91 to −0.46)
High SDI 96,952 (89,685–100,974) 6.24 (5.83–6.48) 112,240 (102,489–118,738) 5.89 (5.44–6.21) −0.65 (−0.74 to −0.55)
Region
Africa 17,599 (15,794–19,425) 4.76 (3.84–4.13) 21,537 (18,873–24,287) 4.37 (3.90–4.87) −0.92 (−0.97 to −0.88)
Eastern Mediterranean 21,615 (20,010–23,703) 6.92 (6.40–7.55) 27,219 (22,054–33,580) 6.49 (5.33–7.91) −0.72 (−0.83 to −0.61)
Europe 56,407 (53,637–57,839) 4.03 (3.84–4.13) 63,501 (58,916–67,531) 3.95 (3.67–4.19) 0.31 (−0.47 to −0.15)
Americas 32,449 (30,926–33,426) 3.26 (3.11–3.36) 46,132 (42,506–49,469) 3.61 (3.33–3.88) 1.09 (0.97–1.22)
Southeast Asia 53,647 (49,252–57,466) 4.37 (4.01–4.68) 70,029 (60,641–80,604) 4.22 (3.67–4.84) −0.53 (−0.73 to −0.33)
Western Pacific 202,914 (187,913–219,829) 9.84 (9.11–10.66) 254,054 (221,667–289,533) 9.50 (8.31–10.78) −0.29 (−0.64 to 0.06)
Etiology
Alcohol 68,980 (57,146–82,279) 1.08 (0.90–1.29) 90,740 (73,349–109,402) 1.10 (0.89–1.33) 0.23 (0.09–0.37)
Hepatitis B 156,307 (139,827–175,398) 2.35 (2.10–2.64) 191,736 (161,861–223,727) 2.31 (1.95–2.69) −0.20 (−0.31 to −0.09)
Hepatitis C 114,657 (100,138–128,567) 1.89 (1.64–2.11) 141,810 (121,787–161,828) 1.78 (1.53–2.04) −0.62 (−0.79 to −0.46)
NASH 25,249 (20,882–30,666) 0.40 (0.33–0.49) 34,729 (28,395–43,182) 0.43 (0.35–0.53) 0.70 (0.43–0.97)
Other causes 21,147 (18,055–24,682) 0.32 (0.28–0.38) 25,560 (21,229–30,491) 0.32 (0.27–0.38) −0.02 (−0.17 to 0.12)
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ASDR, age-standardized death rate; SDI, sociodemographic index; NASH, nonalcoholic steatohepatitis.

Figure 1. Estimated global death cases and age-standardized death rates of liver cancer from 2010 to 2019.

Figure 1.

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(A) Frequency of liver cancer deaths in 2010 versus 2019, global and by World Health Organization region.

(B) Frequency of liver cancer deaths by World Health Organization region from 2010 to 2019.

(C) Contribution to global liver cancer deaths in 2019 by World Health Organization region.

(D) Age-standardized death rates of liver cancer by World Health Organization region in 2010 versus 2019.

(E) Age-standardized death rates of liver cancer by World Health Organization region from 2010 to 2019.

(F) Frequency of liver cancer deaths in 2010 versus 2019 by sociodemographic index.

(G) Age-standardized death rates of liver cancer from 2010 to 2019 by sociodemographic index ASDR, age-standardized death rate; SDI, sociodemographic index.

Burden of liver cancer by World Health Organization region

The estimated frequencies of incident liver cancer cases, deaths, DALYs, and rates (ASIRs, ASDRs, and ASDALYs) in different World Health Organization (WHO) regions are summarized in Tables 1, 2, and S4. In 2019, the Western Pacific region had the highest frequency of incident liver cancer cases (n = 295,484), deaths (n = 254,054), and DALYs (6.7 million) (Figures 1A and 1B). However, the Americas had the greatest increase between 2010 and 2019 in liver cancer incident cases (+41%), deaths (+42%), and DALYs (+36%). The proportions of global liver cancer deaths in 2019 contributed by each WHO region are shown in Figure 1C.

