Comparative study of early onset cancer burden between China and the United States from 1990 to 2021.

Текст сохранён. Часть иллюстраций пока доступна только в первоисточнике; загрузка будет проверена повторно.

Introduction

Cancer has become one of the leading causes of death globally 1 . In recent years, the incidence of early-onset cancer (defined as the occurrence of new cases in individuals under 50 years of age) has been increasing globally 2 , reflecting a concerning trend toward younger populations being affected by the disease. The increasing incidence of early-onset cancer exacerbates the burden on health insurance systems and families, with young patients facing not only the physical pain of the disease but also substantial diagnostic, treatment, and rehabilitation costs. This places tremendous pressure on individuals, families, healthcare organizations, and society 3 – 5 . Compared with previous generations, young people—the backbone of future society—face pressure from all aspects of life. They are deeply affected by unhealthy lifestyles such as tobacco 6 , alcohol consumption 7 and drug use 8 , along with environmental factors like air pollution 9 , These factors accelerate the decline in young people’s health, potentially leading to cancer, and they often face significant challenges in early diagnosis, treatment, and access to healthcare 10 . Therefore, implementing active cancer prevention and control policies, strengthening epidemiologic research and screening, launching campaigns to raise awareness among young people about their health, and adopting other health management strategies are essential to reducing the disease burden.

The burden of early-onset cancer is unevenly distributed between developed and developing countries 11 . As the world’s largest developing country, China’s cancer spectrum is transitioning from that typical of a developing nation to one more akin to developed nations 12 . The country’s large population and shifting lifestyles have intensified the challenges of preventing and controlling early-onset cancers. Changes in incidence and mortality rates, as well as long-term trends in cancer burden, reflect shifts in behavioral patterns and medical practices associated with disease risk 13 . The successful experiences and practical achievements of the United States (US) in cancer research, prevention, and care serve as important references for developing countries, such as China. By comparing the early-onset cancer profiles, trends, and risk factors between China and the US, our study provides important insights for early-onset cancer prevention and policy development in China 14 .

Existing studies have primarily focused on one or more cancer types within a single country 15 – 18 , or have compared differences in specific cancers across countries 19 – 22 . However, comparative studies on early-onset cancers and the cancer burden in China and the US are lacking. Therefore, based on data from the Global Burden of Disease Study 2021, which systematically integrates disease data from 204 countries and territories between 1990 and 2021, this study aims to comprehensively analyze the trends in 33 early-onset cancers burden among populations aged 15–49 years in China and the United States. By examining incidence, mortality, and disability-adjusted life years (DALYs), we aim to enhance the understanding of the burden of disease in China and the US. These findings are expected to provide scientific evidence for policymaking and ultimately contribute to improving population health and life quality.

Methods

Study data

We obtained data on the incidence, mortality, and DALYs for early-onset cancers (diagnosed in individuals aged 15–49) in China and the US from the 2021 Global Burden of Disease database (GBD 2021, https://ghdx.healthdata.org/gbd-2021 ), covering the years 1990 to 2021. The GBD 2021 was developed by the Institute for Health Metrics and Evaluation at the University of Washington, employing cause aggregation models, spatiotemporal Gaussian regression models, and Bayesian regression tools, such as DisMod-MR2.1. It evaluates disease burden indicators for 371 diseases and injuries in 204 countries and regions worldwide from 1990 to 2021, quantifying the impact of diseases, injuries, and risk factors on health both globally and regionally 23 – 25 . GBD integrates data from multiple sources and applies DisMod-MR 2.1 to correct for data biases. Specifically: GBD conducts 500 random draws per parameter using Monte Carlo simulation to model possible value ranges. This approach retains and propagates uncertainty from measurement error, modeling assumptions, and regional variation. Final estimates are presented with 95% uncertainty intervals, derived from the 2.5th and 97.5th percentiles of the simulated draws.

The GBD 2021 utilizes the International Classification of Diseases, 10th Revision (ICD-10), for disease coding. In our study, 33 early-onset cancers were identified (Table 1 ). The database divides risk factor data into four levels, from the broader first level (including environmental, behavioral, and metabolic risk factors) to the more specific fourth level (including 22 factors, such as occupational insomnia exposure). Based on the World Cancer Research Fund’s guidelines 26 , this study incorporated 11 secondary attributable risk factors, namely: high fasting plasma glucose (HFPG), high body mass index (BMI), drug use, high alcohol consumption, low physical activity, dietary risks, tobacco use, unsafe sex, other environmental risks, occupational risks, and air pollution.

