Introduction
In 2023, three major liver associations redefined metabolic dysfunction–associated steatotic liver disease (MASLD), which was updated from non-alcoholic fatty liver disease (NAFLD), and renamed non-alcoholic steatohepatitis as metabolic dysfunction–associated steatohepatitis.1 This new nomenclature included five cardiometabolic risk factors: overweight or increased waist circumference; prediabetes and type 2 diabetes mellitus (T2DM); hypertension; hypertriglyceridemia; and low high-density lipoprotein cholesterol (HDL-C). The population affected by MASLD has been estimated to be consistent with that of NAFLD.2 The global burden of MASLD in 2021 was 15,018.1 cases (95% UI 13,756.5–16,361.4) per 100,000 population, along with the largest increase occurring in China from 2010 to 2021 (16.9%, 95% UI 14.7–18.9%).3
Previous studies demonstrated that cardiovascular diseases, as the primary extrahepatic fatal outcomes among chronic liver disease, were the leading cause-specific mortality in the NAFLD population.4,5 However, extrahepatic cancers were identified as another cause-specific mortality in the NAFLD population and were even regarded as the first cause-specific mortality in some studies.6 Meanwhile, obesity or overweight, along with T2DM, are acknowledged risk factors for extrahepatic cancers in NAFLD populations.7 Interestingly, in the general cancer population, hypertension has been identified as a comorbidity during anti-cancer treatment or as a risk factor of cancers.8
Although emerging evidence has shown a strong association between MASLD and an increased risk of extrahepatic cancers,7 the association between cardiometabolic risk factors—especially hypertension—and extrahepatic cancers in patients with MASLD remains unclear. Therefore, we hypothesize that hypertension is associated with the risk of extrahepatic cancers in the MASLD population. The combined effects of these factors, including widely acknowledged diabetes or dyslipidemia, metabolism-based treatments, and the severity of liver fibrosis, will also be illustrated in this study.
Methods
Population and study design
This multicenter cross-sectional retrospective study was based on a multicenter hospital-based database from 11 tertiary hospitals across six cities in China (Beijing, Shanghai, Xi'an, Chongqing, Shenyang, and Wuhan), which was compiled between 1/1/2020 and 12/31/2022.
Definition
Definition of MASLD
According to the criteria for the diagnosis of MASLD proposed in 2023,9 MASLD was diagnosed in individuals aged ≥18 years as evidence of hepatic steatosis with one of the following five cardiometabolic criteria: (I) overweight/obesity [BMI ≥ 23.00 kg/m2 for Asians] OR waist circumference ≥94 cm (male) or ≥80 cm (female); (II) fasting serum glucose ≥5.6 mmol/L [100 mg/dL] OR 2-h post-load glucose levels ≥7.8 mmol/L [≥140 mg/dL] OR HbA1c ≥ 5.7% [39 mmol/mol] OR type 2 diabetes OR treatment for T2DM; (III) blood pressure ≥130/85 mmHg OR specific antihypertensive drug treatment; (IV) plasma triglycerides ≥1.70 mmol/L [150 mg/dL] OR lipid-lowering treatment; (V) plasma HDL-C ≤ 1.0 mmol/L [40 mg/dL] (male) or ≤ 1.3 mmol/L [50 mg/dL] (female) OR lipid-lowering treatment.
Definition of hyperlipidemia
Hyperlipidemia was defined when ≥1 of the following fasting venous plasma test indicators was met: total cholesterol ≥5.2 mmol/L; low-density lipoprotein cholesterol ≥3.4 mmol/L; triglycerides ≥1.7 mmol/L; HDL-C < 1.0 mmol/L for males and <1.3 mmol/L for females, termed lower HDL-C in the following analyses.10
Ascertainment of MASLD population and extrahepatic cancers
The accuracy of diagnosis was evaluated by experienced clinicians. First, individuals diagnosed with “hepatic steatosis” were extracted from the database using ICD-10 codes with keywords (in Chinese), excluding other etiologies of hepatic steatosis. The ICD-10 codes and keywords (in Chinese) used to identify patients with MASLD are illustrated in Supplementary Table 1. Screening and appraisal to identify and extract individuals who met the MASLD diagnostic criteria were performed. According to real-world clinical practice, MASLD cardiometabolic criterion (IV) included the diagnosis of hyperlipidemia. The absence of BMI and waist circumference data (criterion I) in our database meant that these two criteria were not utilized. As primary or secondary tumors were uncertain, in subsequent logistic analyses, populations with extrahepatic cancers who were identified as having hepatic tumors were excluded, along with the non-cancer population as their counterparts.