During the study period, ASIRs increased in the Americas (APC: 1.11%, 95% CI 1.09–1.15), remained stable in the Western Pacific and Europe, and decreased in all other WHO regions, with the greatest decrease in Africa (APC: −0.89%, 95% CI −0.91 to −0.87) (Table 1). Similarly, ASDRs increased in the Americas between 2012 and 2019 (APC 1.09%, 95% CI 0.97–1.22), remained stable in the Western Pacific, but decreased in Europe and all other WHO regions, with the greatest decrease in Africa (APC: −0.92%, 95% CI −0.97 to −0.88) (Table 2; Figures 1D and 1E). Finally, ASDALYs increased in the Americas (APC: 0.86%, 95% CI 0.65–1.07), remained stable in the Western Pacific, and decreased in all other regions, with the greatest decrease in the Eastern Mediterranean (APC: −0.99%, 95% CI −1.09 to −0.89) (Table S4).

Age-standardized death rates by country

The estimated ASDRs of liver cancer in 2019 by country are shown in Figure 2. The estimated ASDRs ranged from 0.65 deaths per 100,000 (95% UI 0.49–0.84) in Niger to 115.23 deaths per 100,000 (95% UI 91.48–142.48) in Mongolia.

Figure 2. Estimated age-standardized death rates from liver cancer in 2019 by country.

Figure 2.

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Burden of liver cancer by sociodemographic index

The numbers of incident liver cancer cases, deaths, and DALYs, as well as ASIR and ASDR by country’s sociodemographic index (SDI), are summarized in Tables 1, 2, and S4. The highest frequency of incident cases (n = 185,567), deaths (n = 196,959), and DALYs (5.5 million) in 2019 took place in middle SDI countries (Figure 1F). Between 2010 and 2019, the greatest increase in the frequency of incident cases (+39% ) and ASIR (APC: 0.68%, 95% CI 0.52–0.84) occurred in middle SDI countries, whereas the greatest increase in the frequency of deaths (+36%), ASDR (APC: 0.40%, 95% CI 0.08–0.71), and ASDALYs (APC: 0.33%, 95% CI 0.17–0.49) occurred in low-middle SDI countries (Tables 1, 2, and S4; Figures 1F and 1G). By contrast, the greatest reduction in ASIRs, ASDRs, and ASDALYs occurred in low SDI countries, high-middle SDI countries, and high SDI countries, respectively.

Trends in etiology of liver cancer

The frequency of incident cases, deaths, ASIRs, ASDRs, and DALYs by etiology of liver disease is summarized in Tables 1, 2, and S4 and Figure 3A. In 2019, HBV accounted for 40% of the frequency of global liver cancer deaths, followed by HCV (29%), alcohol (19%), NASH (7%), and other causes (5%) (Figure 3B). Between 2010 and 2019, NASH was the fastest growing etiology of incident liver cancer cases (+39%) worldwide, while HCV had the lowest increase (+23%). Similarly, NASH was the fasting growing etiology of liver cancer deaths (+38%), while other causes had the lowest increase (+21%) (Figure 3A). The frequency of liver cancer deaths by etiology and region is summarized in Figure 3C.

Figure 3. Temporal trends in the etiology of liver cancer from 2010 to 2019.

Figure 3.

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(A) Frequency of liver cancer deaths in 2010 versus 2019 by etiology.

(B) Contribution to frequency of liver cancer deaths by etiology in 2019.

(C) Frequency of deaths from liver cancer by region and etiology from 2010 to 2019.

(D) Estimated age-standardized death rates of liver cancer in 2010 versus 2019 by World Health Organization region and etiology.

(E) Estimated age-standardized death rates of liver cancer in 2010 versus 2019 by sociodemographic index and etiology.

NASH; nonalcoholic steatohepatitis; ASDR, age-standardized death rate; SDI, sociodemographic index.

The ASIRs, ASDRs, ASDALYs, and the APCs in these rates between 2010 and 2019 stratified by etiology and region are summarized in Tables S5–S7 and Figure 3D. The global ASIRs for HCV-related HCC decreased (APC: −0.60%, 95% CI −0.67 to −0.54), while the ASIRs for the other four etiologies increased (Table 1). NASH was the etiology with the largest increment in liver cancer ASIRs (APC: 0.88%, 95% CI 0.79–0.98). The ASIRs for NASH-associated liver cancer increased in five of six WHO regions, with the greatest increase in the Americas (APC: 1.33%, 95% CI 1.25–1.41), while the only region with a decrease in ASIR was Africa (APC: −0.19%, 95% CI −0.23 to −0.14) (Table S5). The ASIRs for alcohol-associated liver cancer increased in the Americas, Southeast Asia, and the Western Pacific but decreased in Africa, the Eastern Mediterranean, and Europe, with the greatest increase in the Americas (APC 1.81%, 95% CI 1.76–1.86). ASIRs for HCV-associated liver cancer increased only in the Americas, remained stable in Europe, and decreased in the other four regions. ASIRs for HBV-associated liver cancer increased in the Americas, the Western Pacific, and the Eastern Mediterranean, while the ASIRs decreased in the other three regions.