Table 1 ICD-10 codes for 33 early-onset cancers. Cancer name ICD10 Esophageal cancer C15-C15.9 Stomach cancer C16-C16.9 Liver cancer C22-C22.4, C22.7-C22.8 Larynx cancer C32-C32.9 Tracheal, bronchus, and lung cancer C33, C34-C34.92 Breast cancer C50-C50.629, C50.8-C50.929 Cervical cancer C53-C53.9 Uterine cancer C54-C54.3, C54.8-C54.9 Prostate cancer C61-C61.9 Colon and rectum cancer C18-C19.0, C20, C21-C21.8 Lip and oral cavity cancer C00-C07, C08-C08.9 Nasopharynx cancer C11-C11.9 Other pharynx cancer C09-C10.9, C12-C13.9 Gallbladder and biliary tract cancer C23, C24-C24.9 Pancreatic cancer C25-C25.9 Malignant skin melanoma C43-C43.9 Non-melanoma skin cancer C44.01-C44.99 Ovarian cancer C56-C56.2, C56.9 Testicular cancer C62-C62.92 Kidney cancer C64-C64.2, C64.9-C65.9 Bladder cancer C67-C67.9 Brain and central nervous system cancer C70-C70.1, C70.9-C72.9 Thyroid cancer C73 Mesothelioma C45-C45.2, C45.7, C45.9 Hodgkin lymphoma C81-C81.49, C81.7-C81.79, C81.9-C81.99 Non-Hodgkin lymphoma C82-C85.29, C85.7-C86.6, C96-C96.9 Multiple myeloma C88-C90.32 Leukemia C91-C93.7, C93.9-C95.2, C95.7-C95.92 Eye cancer C69-C69.92 Soft tissue and other extraosseous sarcomas C49-C49.9 Malignant neoplasm of bone and articular cartilage C40-C40.92, C41.0-C41.4, C41.8-C41.9 Neuroblastoma and other peripheral nervous cell tumors C47-C47.9 Other malignant neoplasms C17-C17.9, C30-C30.1, C31-C31.9, C37-C37.0, C38-C38.8, C41, C44-C44.00, C48-C48.9, C4A, C51-C52, C57-C57.8, C58-C58.0, C60-C60.9, C63-C63.8, C66-C66.9, C68.0-C68.8, C74-C75.5, C75.8

Definitions

Our research primarily analyzes three indicators—incidence, mortality, and DALYs—to quantify and describe the disease burden of early-onset cancers in China and the US 27 .

Incidence refers to the number of new cases of a specific disease occurring in a defined population over a specified period (typically one year), usually expressed as the number of new cases per thousand or per hundred thousand people. Incidence reflects the extent of disease transmission and risk within a specific population and aids in formulating public health policies and disease prevention strategies. The calculation formula is as follows: 1 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\begin{array}{c}Incidence\:Rate=\frac{{N}_{i}}{{T}_{i}\text{}}\times\:K \end{array}$$\end{document}

Where N i represents the number of new cases, T i represents the total population of the specified group, and is a constant, set to 100,000 in our research 28 .

Mortality refers to the proportion of individuals in a specific population who die from a particular disease within a designated period. Mortality is an indicator used to assess the level of economic development, allocation of medical resources, and the public health environment of a country or region. The calculation formula is as follows: 2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\begin{array}{c}Mortality\:Rate=\frac{{N}_{m}}{{T}_{m}\text{}}\times\:K \end{array}$$\end{document}

Where N m represents the number of deaths, T m represents the total population of the specified group during the same period, and is a constant, set to 100,000 in our research 29 .

DALYs refers to the total number of healthy years of life lost from the onset of the disease to death, including years of life lost due to premature death (YLLs) and years of healthy life lost due to disability (YLDs), i.e., DALYs = YLLs + YLDs, where YLL reflects years of life lost due to premature death and YLD measures the impact of disability on quality of life. DALYs take into account factors such as disease incidence, mortality, age at onset, duration, and disability weight, and are crucial indicators for assessing the disease burden, helping policymakers understand the overall impact of health issues, and guiding resource allocation and public health interventions. The formula for calculating the DALYs rate is as follows: 3 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\begin{array}{c}DALYs\:Rate=\frac{{N}_{d}}{{T}_{d}\text{}}\times\:K \end{array}$$\end{document}

Where N d represents the number of DALYs, Tm represents the total population of the specified group during the same period, and is a constant, set to 100,000 in our research 30 .

Statistics

Our research used the World Standard Population structure (World Health Organization, 2000–2025) as a reference to directly standardize the crude rate data obtained for the following age groups: 15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49 years, and calculated the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and age-standardized DALYs rate (per 100,000) 31 . All analyses were performed using R software version 4.4.1 (URL: https://www.r-project.org/ ) and Joinpoint trend analysis software version 5.2.0 (URL: https://surveillance.cancer.gov/joinpoint/ ). The formula for calculating the age-standardized rate (ASR) is as follows: 4 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\begin{array}{c}ASR=\frac{{\sum\:}_{i=1}^{A}{a}_{i}{w}_{i}}{{\sum\:}_{i=1}^{A}{w}_{i}}\times\:\text{100,000} \end{array}$$\end{document}

Where a i represents the crude rate for a specific age group, w represents the population size (or weight) of the corresponding age group in the standard population, and A represents the number of age groups.

The Joinpoint model is a statistical method used to analyze trend changes in time series data. The trend changes in ASIR, ASMR, and age-standardized DALYs rates for early-onset cancers in China and the US were evaluated using Annual Percentage Change (APC) and Average Annual Percentage Change (AAPC). The basic principle involves fitting the data using linear or logarithmic regression and describing trend changes by selecting the optimal number and position of the joinpoints. The model is typically fitted on a logarithmic scale to better account for the volatility and non-linear characteristics of the data 32 . The calculation formula for APC is: 5 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\begin{array}{c}APC\:\left(\%\right)=\left(\frac{{R}_{\left(t+1\right)}}{{R}_{t}}-1\right)\times\:100=\left({e}^{a}-1\right)\times\:100 \end{array}$$\end{document}

Where R t is the rate for year t, and α is the slope coefficient in the linear equation ln (R t ) = at + b. AAPC is calculated by the weighted average of the APC values, with the weights being the length of time for each APC segment. Finally, the Monte-Carlo permutation method is used to verify the statistical significance of the APC values for each trend segment and the overall AAPC value, with a significance level set at α = 0.05.