Subgroups
In logistic regression analyses, metabolic dysfunctions were classified as follows: hypertension, including diagnosed hypertension and use of antihypertensive agents; abnormal lipid metabolism, including plasma triglycerides ≥ 1.70 mmol/L, diagnosed hyperlipidemia, lower HDL-C, and use of lipid-lowering treatment; hyperglycemia and pre-diabetes, defined as fasting blood glucose 5.6–6.9 mmol/L, HbA1c 5.7–6.4%, 2-h post-meal blood glucose 7.8–11.0 mmol/L; and T2DM and treatment for T2DM. In metabolic dysfunction subgroup analyses, groups included the hypertension group (diagnosed hypertension and use of antihypertensive agents), abnormal lipid metabolism group (plasma triglycerides ≥ 1.70 mmol/L, diagnosed hyperlipidemia, lower HDL-C, and lipid-lowering treatment), and T2DM group (diagnosed T2DM and treatment for T2DM). Ascertainment of pharmacological treatments for metabolic dysfunctions and comorbidities was shown in the supplementary materials (Supplementary Table 2).
Fibrosis assessment
The fibrosis-4 (FIB-4) score11,12 was calculated using the established equation incorporating age, aspartate aminotransferase level, alanine aminotransferase level, and platelet count. In individuals aged 35 to 64 years,13 a FIB-4 score <1.3 (F0–F1) was considered low risk for advanced fibrosis, while a score ranging from 1.3 to 2.67 (F2) indicated intermediate risk and required further evaluation through liver stiffness measurement via elastography, liver function tests, or other methods. A score exceeding 2.67 and 3.4814 was classified as high risk for advanced fibrosis (F3–F4) and cirrhosis, which was linked to an increased risk of adverse liver outcomes. For those those aged ≥ 65 years old, the FIB-4 cutoff was raised to 2.13 Stratified age analyses and adjusted odds ratios (aORs) were used to demonstrate the association between liver fibrosis assessed by FIB-4 score and extrahepatic cancers in the MASLD population.
Statistical analysis
SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) was used for statistical analysis, with p < 0.05 considered statistically significant. Continuous variables were expressed as mean ± standard deviation; skewed distributions were presented as median and interquartile range (Q1, Q3) and analyzed using the Wilcoxon test or Kruskal–Wallis test. Univariate and multivariate logistic regression analyses were conducted to evaluate risk factors for extrahepatic cancers, with odds ratios (ORs), aORs, and 95% confidence intervals (95% CIs) calculated. Covariates were identified according to clinical importance and statistical significance. Considering clinical impact and statistical results from univariate logistic analyses, multivariate logistic regression analyses were performed. A product term (Hypertension*Hyperglycemia) was included in the model to explore their interaction effect on the risk of extrahepatic cancers. Forest plots were generated using R version 4.4.2.
Results
Demographic and baseline characteristics of patients with MASLD and extrahepatic cancers
A total of 103,652 patients with MASLD were included in this study (Fig. 1). Among them, 6,605 individuals with MASLD and extrahepatic cancers were identified, including 3,243 females (49.10%). The mean age was 58.61 ± 12.49 years. Dyslipidemia was the most prevalent condition, observed in 4,275 patients (64.72%). The combination of cardiometabolic risk factors and other baseline clinical characteristics, including comorbidities and metabolism-based treatments, is presented in Table 1. Overall, lung cancer, thyroid cancer, and breast cancer were identified as the top three extrahepatic malignancies. Gender differences in site-specific extrahepatic cancers were also reported in detail. There was no difference in incidence between genders (Fig. 2, Supplementary Table 3).