Between 2010 and 2019, the global ASDRs of liver cancer due to NASH (APC: 0.70%, 95% CI 0.43–0.97) and alcohol (APC: 0.23%, 95% CI 0.09–0.37) increased, while the ASDRs of liver cancer due to HCV (APC: −0.62%, 95% CI −0.79 to −0.46) and HBV (APC: −0.20%, 95% CI −0.31 to −0.09) declined, and other etiologies remained stable (Table 2). The ASDRs for NASH-associated liver cancer increased in the Americas, Eastern Mediterranean, Western Pacific, and Europe (Table S6; Figure 3D), with the greatest rise in the Americas (APC: 1.33%, 95% CI 1.25–1.42). The ASDRs for NASH-associated liver cancer remained stable in Africa and Southeast Asia. The ASDRs for alcohol-associated liver cancer increased in the Americas (APC: 1.78%, 95% CI 1.64–1.93) and the Western Pacific (APC: 0.48%, 95% CI 0.22–0.73); decreased in Africa, the Eastern Mediterranean, and Europe; but remained stable in Southeast Asia. The ASDRs for HBV-associated liver cancer increased only in the Americas (APC: 0.66%, 95% CI 0.56–0.75) but decreased in Africa, Europe, and Southeast Asia and remained stable in the Western Pacific. The ASDRs for HCV-associated liver cancer increased only in the Americas (APC: 0.70%, 95% CI 0.42–0.99) and decreased in all other WHO regions, with the greatest decrease in the Western Pacific (APC: −1.36%, 95% CI −1.51 to −1.21).

The increase in the liver cancer ASDRs between 2010 and 2019 among middle SDI countries was largely driven by an increase in NASH (APC: 1.15%, 95% CI 0.82–1.48) and alcohol (APC 0.87%, 95% CI 0.51–1.24). (Table S8; Figure 3E). Similarly, the increase in ASDRs among low-middle SDI countries was driven by NASH (APC: 1.08%, 95% CI 0.87–1.27), alcohol (APC: 1.04%, 95% CI 0.83–1.26), and HCV (APC: 0.48%, 95% CI 0.25–0.70). By contrast, low, high-middle, and high SDI countries experienced reductions in the ASDRs from HCV, HBV, and other causes.

DISCUSSION

Main findings

Utilizing data from the 2019 GBD study, we determined that there were an estimated 534,000 incident cases, 485,000 deaths, and 12.5 million DALYs due to liver cancer. Between 2010 and 2019, there was a 27% increase in the frequency of incident liver cancer cases and a 25% increase in the frequency of liver cancer deaths, although there were no significant changes in age-standardized incidence and death rates. The growth as well as aging of the world population may contribute to the observed disconnect in the temporal trends of frequency and age-standardized incidence and death rates. Although the Western Pacific contributed more than half of the global liver cancer deaths in 2019, ASDRs (APC: −0.29%) remained stable between 2010 and 2019. By contrast, ASDRs (APC: 1.09%) rose sharply in the Americas but declined in all other WHO regions.

The global ASDR due to HBV-associated liver cancer decreased (APC: −0.20%) between 2010 and 2019, likely due to the impact of successful vaccination programs, aflatoxin reduction programs, and antiviral therapy (Cox et al., 2020). However, the ASDR of HBV-associated liver cancer in the Americas increased, in contrast to all other regions, possibly due to underdiagnosis and a lack of disease awareness (Le et al., 2020). There was a reduction in the global ASDR of HCV-associated liver cancer (APC: −0.62%), due to decreasing death rates in all WHO regions except for the Americas, contributed by the availability of highly effective oral antiviral therapy (Dang et al., 2020). However, there remain major gaps in diagnosis and linkage to care (Desai et al., 2021; Huang et al., 2021c; Thomas, 2019; Ye et al., 2022), and substantial improvements are required in infection control, screening, and treatment rates to achieve the elimination targets set by the WHO (Heffernan et al., 2019).