Results

Overall burden of early-onset cancers in 2021

In 2021, China reported 750,600 (64,090–886,100) new cases of early-onset cancers, with an ASIR of 94.91 (80.59–112.59) per 100,000. The total number of deaths was 240,800 (198,500–287,900), with an ASMR of 30.20 (24.85–36.10) per 100,000. The number of DALYs was 12,072,000 (9,969,100–14,411,800) person-years, with an age-standardized DALYs rate of 1,550.20 (1,278.92–1,850.54) per 100,000. In the US, 472,600 (432,800–516,700) new cases were reported, 30,600 deaths (29,700–31,400), and 1,607,900 (1,554,800–1,666,800) DALYs. The ASRs were 288.62 (255.47–328.39) per 100,000, 18.76 (18.19–19.33) per 100,000, and 994.81 (959.02–1,033.14) per 100,000, respectively (Tables 2 and 3 ).

In both China and the US, the three most common types of early-onset cancers in 2021 were breast cancer, non-melanoma skin cancer (NMSC), and colorectal cancer (CRC). In China, the number of new cases for these three cancers were 113,700 (85,700–146,300), 102,900 (77,800–131,600), and 78,700 (62,700–96,500), with ASIRs of 13.95 (10.41–18.18), 12.82 (8.50–18.48), and 9.83 (7.80–12.15) per 100,000, respectively. In the US, the numbers of new cases for these cancers were 40,900 (38,800–43,200), 295,900 (259,300–339,800), and 17,300 (16,700–17,900), with ASIRs of 24.84 (23.26–26.53), 179.48 (147.20–217.90), and 10.50 (10.01–11.01) per 100,000, respectively (Tables 2 and 3 ).

In China, the highest number of deaths from early-onset cancers was due to tracheal, bronchus, and lung (TBL) cancer, with 40,800 (31,700–50,100) deaths, and a total of 1,940,000 (1,512,300–2,377,400) DALYs. The ASMR and age-standardized DALYs rate for TBL cancer were 4.93 (3.84–6.10) and 237.88 (185.64–294.30) per 100,000. In the US, breast cancer had the highest burden of deaths [4,600 (4,300–4,800)] and DALYs [247,000 (231,700–262,100) person-years], with an ASMR of 2.76 (2.61–2.91) per 100,000, and an age-standardized DALYs rate of 150.17 (140.04–160.36) per 100,000 (Tables 2 and 3 ).