Table 1Baseline characteristics of MASLD with extrahepatic cancers
| MASLD (%) | Non cancer (%) | Extrahepatic cancers (%) | p |
|---|
| Total | 103,652 | 93,065 | 6,605 | |
| Male | 67,421 (65.05) | 61,597 (66.19) | 3,362 (50.90) | <0.001 |
| Female | 36,231 (34.95) | 31,468 (33.81) | 3,243 (49.10) | <0.001 |
| Age, year | | | | |
| <30 | 6,084 (5.87) | 5,913 (6.35) | 105 (1.59) | <0.001 |
| 30–39 | 16,491 (15.91) | 15,808 (16.99) | 380 (5.75) | <0.001 |
| 40–49 | 21,768 (21.00) | 20,226 (21.73) | 913 (13.82) | <0.001 |
| 50–59 | 29,683 (28.64) | 26,342 (28.30) | 2,147 (32.51) | <0.001 |
| 60–69 | 18,458 (17.81) | 15,574 (16.73) | 1,839 (27.84) | <0.001 |
| ≥70 | 11,168 (10.77) | 9,202 (9.89) | 1,221 (18.49) | <0.001 |
| Cardiometabolic factors | | | | |
| Hypertension | 43,717 (42.18) | 38,539 (41.41) | 3,271 (49.52) | <0.001 |
| Blood pressure ≥ 130/85 mmHg | 41,254 (39.80) | 36,411 (39.12) | 3,034 (45.93) | <0.001 |
| Utility of antihypertensive drug | 24,219 (23.37) | 21,970 (23.61) | 1,183 (17.91) | <0.001 |
| Dyslipidemia | 84,488 (81.51) | 77,299 (83.06) | 4,275 (64.72) | <0.001 |
| Diagnosis of hyperlipidemia | 41,735 (40.26) | 38,843 (41.74) | 1,666 (25.22) | <0.001 |
| Triglycerides ≥ 1.7 mmol/L | 46,757 (45.11) | 43,005 (46.21) | 2,401 (36.35) | <0.001 |
| Lower HDL-C | 41,885 (40.41) | 37,689 (40.50) | 2,568 (38.88) | <0.001 |
| LDL-C ≥ 3.4 mmol/L | 22,451 (21.66) | 20,687 (22.23) | 1,143 (17.31) | <0.001 |
| Total cholesterol ≥ 5.2 mmol/L | 26,449 (25.52) | 24,338 (26.15) | 1,420 (21.50) | <0.001 |
| Utility of lipid-lowering agent | 24,417 (23.56) | 22,577 (24.26) | 738 (11.17) | <0.001 |
| Hyperglycemia | 48,346 (46.64) | 42,962 (46.16) | 3,237 (49.01) | <0.001 |
| Type 2 diabetes mellitus | 39,003 (37.63) | 34,409 (36.97) | 2,691 (40.74) | <0.001 |
| Fasting blood-glucose 5.6–6.9 mmol/L | 9,368 (9.04) | 8,420 (9.05) | 629 (9.52) | <0.001 |
| HbA1c 5.7–6.4% | 13,645 (13.16) | 12,402 (13.33) | 810 (12.26) | <0.001 |
| 2-h post-meal blood glucose 7.8–11.0 mmol/L | 998 (0.96) | 936 (1.01) | 38 (0.58) | <0.001 |
| Utility of hypoglycemic agent | 20,134 (19.42) | 18,511 (19.89) | 903 (13.67) | <0.001 |
| Other related indicators | | | | <0.001 |
| HOMA-IR ≥ 2.5 | 987 (0.95) | 954 (1.03) | 13 (0.20) | <0.001 |
| hs-CRP over 2 mg/L | 10,456 (10.09) | 8,793 (9.45) | 1,281 (19.39) | <0.001 |
| Combination of cardiometabolic risk factors | | | | |
| Hypertension and abnormal lipid metabolism | 35,863 (34.60) | 29,934 (32.16) | 1,760 (26.65) | <0.001 |
| Hypertension and hyperglycemia | 23,617 (22.78) | 20,948 (22.51) | 1,570 (23.77) | <0.001 |
| Abnormal lipid metabolism and hyperglycemia | 35,863 (34.60) | 32,621 (35.05) | 1,857 (28.12) | <0.001 |
| Hypertension, abnormal lipid metabolism, and hyperglycemia | 15,152 (14.62) | 13,683 (14.70) | 1,009 (15.28) | <0.001 |
| Liver function | | | | |
| AST > 40 U/L | 16,296 (15.72) | 14,370 (15.44) | 1,097 (16.61) | <0.001 |
| AST > 80 U/L | 4,830 (4.66) | 4,096 (4.40) | 333 (5.04) | <0.001 |
| ALT > 40 U/L | 27,909 (26.93) | 25,242 (27.12) | 1,608 (24.35) | <0.001 |
| ALT > 80 U/L | 9,713 (9.37) | 8,720 (9.37) | 522 (7.90) | <0.001 |
| Fibrosis-4 index | | | | |
| Age 35–64 | | | | |
| FIB-4 < 1.3 | 30,071 (29.01) | 27,454 (29.50) | 1,789 (27.09) | <0.001 |
| FIB-4 1.3–2.66 | 13,498 (13.02) | 11,776 (12.65) | 1,175 (17.79) | <0.001 |
| FIB-4 2.67–3.47 | 1,289 (1.24) | 1,074 (1.15) | 130 (1.97) | <0.001 |
| FIB-4 ≥ 3.48 | 2,483 (2.40) | 1,941 (2.09) | 267 (4.04) | <0.001 |
| Age ≥ 65 | | | | |
| FIB-4 < 2 | 8,630 (8.33) | 7,301 (7.85) | 934 (14.14) | <0.001 |
| FIB-4 ≥ 2 | 6,930 (6.69) | 5,446 (5.85) | 955 (14.46) | <0.001 |
| Comorbidities | | | | |
| Cardiovascular disease | 48,261 (46.56) | 42,649 (45.83) | 3,445 (52.16) | <0.001 |
| Abnormal liver function | 10,849 (10.47) | 9,986 (10.73) | 509 (7.71) | <0.001 |
| Viral hepatitis | 9,759 (9.42) | 8,948 (9.61) | 233 (3.53) | <0.001 |
| Cirrhosis | 2,061 (1.99) | 1,602 (1.72) | 50 (0.76) | <0.001 |
| Chronic kidney disease | 7,646 (7.38) | 7,132 (7.66) | 258 (3.91) | <0.001 |
| Osteoporosis | 4,603 (4.44) | 4,098 (4.40) | 307 (4.65) | <0.001 |
| Hypothyroidism | 3,025 (2.92) | 2,598 (2.79) | 302 (4.57) | <0.001 |