NASH was the fastest growing cause of liver cancer deaths globally, especially in the Americas, driven by rapidly rising obesity rates (Ward et al., 2019). The incidence of liver cancer due to NASH is projected to increase further in the next decade in the United States, Europe, and Asia (Estes et al., 2018a, 2018b, 2020). Urgent measures are required at a global level to tackle the underlying metabolic risk factors and slow the growing burden of NASH-related liver cancer (Estes et al., 2018a; Huang et al., 2022; Lazarus et al., 2022; Loomba et al., 2010; Singal and El-Serag, 2022; Tan et al., 2022). Alcohol had the second fastest rising cause of liver cancer ASDRs globally (APC: 0.23%), with the highest increase in the Americas (APC: 1.78%). The global alcohol-per-capita consumption is projected to rise further, especially in the Western Pacific and Southeast Asia (Vos et al., 2020). Implementing policies such as an increased price and taxation for alcohol may be considered at a national level to reduce the burden of alcohol-associated liver cancer in countries with a high alcohol-per-capita consumption (Sheron, 2016). It is notable that the greatest increase in liver cancer ASDRs between 2010 and 2019 took place in middle and low-middle SDI countries, driven by a combination of NASH and alcohol.

In context with published literature

Our study builds on two previous studies of liver cancer using GBD 2015 and GBD 2017 (Global Burden of Disease Liver Cancer Collaboration et al., 2017; Paik et al., 2020) and provides an in-depth analysis of the temporal trends of liver cancer and the contributions of various etiologies using updated data from GBD 2019. The GBD 2017 study included deaths secondary to both primary and secondary cancers under liver cancers (GBD 2017 Disease and Injury Incidence and Prevalence Collaborators, 2018). GBD 2019 proportionally redistributed cases of metastases to the liver, resulting in more accurate estimates of liver cancer mortality in our study. Our findings validate several country-specific studies that have reported the growing impact of NASH and alcohol on the burden of liver cancer and provide important data for care providers and policy makers (Dyson et al., 2014; Ganne-Carrié and Nahon, 2019; Julien et al., 2020; Tohra et al., 2021; Younossi et al., 2019, 2015). The current study provides a global overview of the temporal trends in liver cancer burden and the contributions of various liver disease etiologies from 2010 to 2019, unlike most of the other studies that focused on a specific country/region or etiology of liver disease. These data may help promote future investment into liver cancer diagnosis management and research. However, it remains important to continue to track the epidemiology of liver cancer over time, particularly given early signals of potential changes in trends in some countries (Petrick et al., 2020).

Conclusions

The frequency of new cases, deaths, and DALYs from liver cancer increased substantially between 2010 and 2019. Age-standardized incidence and death rates remained stable at the global level but increased substantially in the Americas. NASH and alcohol are the fastest growing causes of age-standardized liver cancer mortality, highlighting the need for urgent measures to tackle these growing issues.

Limitations of study

Our study shares the limitations of the GBD 2019, namely the availability of primary data that is dependent on the quality of each country’s registry (Vos et al., 2020). In countries or regions with missing data, the estimates rely on modeling studies and past trends, potentially resulting in heterogeneity and discrepancies in the accuracy of the data. In addition, there was likely to be under-reporting of data in certain regions such as Africa, due to a lack of disease awareness and access to care. The estimates for the burden of liver cancer are susceptible to some degree of reporter or ascertainment bias, which are inherent issues with utilizing data from the GBD study. Therefore, cautious interpretation is required. The GBD 2019 study classified individuals with cryptogenic liver disease under other causes of liver disease. It is possible that some of these individuals may have had NASH, resulting in an underestimate of the burden of NASH-associated liver cancer, especially in the United States, given the lack of ICD codes and adjudication for NASH. However, we determined that NASH was the fastest rising cause of liver cancer despite the possible underestimate of NASH-associated liver cancer burden. Although NASH and non-alcoholic fatty liver disease (NAFLD) were not specifically listed in the search terms used by the GBD 2019 study, studies were only included if they were population based and representative of the proportions of the etiologies of liver cancer for the respective location. Liver cancer cases were then attributed to NASH when the study explicitly listed the etiology to be NASH or NAFLD. It is less likely to have resulted in missed data for NASH, given the requirement for the included studies to be population based. Finally, data regarding the histological subgroups of liver cancer such as HCC or cholangiocarcinoma are lacking in the GBD 2019 study; therefore, further studies are required to determine the global burden of each histological subgroup.

STAR★METHODS

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources should be directed to and will be fulfilled by the lead contact, Rohit Loomba (roloomba@ucsd.edu).

Materials availability

No new reagents or materials were generated in this study.

Data and code availability

  • This paper utilizes publicly available data. Access to the data is available from http://ghdx.healthdata.org/gbdresults-tool.

  • This study did not generate any unique datasets or code.

  • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

METHOD DETAILS

Data source

This study was performed using data from the GBD 2019, a systematic effort to estimate the burden caused by 369 diseases and 87 risk factors in 204 countries/territories (Vos et al., 2020). Annual frequencies and age-standardized rates (ASRs) of liver cancer-related incidence, mortality and DALYs, from 2010 to 2019 by sex, age, region, and country were obtained from an online data source, the GlobalHealth Data Exchange (GHDx) query tool (http://ghdx.healthdata.org/gbd-results-tool), which is maintained by an ongoing multinational collaboration and coordinated by the Institute for Health Metrics and Evaluation.

Estimation methods

The general estimation methods for the GBD 2019 and the methods for liver cancer disease burden estimation were previously described (Global Burden of Disease Liver Cancer Collaboration et al., 2017; GBD 2019 Diseases and Injuries Collaborators, 2020; Paik et al., 2020). Briefly, data were obtained from population-based cancer registries, vital registration systems or verbal autopsy studies (GBD 2019 Diseases and Injuries Collaborators, 2020). The ICD-10 codes used by the GBD 2019 study for liver cancer deaths were C22.0-C22.8, D13.4, and the ICD-9 codes used were 155–155.1, 155.3–155.9 and 211.5. The GBD study provides a simple quality assessment from 0 to 5 to assess the quality of the data provided by each country/territory. Data quality ratings for the causes of death data from each country are available in Table S1.

Previous estimates of liver cancer deaths in the GBD 2017 included deaths secondary to both primary and secondary cancers (Global Burden of Disease Liver Cancer Collaboration et al., 2017; Paik et al., 2020). In GBD 2019, these deaths were proportionally distributed to both primary liver cancer and extrahepatic primary sites that metastasized to the liver, resulting in fewer deaths attributed to liver cancer in GBD 2019 compared to the GBD 2017 (GBD 2019 Diseases and Injuries Collaborators, 2020). Multiple statistical methods were utilized to minimize data heterogeneity, including misclassification correction, garbage code redistribution and noise reduction algorithms (GBD 2019 Diseases and Injuries Collaborators, 2020). A Cause of Death Ensemble model (CODEm), a Bayesian geospatial regression analysis, was utilized to estimate mortality by age, sex, location, and year. Incidence was estimated by dividing mortality estimates by mortality-to-incidence ratios. DALYs were calculated as the sum of years of life lost and years lived with disability.

To derive the proportions of liver cancer cases due to the five etiology groups included in GBD (hepatitis B; hepatitis C; alcohol; NASH; and other causes), the GBD collaborators performed a systematic literature search of Pubmed (Table S2) and included only population-based studies that provided data for the contribution of liver cancer etiologies. Cases where the etiology was described as “cryptogenic”, “idiopathic”, or “unknown” were included within the “other causes” category. Other etiologies of liver disease, such as haemochromatosis, autoimmune hepatitis, Wilson’s disease, were also included in the “other causes” category. The proportions of liver cancer due to the five specific risk factors were calculated for each study, and the pooled proportions were then used in five separate DisMod-MR 2.1 models (a Bayesian meta-regression-type model) to determine the proportion of liver cancers due to the five liver disease etiologies, stratified by country/territory, gender, and year. When multiple risk factors were reported for individual patients, these were assigned proportionally to the individual risk factors. These estimated proportions were used to split the overall liver cancer estimates into estimates for their respective etiologies of liver disease. As the proportion models were run independently of each other, the final proportion models were scaled to sum to 100% within each age, sex, year, and location, by dividing each proportion by the sum of the five models.

To group countries with similar development status, a Sociodemographic Index (SDI) was used, which combines total fertility rate, average educational attainment in the population over age 15, and measures of income per capita (Table S3). The STROBE statement is enclosed in Table S9.

QUANTIFICATION AND STATISTICAL ANALYSIS

Estimates for the frequency of incident cases and deaths were reported with 95% uncertainty intervals (UIs) as 2.5th and 97.5th ranked values across all 1,000 draws from a posterior distribution. Age-standardized rates were derived using the direct method to the GBD 2019 population estimate (GBD 2019 Diseases and Injuries Collaborators, 2020). The change in any category between 2010 and 2019 was calculated as follows: (value in 2019 - value in 2010)/ value in 2010). For changes of age-standardized rates over time, we calculated annual percent change (APC) and 95% confidence interval (CI) in age-standardized rates using the Joinpoint regression program, version 4.6.0.0 (Statistical Research and Applications Branch, National Cancer Institute, Bethesda). When the annualized rate of change and the lower boundary of its 95% CI were both positive, this was considered as an increasing trend. By contrast, when the annualized rate of change and the upper boundary were negative, this was considered as a decreasing trend. Statistical analyses were conducted using RStudio (Version 4.1.1) and GraphPad Prism.