Table 2 Number of incidences, deaths, dalys, and ASR of early-onset cancers in China, 2021. Cancer name Incidence Mortality DALYs Number (10 thousands ) ASR per 100,000 persons Number (10 thousands ) ASR per 100,000 persons Number (10 thousands ) ASR per 100,000 persons Total cancers 75.06 (64.09, 88.61) 94.91(80.59,112.59) 24.08 (19.85, 28.79) 30.20(24.85,36.10) 1207.20 (996.91, 1441.18) 1550.20(1278.92,1850.54) Esophageal cancer 1.89 (1.46, 2.36) 2.23 (1.74, 2.84) 1.30 (1.00, 1.65) 1.53 (1.18, 1.97) 60.58 (46.73, 76.73) 72.39(55.67, 92.79) Stomach cancer 5.81 (4.59, 7.44) 7.18 (5.56, 9.18) 3.06 (2.40, 3.95) 3.73 (2.90, 4.79) 148.01 (117.01, 189.96) 183.47(142.37,234.73) Liver cancer 3.85 (3.05, 5.02) 4.72(3.60, 6.15) 2.81 (2.24, 3.65) 3.45 (2.63, 4.51) 136.31 (108.32, 176.91) 169.68(129.50,221.83) Larynx cancer 0.28 (0.22, 0.36) 0.34 (0.26, 0.43) 0.11 (0.08, 0.14) 0.13 (0.10, 0.16) 5.14 (3.94, 6.53) 6.22 (4.75, 7.95) Tracheal, bronchus, and lung cancer 5.29 (4.13, 6.52) 6.38 (4.99, 7.88) 4.08 (3.17, 5.01) 4.93 (3.84, 6.10) 194.00 (151.23, 237.74) 237.88(185.64,294.30) Breast cancer 11.37 (8.57, 14.63) 13.95 (10.41, 18.18) 1.68 (1.27, 2.19) 2.05 (1.53, 2.67) 88.37 (66.98, 114.40) 108.96(81.05,142.54) Cervical cancer 4.98 (3.55, 6.56) 6.28 (4.45, 8.36) 0.92 (0.66, 1.21) 1.13 (0.80, 1.51) 46.76 (33.60, 62.13) 58.16 (41.33, 77.73) Uterine cancer 1.43 (0.98, 2.04) 1.75 (1.17, 2.49) 0.16 (0.11, 0.22) 0.19 (0.13, 0.27) 8.36 (5.76, 11.72) 10.36 (6.95, 14.63) Prostate cancer 0.24 (0.16, 0.32) 0.29 (0.19, 0.41) 0.04 (0.03, 0.05) 0.05(0.03, 0.06) 1.98 (1.31, 2.68) 2.47 (1.58, 3.45) Colon and rectum cancer 7.87 (6.27, 9.65) 9.83 (7.80, 12.15) 2.45 (1.95, 3.00) 3.05 (2.41, 3.80) 124.36 (98.31, 152.44) 158.06 (125.08,196.29) Lip and oral cavity cancer 0.76 (0.61, 0.93) 0.95 (0.75, 1.18) 0.21 (0.16, 0.26) 0.25 (0.20, 0.32) 10.25 (8.04, 12.69) 12.79 (10.04, 16.05) Nasopharynx cancer 2.71 (2.12, 3.39) 3.50 (2.66, 4.56) 0.61 (0.47, 0.77) 0.76 (0.59, 0.97) 31.20 (24.40, 38.98) 39.82 (30.67, 50.52) Other pharynx cancer 0.15 (0.12, 0.19) 0.18 (0.14, 0.23) 0.05 (0.04, 0.06) 0.06 (0.05, 0.08) 2.36 (1.83, 2.99) 2.87 (2.20, 3.67) Gallbladder and biliary tract cancer 0.39 (0.24, 0.51) 0.48 (0.30, 0.63) 0.19 (0.13, 0.25) 0.24(0.15,0.31) 9.34 (6.02, 12.14) 11.47 (7.46, 15.10) Pancreatic cancer 1.03 (0.79, 1.29) 1.25 (0.97, 1.58) 0.89 (0.69, 1.11) 1.08(0.83,1.36) 42.46 (32.78, 52.98) 52.31 (40.50, 65.64) Malignant skin melanoma 0.37 (0.20, 0.51) 0.49 (0.26, 0.68) 0.09 (0.05, 0.12) 0.12 (0.06, 0.16) 4.81 (2.64, 6.48) 6.31 (3.42, 8.56) Non-melanoma skin cancer 10.29 (7.78, 13.16) 12.82 (8.50, 18.48) 0.10 (0.08, 0.13) 0.13 (0.10, 0.17) 5.27 (4.09, 6.54) 6.87 (5.18, 8.63) Ovarian cancer 1.13 (0.83, 1.52) 1.49 (1.05, 2.05) 0.35 (0.26, 0.47) 0.44 (0.31, 0.60) 17.64 (12.69, 23.64) 22.31 (15.74, 30.72) Testicular cancer 0.42 (0.33, 0.53) 0.62(0.46, 0.83) 0.04 (0.03, 0.06) 0.06 (0.05, 0.08) 2.67 (2.09, 3.33) 3.98 (3.01, 5.08) Kidney cancer 1.33 (1.08, 1.64) 1.70(1.35, 2.12) 0.25 (0.20, 0.31) 0.32 (0.25, 0.40) 13.02 (10.44, 16.07) 16.72 (13.26, 20.92) Bladder cancer 0.90 (0.71, 1.14) 1.12 (0.87, 1.45) 0.16 (0.12, 0.20) 0.19(0.15, 0.25) 8.15 (6.46, 10.51) 10.17 (7.92, 13.18) Brain and central nervous system cancer 2.99 (2.31, 3.87) 4.23 (3.22, 5.57) 1.33 (1.01, 1.76) 1.80 (1.36, 2.38) 70.37 (53.87, 92.97) 99.13 (74.61, 130.60) Thyroid cancer 1.72 (1.37, 2.24) 2.23 (1.73, 2.96) 0.06 (0.05, 0.08) 0.08 (0.06, 0.11) 4.08(3.16, 5.20) 5.34 (4.09, 6.93) Mesothelioma 0.06 (0.05, 0.07) 0.07 (0.06, 0.09) 0.05 (0.04, 0.06) 0.06 (0.05, 0.08) 2.38 (1.94, 2.90) 3.05 (2.45, 3.78) Hodgkin lymphoma 0.13 (0.08, 0.18) 0.18 (0.12, 0.26) 0.04 (0.03, 0.06) 0.06 (0.04, 0.09) 2.43 (1.64, 3.55) 3.55 (2.36, 5.29) Non-Hodgkin lymphoma 2.16 (1.67, 2.65) 2.84 (2.13, 3.55) 0.62 (0.48, 0.76) 0.83 (0.63, 1.03) 33.30 (25.61, 41.01) 46.06 (35.24, 56.88) Multiple myeloma 0.19 (0.11, 0.26) 0.25 (0.14, 0.34) 0.11 (0.07, 0.15) 0.15(0.08,0.20) 5.72 (3.28, 7.59) 7.56(4.17, 10.28) Leukemia 2.76 (1.97, 3.46) 4.04 (2.79, 5.16) 1.55 (1.13, 1.94) 2.28(1.61,2.90) 87.05 (63.27, 108.91) 133.56 (94.16, 169.12) Other malignant neoplasms 1.77 (1.37, 2.27) 2.37 (1.78, 3.07) 0.42 (0.33, 0.54) 0.57(0.43,0.73) 22.48 (17.33, 28.51) 31.26 (23.51, 40.20) Eye cancer 0.05 (0.03, 0.07) 0.07 (0.04, 0.11) 0.01 (0.00, 0.01) 0.01(0.00,0.01) 0.32 (0.17, 0.44) 0.43 (0.23, 0.61) Soft tissue and other extraosseous sarcomas 0.16 (0.11, 0.24) 0.22 (0.15, 0.32) 0.06 (0.04, 0.08) 0.08 (0.05, 0.11) 2.99 (2.10, 4.44) 4.10 (2.80, 6.22) Malignant neoplasm of bone and articular cartilage 0.55 (0.34, 0.72) 0.80 (0.49, 1.08) 0.25 (0.16, 0.33) 0.36(0.23,0.49) 13.92 (8.89, 18.45) 21.28 (13.53, 28.58) Neuroblastoma and other peripheral nervous cell tumors 0.04 (0.03, 0.05) 0.06 (0.04, 0.08) 0.02 (0.02, 0.03) 0.03(0.02, 0.04) 1.11 (0.89, 1.36) 1.62(1.23, 2.03) 95% Uncertainty Interval (UI) in the number column and 95% Confidence Interval (CI) in parentheses in the ASR column.