| Obstructive sleep apnea | 1,557 (1.50) | 1,480 (1.59) | 41 (0.62) | <0.001 |
| Polycystic ovarian syndrome | 325 (0.31) | 313 (0.34) | 6 (0.09) | <0.001 |
| Hp. Infection | 1,888 (1.82) | 1,695 (1.82) | 83 (1.26) | <0.001 |
| Autoimmune hepatitis | 304 (0.29) | 285 (0.31) | 7 (0.11) | <0.001 |
| Chronic obstructive pulmonary disease | 1,008 (0.97) | 771 (0.83) | 134 (2.03) | <0.001 |
| Metabolic-based treatments | | | | |
| Hyperglycemia | | | | |
| Insulin (aspart insulin and glargine insulin) | 5,133 (4.95) | 4,732 (5.08) | 226 (3.42) | <0.001 |
| Biguanides (metformin) | 9,173 (8.85) | 8,447 (9.08) | 404 (6.12) | <0.001 |
| SGLT-2 inhibitors | 2,786 (2.69) | 2,605 (2.80) | 87 (1.32) | <0.001 |
| GLP-1 receptor agonists | 1,177 (1.14) | 1,122 (1.21) | 28 (0.42) | <0.001 |
| DPP-4 inhibitors | 2,433 (2.35) | 2,224 (2.39) | 101 (1.53) | <0.001 |
| Thiazolidinediones | 630 (0.61) | 601 (0.65) | 13 (0.20) | <0.001 |
| Dyslipidemia | | | | |
| Statins | 12,980 (12.52) | 11,905 (12.79) | 442 (6.69) | <0.001 |
| Fibrates | 2,575 (2.48) | 2,459 (2.64) | 47 (0.71) | <0.001 |
| Cholesterol absorption inhibitors (ezetimibe) | 1,326 (1.28) | 1,209 (1.30) | 37 (0.56) | <0.001 |
| Hypertension | | | | |
| Calcium channel blockers | 12,561 (12.12) | 11,321 (12.16) | 705 (10.67) | <0.001 |
| ACEIs/ARBs | 11,795 (11.38) | 10,843 (11.65) | 451 (6.83) | <0.001 |
| Beta-blockers | 7,635 (7.37) | 6,974 (7.43) | 282 (4.27) | <0.001 |
Hypertension associated with extrahepatic cancers in the MASLD population
To exclude selection bias and metastatic hepatic tumors, patients with both extrahepatic cancers and hepatic tumors were excluded, and the non-cancer population was included as counterparts in the logistic analysis. Finally, 6,499 patients with extrahepatic cancers and 93,065 non-cancer MASLD individuals were included. Univariate logistic analysis indicated that aging, female gender, and cardiometabolic risk factors were significantly associated with extrahepatic cancers (Supplementary Table 4). Considering the interaction of risk factors, multivariate logistic regression analysis was performed.
Hypertension was significantly associated with the risk of extrahepatic cancers in the MASLD population (OR 1.15, 95% CI: 1.04–1.26, p = 0.044). As for age, compared with individuals under 30 years old, those aged 30–39 (OR 1.46, 95% CI: 1.17–1.82, p < 0.001), 40–49 (OR 2.75, 95% CI:2.23–3.39, p < 0.001), 50–59 (OR 4.58, 95% CI: 3.74–5.61, p < 0.001), 60–69 (OR 6.47, 95% CI: 5.27–7.95, p < 0.001), and over 70 years (OR 7.47, 95% CI: 6.05–9.22, p < 0.001) had a higher likelihood of comorbidity with extrahepatic cancers, as shown in Figure 3. In 10-year age stratifications, hypertension was associated with extrahepatic cancers in the 40–49 and 50–59 age groups without statistical significance, likely due to the low incidence of events in these subgroups. Subsequently, hypertension was significantly associated with extrahepatic cancers in patients aged ≥40 years (OR 1.19, 95% CI: 1.13–1.25, p < 0.001), as shown in Supplementary Figure 1. Additionally, female gender (OR 1.41, 95% CI: 1.33–1.48, p < 0.001), aspartate aminotransferase (OR 1.25, 95% CI: 1.14–1.38, p < 0.001), and alanine aminotransferase (OR 1.19, 95% CI: 1.09–1.29, p < 0.001) levels over 40 U/L were associated with a higher risk of extrahepatic cancers (Fig. 3). Furthermore, the combination of hypertension and hyperglycemia (OR 1.36, 95% CI: 1.22–1.51, p < 0.001) was significantly associated with the risk of extrahepatic cancers in patients with MASLD (Fig. 4). Potential effect modification was assessed by including an interaction term (Hypertension*Hyperglycemia) in the same regression model shown in Figure 3. This term was associated with extrahepatic cancers (OR 1.09, 95% CI: 0.98–1.22, p = 0.116) but did not reach statistical significance, indicating that the interaction effect was insignificant. Specifically, as shown in Supplementary Figure 2, diagnosed hypertension (OR 1.14, 95% CI: 1.08–1.21, p < 0.001) and T2DM (OR 1.19, 95% CI: 1.12–1.26, p < 0.001) were identified as risk factors for extrahepatic cancers.