Supplementary Material

SUPPLEMENTARY MATERIAL
Table S3
Table S1

KEY RESOURCES TABLE.

REAGENT or RESOURCE SOURCE IDENTIFIER
Software and algorithms
RStudio (Version 4.1.1) R Foundation for Statistical Computing https://www.r-project.org/
GraphPad Prism GraphPad Software company https://www.graphpad.com/
Mapchart Mapchart https://www.mapchart.net/
Joinpoint regression program (version 4.6.0.0) Statistical Research and Applications Branch, National Cancer Institute, Bethesda https://surveillance.cancer.gov/joinpoint/download
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Highlights.

  • In 2019, there were an estimated 485,000 deaths globally due to liver cancer

  • Between 2010 and 2019, death rates from liver cancer increased only in the Americas

  • NASH is the fastest growing cause of age-adjusted liver cancer deaths globally

  • Age-adjusted liver cancer deaths from hepatitis B and C declined

ACKNOWLEDGMENTS

The world map was created using https://www.mapchart.net/. R.L. receives funding support from NIAAA (U01AA029019), NIEHS (5P42ES010337), NCATS (5UL1TR001442), NIDDK (U01DK130190, U01DK061734, R01DK106419, P30DK120515, R01DK121378, and R01DK124318), NHLBI (P01HL147835), and DOD PRCRP (W81XWH-18-2-0026). R.L.’s institutions received research grants from Arrowhead Pharmaceuticals, AstraZeneca, Boehringer-Ingelheim, Bristol-Myers Squibb, Eli Lilly, Galectin Therapeutics, Galmed Pharmaceuticals, Gilead, Intercept, Hanmi, Intercept, Inventiva, Ionis, Janssen, Madrigal Pharmaceuticals, Merck, NGM Biopharmaceuticals, Novo Nordisk, Merck, Pfizer, Sonic Incytes, and Terns Pharmaceuticals. D.Q.H. receives funding support from Singapore Ministry of Health’s National Medical Research Council under its NMRC Research Training Fellowship (MOH-000595-01). A.G.S. receives funding support from National Cancer Institute R01 MD012565, U01 CA230694, R01 212008, R01 222900, and R01 256977. Y.K. receives funding support from NIH 1R01CA194307 and 1R01CA215520-01 and research support from GE Healthcare, Canon Medical Systems Co., Lantheus Medical Imaging, and Bracco Diagnostics Inc. H.B.E.-S. receives funding support from NIH P30 DK 56338, Cancer Prevention Research Institute of Texas CAP-CAC RP190641, and VA CSR&D Merit Award IIR 16I31.HB.

Footnotes

DECLARATION OF INTERESTS

R.L. serves as a consultant to Aardvark Therapeutics, Altimmune, Anylam/Regeneron, Amgen, Arrowhead Pharmaceuticals, AstraZeneca, Bristol-Myer Squibb, CohBar, Eli Lilly, Galmed, Gilead, Glympse Bio, Hightide, Inipharma, Intercept, Inventiva, Ionis, Janssen Inc., Madrigal, Metacrine, Inc., NGM Biopharmaceuticals, Novartis, Novo Nordisk, Merck, Pfizer, Sagimet, Theratechnologies, 89 Bio, Terns Pharmaceuticals, and Viking Therapeutics and is cofounder of LipoNexus Inc. D.Q.H. has served as an advisory board member for Eisai. A.G.S. has served as a consultant or on advisory boards for Genentech, AstraZeneca, Bayer, Eisai, Exelixis, Wako Diagnostics, Exact Sciences, Roche, Glycotest, and GRAIL.

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.cmet.2022.05.003.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

SUPPLEMENTARY MATERIAL
NIHMS1852434-supplement-SUPPLEMENTARY_MATERIAL.pdf (211.7KB, pdf)
Table S3
NIHMS1852434-supplement-Table_S3.xlsx (59.9KB, xlsx)
Table S1
NIHMS1852434-supplement-Table_S1.xlsx (15.1KB, xlsx)

Data Availability Statement

  • This paper utilizes publicly available data. Access to the data is available from http://ghdx.healthdata.org/gbdresults-tool.

  • This study did not generate any unique datasets or code.

  • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

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