Table 3 Number of incidences, deaths, dalys, and ASR of early-onset cancers in the US, 2021. Cancer name Incidence Mortality DALYs Number (10 thousands ) ASR per 100,000 persons Number (10 thousands ) ASR per 100,000 persons Number (10 thousands ) ASR per 100,000 persons Total cancers 47.26 (43.28, 51.67) 288.62 (255.47, 328.39) 3.06 (2.97, 3.14) 18.76 (18.19, 19.33) 160.79 (155.48, 166.68) 994.81 (959.02, 1033.14) Esophageal cancer 0.11 (0.11, 0.12) 0.69 (0.66, 0.72) 0.07 (0.07, 0.08) 0.45 (0.43, 0.47) 3.53 (3.41, 3.66) 21.40 (20.53, 22.31) Stomach cancer 0.26 (0.25, 0.27) 1.61 (1.54, 1.68) 0.11 (0.11, 0.12) 0.68 (0.66, 0.71) 5.51 (5.33, 5.68) 33.76 (32.48, 35.03) Liver cancer 0.17 (0.16, 0.17) 1.03 (0.98, 1.08) 0.09 (0.09, 0.09) 0.55 (0.53, 0.58) 4.48 (4.32, 4.64) 27.63 (26.41, 28.87) Larynx cancer 0.06 (0.06, 0.06) 0.37 (0.35, 0.39) 0.01 (0.01, 0.01) 0.07 (0.07, 0.08) 0.59 (0.57, 0.62) 3.58 (3.42, 3.74) Tracheal, bronchus, and lung cancer 0.45 (0.43, 0.47) 2.70 (2.60, 2.81) 0.31 (0.30, 0.32) 1.86 (1.79, 1.94) 14.46 (13.99, 14.99) 87.24 (84.07, 90.71) Breast cancer 4.09 (3.88, 4.32) 24.84 (23.26, 26.53) 0.46 (0.43, 0.48) 2.76 (2.61, 2.91) 24.70 (23.17, 26.21) 150.17 (140.04, 160.36) Cervical cancer 1.24 (1.18, 1.30) 7.70 (7.19, 8.26) 0.14 (0.13, 0.14) 0.85 (0.80, 0.89) 7.46 (7.09, 7.88) 45.87 (43.17, 48.97) Uterine cancer 0.70 (0.67, 0.73) 4.24 (4.01, 4.50) 0.04 (0.04, 0.04) 0.23 (0.22, 0.24) 2.13 (1.99, 2.30) 12.89 (12.00, 13.95) Prostate cancer 0.34 (0.32, 0.37) 2.04 (1.88, 2.21) 0.01 (0.01, 0.01) 0.08 (0.07, 0.08) 0.82 (0.74, 0.92) 4.92 (4.40, 5.48) Colon and rectum cancer 1.73 (1.67, 1.79) 10.50 (10.01, 11.01) 0.41 (0.39, 0.42) 2.47 (2.37, 2.58) 20.55 (19.77, 21.31) 125.16 (119.67, 130.69) Lip and oral cavity cancer 0.28 (0.27, 0.30) 1.74 (1.65, 1.84) 0.04 (0.03, 0.04) 0.21 (0.21, 0.22) 1.84 (1.76, 1.92) 11.28 (10.75, 11.83) Nasopharynx cancer 0.07 (0.06, 0.07) 0.43 (0.40, 0.46) 0.01 (0.01, 0.01) 0.08 (0.08, 0.08) 0.68 (0.65, 0.71) 4.23 (4.01, 4.47) Other pharynx cancer 0.12 (0.11, 0.12) 0.70 (0.66, 0.74) 0.02 (0.01, 0.02) 0.09 (0.09, 0.10) 0.77 (0.74, 0.81) 4.64 (4.41, 4.90) Gallbladder and biliary tract cancer 0.07 (0.06, 0.07) 0.41 (0.39, 0.44) 0.02 (0.02, 0.02) 0.10 (0.09, 0.10) 0.79 (0.76, 0.82) 4.78 (4.57, 5.01) Pancreatic cancer 0.21 (0.20, 0.21) 1.23 (1.19, 1.28) 0.15 (0.15, 0.16) 0.90 (0.87, 0.94) 7.04 (6.82, 7.30) 42.49 (40.92, 44.21) Malignant skin melanoma 1.54 (1.48, 1.59) 9.56 (9.04, 10.09) 0.08 (0.08, 0.08) 0.50 (0.49, 0.52) 4.86 (4.58, 5.21) 30.15 (28.30, 32.36) Non-melanoma skin cancer 29.59 (25.93, 33.98) 179.48 (147.20, 217.90) 0.02 (0.01, 0.02) 0.09 (0.09, 0.10) 0.99 (0.89, 1.12) 6.08 (5.40, 7.02) Ovarian cancer 0.35 (0.33, 0.36) 2.15 (2.02, 2.29) 0.09 (0.09, 0.10) 0.56 (0.53, 0.59) 4.61 (4.38, 4.83) 28.22 (26.63, 29.94) Testicular cancer 0.99 (0.94, 1.04) 6.44 (5.93, 7.01) 0.03 (0.03, 0.03) 0.20 (0.19, 0.22) 2.32 (2.14, 2.55) 15.13 (13.76, 16.79) Kidney cancer 0.60 (0.58, 0.63) 3.70 (3.54, 3.88) 0.07 (0.07, 0.07) 0.43 (0.41, 0.44) 3.68 (3.51, 3.85) 22.57 (21.45, 23.75) Bladder cancer 0.32 (0.31, 0.33) 1.93 (1.85, 2.02) 0.03 (0.02, 0.03) 0.15 (0.15, 0.16) 1.39 (1.31, 1.48) 8.43 (7.93, 9.00) Brain and central nervous system cancer 0.65 (0.62, 0.67) 4.15 (3.88, 4.43) 0.25 (0.25, 0.26) 1.60 (1.54, 1.66) 13.54 (13.12, 13.98) 85.87 (82.51, 89.36) Thyroid cancer 0.66 (0.63, 0.69) 4.07 (3.82, 4.35) 0.01 (0.01, 0.01) 0.07 (0.07, 0.08) 0.93 (0.83, 1.07) 5.75 (5.06, 6.63) Mesothelioma 0.01 (0.01, 0.01) 0.05 (0.05, 0.06) 0.01 (0.01, 0.01) 0.04 (0.04, 0.04) 0.32 (0.31, 0.34) 1.99 (1.88, 2.10) Hodgkin lymphoma 0.32 (0.30, 0.33) 2.07 (1.93, 2.22) 0.02 (0.02, 0.02) 0.14 (0.14, 0.15) 1.40 (1.33, 1.49) 9.05 (8.51, 9.67) Non-Hodgkin lymphoma 0.86 (0.82, 0.91) 5.43 (4.96, 5.93) 0.12 (0.12, 0.12) 0.74 (0.71, 0.77) 6.71 (6.43, 7.00) 42.23 (40.25, 44.34) Multiple myeloma 0.05 (0.05, 0.05) 0.29 (0.28, 0.31) 0.03 (0.03, 0.04) 0.20 (0.19, 0.21) 1.60 (1.53, 1.67) 9.65 (9.22, 10.08) Leukemia 0.40 (0.39, 0.42) 2.58 (2.46, 2.72) 0.19 (0.19, 0.20) 1.23 (1.18, 1.29) 10.61 (10.24, 10.97) 68.65 (65.76, 71.79) Other malignant neoplasms 0.57 (0.55, 0.60) 3.56 (3.33, 3.80) 0.07 (0.07, 0.08) 0.46 (0.44, 0.48) 4.05 (3.88, 4.25) 25.43 (24.23, 26.80) Eye cancer 0.03 (0.03, 0.04) 0.22 (0.18, 0.27) 0.00 (0.00, 0.00) 0.02 (0.02, 0.02) 0.19 (0.18, 0.20) 1.19 (1.10, 1.29) Soft tissue and other extraosseous sarcomas 0.27 (0.25, 0.29) 1.74 (1.60, 1.87) 0.08 (0.08, 0.09) 0.53 (0.50, 0.56) 4.66 (4.45, 4.85) 30.10 (28.45, 31.61) Malignant neoplasm of bone and articular cartilage 0.13 (0.12, 0.13) 0.86 (0.79, 0.93) 0.05 (0.05, 0.05) 0.35 (0.33, 0.36) 3.19 (3.05, 3.33) 21.76 (20.59, 22.95) Neuroblastoma and other peripheral nervous cell tumors 0.02 (0.01, 0.02) 0.10 (0.08, 0.12) 0.01 (0.01, 0.01) 0.04 (0.04, 0.05) 0.38 (0.35, 0.42) 2.52 (2.28, 2.78) 95% Uncertainty Interval (UI) in the number column and 95% Confidence Interval (CI) in parentheses in the ASR column.