Pharmacological treatments of hypertension showed a protective impact on extrahepatic cancers in the MASLD population
Pharmacological treatments were identified as protective factors, as shown in Supplementary Figures 2–4. To determine which categories of agents conferred protection against extrahepatic cancers, subgroup analyses were conducted among those with hypertension, abnormal lipid metabolism, and T2DM.
After adjustment for confounding factors (Supplementary Tables 5–7), all forms of agents acted as protective factors in univariate analyses. In multivariate analyses (Supplementary Table 8), angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers (hereinafter referred to as ACEIs/ARBs) (aOR 0.68, 95% CI: 0.61–0.77, p < 0.001) and beta-blockers (aOR 0.78, 95% CI: 0.68–0.91, p = 0.001) were protective factors. For lipid-modifying agents, fibrates demonstrated the strongest protective effect (aOR 0.47, 95% CI: 0.35–0.62, p < 0.001), while statins (aOR 0.65, 95% CI: 0.58–0.72, p < 0.001) and cholesterol absorption inhibitors (aOR 0.69, 95% CI: 0.49–0.96, p = 0.026) also exhibited protective effects. In the T2DM subgroup, glucagon-like peptide-1 receptor agonists (hereinafter referred to as GLP-1 RAs) (aOR 0.52, 95% CI: 0.35–0.76, p < 0.001) and thiazolidinediones (aOR 0.45, 95% CI: 0.26–0.79, p = 0.005) showed the strongest protective effects despite lower usage rates. Insulin, sodium–glucose cotransporter-2 inhibitors, and dipeptidyl peptidase-4 inhibitors exhibited similar protective patterns. Metformin, although the most commonly used agent, was only associated with a 16% reduction in risk (p = 0.005).
FIB-4 index associated with extrahepatic cancers in the MASLD population
After adjustment for confounding factors (Supplementary Tables 5–7), multivariate logistic regression analysis was conducted (Table 2). Among individuals aged 35 to 64 years, compared with those with FIB-4 < 1.3, those with FIB-4 ≥ 1.3 showed a higher likelihood of developing extrahepatic cancers. The risk increased across FIB-4 categories of 1.3–2.66 (aOR 1.37, 95% CI: 1.26–1.48, p < 0.001), 2.67–3.47 (aOR 1.50, 95% CI: 1.23–1.82, p < 0.001), and ≥3.48 (aOR 1.62, 95% CI: 1.40–1.87, p < 0.001), respectively. However, when compared with the FIB-4 1.3–2.66 category, only FIB-4 < 1.3 acted as a significant protective factor. Across all subgroups, patients with FIB-4 ≥ 1.3 were identified as having a higher likelihood of developing extrahepatic cancers. Specifically, in the hypertension subgroup, individuals aged 35–64 years with FIB-4 values of 1.3–2.66, 2.67–3.47, and ≥3.48 had 47%, 40%, and 73% higher likelihoods of developing extrahepatic cancers, respectively, compared with those with FIB-4 < 1.3; similar patterns were observed in the T2DM subgroup (50%, 46%, and 90%). In the abnormal lipid metabolism subgroup, individuals aged 35–64 years with FIB-4 values of 2.67–3.47 and ≥3.48 exhibited more than a two-fold increased likelihood. Among individuals older than 65 years, all those with FIB-4 ≥ 2 showed a higher likelihood of developing extrahepatic cancers.