Trends of early-onset cancers burden from 1990 to 2021

Between 1990 and 2021, both ASMR and age-standardized DALYs rate for early-onset cancers in China and the US showed a temporal downward trend, with NMSC, breast cancer, and CRC being the main drivers of the rise in ASIR for early-onset cancers in both countries (Fig. 1 ).

Over the past 32 years, the overall ASIR of early-onset cancers has continued to rise in China, whereas in the US, there was a significant increase in ASIR after 2000 and stabilized after 2004, and the ASIR of early-onset cancers in the US has always been much higher than that in China. The US was in a period of rapid increase in ASIR of early-onset cancers from 2000 to 2004 [APC = 7.76(7.19 to 8.33), p < 0.001]. In contrast, the period of rapid increase in ASIR for early-onset cancers in China occurred from 2008 to 2021 [APC = 3.48(2.69 to 4.28), p < 0.001]. Analysis of the rates of ASMR and age-standardized DALYs rate in both countries revealed a similar pattern of burden change, with both countries showing a downward trend from year to year. This was manifested by a slight decrease in ASMR in China and the US, [AAPC = -1.57 (-1.36 to -1.79), p < 0.001], [AAPC = -1.65 (-1.41 to -1.88), p < 0.001], and age-standardized DALYs rates with AAPCs of − 1.50 (-1.29 to -1.71, p < 0.001) and − 1.59 (-1.34 to -1.85, p < 0.001) (Fig. 2 ).

Fig. 1 Contributions of individual early-onset cancers to the overall ASR in China and the US, 1990–2021. ( A ), ( B ) ASIRs in China and the US. ( C ), ( D ) ASMRs in China and the US. ( E ), ( F ) Age-standardized DALYs rates in China and the US.

Fig. 2 Trends of the overall burden of 33 early-onset cancers in China and the US, 1990–2021. ( A ) Trends of ASIR. ( B ) Trends of ASMR. ( C ) Trends of age-standardized DALYs rate.