Table 2The association of FIB-4 and extrahepatic carcinoma in the MASLD population
| Extrahepatic cancer | Non cancer | aOR (95% CI) | aOR (95% CI) |
|---|
| All MASLD | | | | |
| Age from 35 to 64 | | | | |
| FIB-4 < 1.3 | 1,765 | 27,454 | 1.00 | 0.73 (0.68,0.79)** |
| FIB-4 1.3–2.66 | 1,155 | 11,776 | 1.37 (1.26,1.48)** | 1.00 |
| FIB-4 2.67–3.47 | 125 | 1,074 | 1.50 (1.23,1.82)** | 1.10 (0.90,1.34) |
| FIB-4 ≥ 3.48 | 261 | 1,941 | 1.62 (1.40,1.87)** | 1.18 (1.02,1.37)* |
| Age ≥ 65 | | | | |
| FIB-4 < 2 | 922 | 7,301 | 1.00 | |
| FIB-4 ≥ 2 | 932 | 5,446 | 1.22 (1.10,1.35)** | |
| Hypertension subgroup | | | |
| Age from 35 to 64 | | | | |
| FIB-4 < 1.3 | 735 | 11,157 | 1.00 | 0.68 (0.60,0.77)** |
| FIB-4 1.3–2.66 | 529 | 5,126 | 1.47 (1.30,1.65)** | 1.00 |
| FIB-4 2.67–3.47 | 49 | 469 | 1.40 (1.02,1.92)* | 0.95 (0.69,1.31) |
| FIB-4 ≥ 3.48 | 91 | 716 | 1.73 (1.35,2.21)** | 1.78 (0.92,1.52) |
| Age ≥ 65 | | | | |
| FIB-4 < 2 | 599 | 5,088 | 1.00 | |
| FIB-4 ≥ 2 | 595 | 3,764 | 1.25 (1.10,1.42)** | |
| Abnormal lipid metabolism subgroup | | |
| Age from 35 to 64 | | | | |
| FIB-4 < 1.3 | 1,240 | 23,888 | 1.00 | 0.71 (0.64,0.78)** |
| FIB-4 1.3–2.66 | 737 | 9,936 | 1.42 (1.29,1.56)** | 1.00 |
| FIB-4 2.67–3.47 | 87 | 874 | 2.04 (1.61,2.58)** | 1.44 (1.13,1.83)* |
| FIB-4 ≥ 3.48 | 171 | 1,591 | 2.29 (1.91,2.74)** | 1.61 (1.34,1.94)** |
| Age ≥ 65 | | | | |
| FIB-4 < 2 | 582 | 6,333 | 1.00 | |
| FIB-4 ≥ 2 | 598 | 4,587 | 1.41 (1.25,1.60)** | |
| T2DM subgroup | | | | |
| Age from 35 to 64 | | | | |
| FIB-4 < 1.3 | 572 | 9,248 | 1.00 | 0.67 (0.59,0.76)** |
| FIB-4 1.3–2.66 | 454 | 4,672 | 1.50 (1.31,1.71)** | 1.00 |
| FIB-4 2.67–3.47 | 51 | 491 | 1.46 (1.07,1.99)* | 0.97 (0.71,1.33) |
| FIB-4 ≥ 3.48 | 131 | 969 | 1.90 (1.53,2.35)** | 1.27 (1.02,1.58)* |
| Age ≥ 65 | | | | |
| FIB-4 < 2 | 434 | 3,748 | 1.00 | |
| FIB-4 ≥ 2 | 440 | 2,726 | 1.28 (1.10,1.48)* | |
Discussion
This multicenter cross-sectional study, encompassing a population of 103,652 Chinese individuals with MASLD, found that the incidence of all extrahepatic cancers was higher than that reported by the National Cancer Center of China.15 In the current study, we found that hypertension was independently associated with a modest but significantly higher likelihood of extrahepatic cancers (OR 1.15, 95% CI: 1.04–1.26), with the risk further increased when hypertension coexisted with hyperglycemia (OR 1.36, 95% CI: 1.22–1.51). Meanwhile, several metabolism-targeted medications (ACEIs/ARBs, fibrates, GLP-1 RAs, and thiazolidinediones) might have exhibited robust protective associations against extrahepatic cancers. In stratified analyses by 10-year age groups, hypertension remained a significant risk factor in all strata above 30 years of age, and this association persisted across gender, hyperglycemia, abnormal lipid metabolism, and all FIB-4 subgroups. Our results added new data to a recent study showing that hypertension was associated with increased risks of all-cause mortality, cardiovascular events, progression of liver stiffness or fibrosis, and liver-related events in patients with MASLD.16Although extrahepatic cancers represent the first or second leading cause of death in this population,6,17 evidence linking hypertension to specific cancer types has been limited. Prior studies have suggested elevated risks of thyroid, esophageal, colorectal, liver, renal cell, breast (in women), and endometrial cancers in individuals with hypertension.8,18–21 Several plausible biological pathways may underlie these associations. First, androgens contribute to both hypertension and prostate cancer through shared mechanisms involving the renin–angiotensin system and enhanced sodium reabsorption.22 Second, dysregulation of vascular endothelial growth factor establishes a bidirectional link, whereby elevated vascular endothelial growth factor levels in hypertensive patients promote tumor angiogenesis.8,23 Additionally, chronic inflammation and oxidative stress—common to both conditions—drive endothelial dysfunction, sympathetic overactivity, and pro-proliferative signaling pathways.8 Further mechanistic studies are warranted to elucidate these relationships. Our findings underscore the importance of rigorous hypertension screening and management in patients with MASLD, as effective control may potentially reduce adverse outcomes, including extrahepatic cancers. These results provide insights for future research and clinical practice, particularly the need to further establish the causal association between hypertension and extrahepatic cancers in patients with MASLD, and to evaluate the potential benefits of targeted hypertension management and enhanced extrahepatic cancer screening in specific subgroups, such as those stratified by age or severity of hypertension. Additionally, the combination of hypertension and hyperglycemia was identified as a risk factor associated with extrahepatic cancers without a significant interaction effect in this study. A previous study has demonstrated that the clustering of two or more cardiometabolic risk factors markedly heightens malignancy risk.24 These findings further suggest that, on the basis of the established association between hypertension and extrahepatic cancers, concomitant hyperglycemia may confer additional risk, highlighting the importance of targeting this specific cardiometabolic combination in patients with MASLD.