To further explore country-specific patterns, we conducted a comparative analysis of the top 10 early-onset cancers with the highest ASIRs in the overall population, males, and females in China and the US (Fig. 3 ). From 1990 to 2021, ASIRs of most early-onset cancers showed an upward trend in both countries, but notable differences were observed in the specific cancer types and temporal trajectories. In China, the ASIR of early-onset breast cancer more than doubled, rising from 6.80 per 100,000 in 1990 to 13.95 per 100,000 in 2021—a 104.99% increase. In contrast, the US experienced a steady decline, with the ASIR decreasing by 28.12% to 24.84 per 100,000 in 2021. For NMSC, the ASIR in China remained relatively low and stable, reaching 12.82 per 100,000 in 2021. Meanwhile, the US showed a sharp increase after 2000, stabilizing at a high level of 179 per 100,000. CRC demonstrated a marked increase in ASIR in China, especially after 2005, with a 53.95% rise. In contrast, the ASIR in the US began declining steadily after 2018. By 2021, the two countries had converging ASIRs: 9.83 per 100,000 in China versus 10.50 per 100,000 in the US. For stomach cancer, although ASIRs in China declined by 45.54%—from 13.15 per 100,000 in 1990 to 7.18 per 100,000 in 2021—they remained substantially higher than in the US, where the ASIR was consistently low (1.61 per 100,000 in 2021). TBL cancer rates in China remained relatively stable at a high level, with an ASIR of 6.38 per 100,000 in 2021. In contrast, the US saw a sharp decline to 2.70 per 100,000 in 2021, representing a 66.20% decrease. Liver cancer ASIRs in China declined significantly after 2000 but stabilized after 2005, reaching 4.72 per 100,000 in 2021. In the US, ASIRs remained consistently low at 1.03 per 100,000 in 2021. Cervical cancer exhibited divergent trends: a 26.52% increase in ASIR in China, where rates remained low but were rising, whereas in the US, the ASIR declined by 43.24%, with the two countries showing increasingly similar incidence levels. Malignant skin melanoma showed a decreasing trend in the US, but ASIRs remained markedly higher than in China (9.56 vs. 0.49 per 100,000 in 2021). Testicular cancer incidence remained low in China, while the ASIR in the US was relatively high and rose by 43.21% over the study period. For non-Hodgkin lymphoma, China experienced a moderate increase in ASIR (81.63%), whereas the US saw a decline beginning in 1997, with a 39.21% reduction by 2021.

Early-onset cancers burden stratified by sex

The burden of disease for early-onset cancers varies between genders and countries, although there are similarities. In China, the cancers that ranked high in ASIR, ASMR, and age-standardized DALYs rates in men were CRC, TBL cancer, stomach cancer, and liver cancer, whereas the top ranked cancers in the women were breast cancer, TBL cancer, leukemia, and cervical cancer. In the US, the highest population-wide ASIR was for NMSC, with a higher incidence of testicular cancer in men and higher ASIRs for breast cancer and cervical cancer in women. Notably, breast cancer exhibited high ASIR and age-standardized DALYs rates in both countries (Fig. 4 ).

Fig. 3 Trends of 10 early-onset cancers in ASIRs in China and the US, 1990–2021. ( A ) Breast cancer ( B ) Non-melanoma skin cancer ( C ) Colon and rectum cancer ( D ) Stomach cancer ( E ) Tracheal, bronchus, and lung cancer ( F ) Liver cancer ( G ) Crevical cancer ( H ) Malignant skin melanoma ( I ) Testicular cancer ( J ) Non-Hodgkin lymphoma.

Fig. 4 Ranking of ASIRs, ASMRs, and age-standardized DALYs rates in early-onset cancers by sex in 2021.

Comparison of attributable risk factors for early-onset cancers

Our research focuses on the attribution of risk factors based on DALYs for the seven most typical early-onset cancers with the highest ASIR, ASMR, or age-standardized DALYs rate in 2021 (or by sex), including breast cancer, cervical cancer, CRC, liver cancer, non-Hodgkin lymphoma, stomach cancer, and TBL cancer. The results show that in China, early-onset breast cancer and CRC are primarily attributed to dietary risks, accounting for 14.71% and 56.80%, respectively. Early-onset liver cancer, stomach cancer, and TBL cancer are most strongly attributed to tobacco use, with percentages of 23.99%, 17.90%, and 119.44%, respectively. The highest attribution for early-onset cervical cancer is to unsafe sex (58.13%). Among the 11 risk factors, liver cancer attributable to high BMI saw the greatest increase in age-standardized DALYs rates (177.21%), while dietary risks were associated with the greatest decrease in age-standardized DALYs rates for TBL cancer (-72.12%). In the US, dietary risks were the leading causes for early-onset breast cancer and CRC, accounting for 20.38% and 50.85%, respectively. Unsafe sex accounted for the majority of early-onset cervical cancer (45.87%), and drug use was the major factor for early-onset liver cancer (9.54%). Tobacco use was the dominant factor for early-onset TBL cancer (48.96%), while early-onset stomach cancer showed lower attributions to two known risk factors. Among the 11 risk factors, HFPG was associated with the greatest increase in age-standardized DALYs rate for liver cancer (107.69%), whereas air pollution was linked to the greatest reduction in age-standardized DALYs rate for TBL cancer (-89.53%). Furthermore, due to data limitations and the specificity of the disease, only high BMI was included as a known risk factor for non-Hodgkin lymphoma in our study. Notably, this factor showed a significant difference between the two countries: high BMI caused a marked increase in age-standardized DALYs rate for non-Hodgkin lymphoma in China (55.62%), whereas it led to a notable decrease in the US (-46.09%) (Figs. 5 and 6 ).