To further confirm the association between hypertension and extrahepatic cancers and to elucidate the role of cardiometabolic factors in the context of liver disease, this study investigated these associations among patients with MASLD stratified by different FIB-4 thresholds. Such stratification may reveal whether advanced liver fibrosis modifies the hypertension-related risk of extrahepatic cancers.
Our results demonstrated that the association between hypertension and extrahepatic cancers was observed in patients with FIB-4 scores ≥ 1.3 in the 35–64-year age group and ≥2.0 in those aged ≥ 65 years, but not in patients with FIB-4 scores below these respective thresholds. Priority should therefore be given to individuals with FIB-4 scores ≥ 1.3 or ≥2.0. Interventions and screening strategies should not be limited to cardiology departments but should also be integrated into hepatology, endocrinology, and other relevant departments. A recent study reported that FIB-4 ≥ 2.67 conferred a 16% higher risk in adults with MASLD.25 Our findings further addressed the overlapping effect by demonstrating that the association was primarily observed in patients with higher FIB-4 scores. Other cardiometabolic risk factors warrant additional investigation to determine their independent or combined associations with extrahepatic cancers.
Our results also showed a sharp increase in ORs for extrahepatic cancers with advancing 10-year age strata among individuals over 40 years of age. Compared with a previous study on early-onset cancers in patients with MASLD,26 our findings suggest that extrahepatic cancer screening should be considered even earlier in individuals with MASLD, particularly those with concomitant hypertension. Additionally, women exhibited a 44% higher cancer risk than men in this study, consistent with previous reports of advanced fibrosis and malignancy risk in female patients with MASLD.27,28 Although women tend to be more active in cancer screening programs, these findings simultaneously suggest that men with MASLD and hypertension may warrant particular attention for enhanced extrahepatic cancer screening to address potential disparities in detection and outcomes.
Several limitations merit acknowledgment. First, MASLD was identified using ICD-10 codes; although the diagnosis of fatty liver disease was based on imaging, clinical, or pathological records confirmed by physicians, specific diagnostic modalities were unavailable. Second, data on obesity, overweight status, and alcohol consumption were lacking, precluding adjustment for these confounders. Further studies focusing on obesity and alcohol intake are required; notably, MASLD, rather than obesity, has been shown to be independently associated with malignancy.29 Third, FIB-4 was the only noninvasive liver fibrosis score evaluated. As previous studies have indicated that FIB-4 may underestimate the degree of liver fibrosis in these populations,13 future studies are needed to validate our findings using additional fibrosis scoring systems. Fourth, socioeconomic and educational data were unavailable due to the inherent limitations of hospital records; prior studies have linked lower socioeconomic and educational status to accelerated fibrosis progression and major liver outcomes, including hepatocellular carcinoma.30
The strengths of our study include the demonstration of an association between hypertension and extrahepatic cancers in patients with MASLD using a multicenter, large-scale MASLD cohort. We provide robust evidence that hypertension—alone and in combination with hyperglycemia—is significantly associated with extrahepatic cancers, a finding rarely reported for specific cardiometabolic clusters. Subgroup analyses further highlight the protective potential of metabolism-targeted therapies and the utility of FIB-4 and age stratifications as simple tools for cancer risk stratification in this population.
Conclusions
A total of 6,605 individuals with extrahepatic cancers were identified from a population of 103,652 patients with MASLD. Hypertension and the combination of hypertension and hyperglycemia were significantly associated with extrahepatic cancers. This association was further supported by the finding that metabolism-based treatments might be significantly linked to a protective role in the MASLD population. The association was observed in individuals with FIB-4 scores ≥ 1.3 among those aged 35 to 65 years and ≥2.0 among those aged over 65 years. Individuals with MASLD over 40 years of age may be recommended for extrahepatic cancer screening, especially those with hypertension and FIB-4 scores ≥ 1.3.
Supporting information
Supplementary Table 1
ICD-10 codes and keywords for cardiometabolic factors, comorbidities and cancers.
(DOCX)
Supplementary Table 2
Anti-metabolic dysfunction agents.
(DOCX)
Supplementary Table 3
Gender difference of site-specific extrahepatic cancers in MASLD population.
(DOCX)
Supplementary Table 4
MASLD with extrahepatic cancers risk factors. Univariate logistic regression analysis.
(DOCX)
Supplementary Table 5
Hypertension subgroup the risk factors of extrahepatic cancers. Univariate logistic regression analyses.
(DOCX)
Supplementary Table 6
Abnormal lipid metabolism subgroup the risk factors of extrahepatic cancers.
Univariate logistic regression analyses.
(DOCX)
Supplementary Table 7
T2DM subgroup the risk factors of extrahepatic cancers.
Univariate logistic regression analyses.
(DOCX)
Supplementary Table 8
The association of using specific anti-metabolic dysfunction agents and extrahepatic cancers in MASLD population
(DOCX)
Supplementary Figure 1
The association of hypertension and extrahepatic cancers in age stratification subgroups analysis.
(DOCX)
Supplementary Figure 2
The association of diagnosed specific metabolic dysfunction, elevated liver enzyme, pharmacological treatments of the metabolic dysfunction, comorbidities and extrahepatic cancers in the MASLD population.
(DOCX)
Supplementary Figure 3
The association of diagnosed specific dyslipidemia, elevated liver enzyme, pharmacological treatments of the metabolic dysfunction, comorbidities and extrahepatic cancers in the MASLD population.
(DOCX)
Supplementary Figure 4
The association of comorbidities and extrahepatic cancers in the MASLD population.
(DOCX)
Declarations
Acknowledgement
The authors thank Shuangqing Gao, Haiyun Ding, Shanshan Wang, Feng Xue, Huiying Rao, Fanpu Ji, Jidong Jia, Xiong Ma, Peng Hu, Xiaoguang Dou, and Keshu Xu for data access and statistical analysis. Critical reviewing was conducted by Lai Wei, Ming Yang, Dong Li, Shuangqing Gao, Huiying Rao, Fanpu Ji, Jidong Jia, Xiong Ma, Peng Hu, Xiaoguang Dou, and Keshu Xu for scientific content.
Ethical statement
This study was reviewed and approved by the Beijing Tsinghua Changgung Hospital Ethics Committee, which waived the need for informed consent since the study only used deidentified databases (ID for ethics approval: 25469-0-01), and was conducted in accordance with the Declaration of Helsinki (as revised in 2024). We adhered to all recommendations and requirements set forth by the board.
Data sharing statement
The data were used under license for the current study and are therefore not publicly available.
Funding
XZ, FX, and LW are supported by the National Key R&D Program of China, “Exploration and Clinical Validation of Host–Gut Microbiota Co-metabolic Molecular Markers for MAFLD” (Programme code 2022YFA1303800), and “Host–Gut Microbiota Co-metabolic Mechanisms and Target Discovery in MAFLD” (Project code 2022YFA1303804). MY is supported by the Chief Scientist Research Project of Hubei Shizhen Laboratory (code HSL2024SX0001). The other authors have not declared a specific grant for this research from any funding agency in the public, commercial, or not-for-profit sectors.
Conflict of interest
LW consults for Hiskynedical, BI, Gilead, Kaiyin, MSD, Novo Nordisk, Pfizer, Roche, and VirsiRNA; is a speaker for GSK, Novo Nordisk, and Sanofi; and receives research grants from Amoytop, AZ, Gilead, GSK, Kaiyin, Pfizer, and Sanofi, but has nothing to declare for this manuscript. PH has been an Editor-in-Chief of Journal of Clinical and Translational Hepatology since 2026. LW and JJ have been Executive Associate Editors of Journal of Clinical and Translational Hepatology since 2013. XD has been an Associate Editor of Journal of Clinical and Translational Hepatology since 2013. HR and FJ have been Editorial Board Members of Journal of Clinical and Translational Hepatology since 2023. The other authors have no conflict of interests related to this publication.
Authors’ contributions
Study concept and design (XZ, LW), data acquisition (HD, SW, SG, FX, FJ, JJ, HR, XM, PH, XD, KX), data analysis (HD, SW, XZ), draft of the manuscript (XZ, LW), data interpretation, critical review and revision of manuscript (LW, MY, SG, DL, FJ, JJ, HR, XM, PH, XD, KX), and study supervision (LW). All authors participated in the preparation of the manuscript and have seen and approved the final version.