Fig. 5 Comparison of age-standardized DALYs rates for attributable risk factors for early-onset cancer in China between 1990 and 2021.

Fig. 6 Comparison of age-standardized DALYs rates for attributable risk factors for early-onset cancer in the US between 1990 and 2021.

Discussion

China and the US are two of the most representative socioeconomic systems in the world 33 . Studying the burden of early-onset cancers in these two countries can help us better understand cancer trends and identify major risk factors, which not only helps the two countries formulate public health policies but also provides a reference for the development of global prevention and control strategies. Currently, the ASMR and age-standardized DALYs rate of early-onset cancer in China are higher than those in the US, while the ASIR of early-onset cancer in the US is higher than that in China, highlighting substantial differences in the disease burden between the two countries.

By analyzing typical early-onset cancers as a percentage of overall incidence, it is clear that the ASIR of NMSC has a significant impact on the overall ASIR, especially in the US. NMSC, as the most common type of skin cancer 34 , accounts for 2 to 3 million new cases globally each year 35 , with a large patient population, seriously threatening public health and placing a heavy burden on healthcare systems. Although NMSC is largely preventable and treatable, insufficient research funding and limited public awareness have contributed to its high burden in countries with a large proportion of light-skinned populations, such as the US 36 . In addition to inherent factors such as skin color, genetic background, and geographical location, rising socio-economic status and increased outdoor activity significantly elevate the risk of morbidity, with early cases being more likely to be detected, especially in high socio-economic status populations 37 . Between 2000 and 2005, there was a significant jump in the standardized incidence of NMSC in the US, in 2005, the ASIR reached 176.36 per 100,000, an increase of 95.42%. This phenomenon was not a dramatic increase in the true disease burden, but resulted primarily from changes in data collection and statistical mechanisms. At the beginning of the 21st century, U.S. cancer registries (e.g., SEER) began to collect NMSC-related data more systematically, expanding registry coverage 38 . Moreover, the gradual replacement of ICD-9 by the ICD-10 disease classification system has resulted in more cases of skin tumors being included in the statistics. In addition, the popularization of skin cancer screening technology and the increase in public health awareness have prompted a large number of early and mild cases to be diagnosed and reported in a timely manner, further contributing to the rise in incidence rates. In China, NMSC also exhibits a high incidence rate, ranking second among 33 common cancers. Early-onset NMSC is more prevalent in women than in men. The high incidence of early-onset NMSC presents a shared challenge for both China and the US, necessitating a reassessment of current prevention and control strategies, particularly in enhancing preventive measures. Public education campaigns, promotion of ultraviolet protection measures, and encouragement of self-examination and early screening could raise public awareness of NMSC, foster healthy behaviors, and prevent precancerous lesions such as actinic keratosis, ultimately reducing the burden of NMSC.

The ASIR, ASMR and age-standardized DALYs rate of breast cancer in both countries are also noteworthy. While the incidence of breast cancer in the US is far higher than in China, the ASIR of breast cancer in China is rapidly increasing, and women face a significantly higher disease burden than men. China’s large-scale breast cancer screening programs began nearly 30 years later than in the US 39 , 40 . Moreover, challenges such as low awareness, participation rates, and screening quality persist in China’s early breast cancer screening programs 41 , 42 . Studies have shown that, from 2002 to 2012, the proportion of stage I breast cancer diagnosed in China was 13.5%, significantly lower than the 50.5% in the US 43 . Due to limitations in GBD 2021, this study only assessed the contribution of dietary risks, excessive alcohol consumption, smoking, HFPG, and low physical activity to DALYs for early-onset breast cancer. The most significant attributable risk factors were dietary risks (China: 17.18%, US: 38.36%) and smoking (China: 4.8%, US: 19.06%). In the future, by improving residents’ diets, restricting tobacco use, and optimizing early diagnosis and screening programs for breast cancer, as well as improving treatment methods based on national conditions, we can effectively alleviate the increasing burden of early-onset breast cancer in China 44 .

Taking CRC as examples, from 1990 to 2021, the ranking of CRC as a cause of death from early-onset cancer in the US rose from third to second, second only to breast cancer. In China, the ranking of early-onset CRC as a cause of death also increased, from fifth to fourth. In contrast to the high incidence and low mortality rates in the US, both the incidence and mortality rates for CRC in China are relatively high. This is mainly due to the fact that after China’s rapid development, the demographic structure and socioeconomic environment have changed dramatically, and before traditional infection-related gastrointestinal tumors, such as gastric cancer and hepatocellular carcinoma, can be completely prevented and controlled, urbanization and western lifestyle have caused a gradual high incidence and prevalence of CRC, which ultimately creates a situation where the cancer spectrum of developing and developed countries coexist in China 45 . In 2021, the incidence rate in China has reached 9.83 per 100,000. Without systematic interventions, the incidence of CRC in China is likely to equal or even surpass that of the USin the future. This poses a potential challenge to the allocation of healthcare resources, the burden of healthcare insurance, and socioeconomic development.

Early-onset stomach cancer is currently the second leading cause of death in China, and the disease burden in China is far higher than in the US. The overall ASIR for gastric cancer in China showed a gradual decline from 1990 to 2021, from 13.15 per 100,000 in 1990 to 7.18 per 100,000 in 2021. This is due to the National Cancer Prevention and Control Awareness Week initiated by the Chinese Anti-Cancer Society in 1995, which has increased public awareness of cancer and the overall improvement of China’s healthcare system. However, according to the report, China still accounts for nearly half of the world’s new cases and deaths from gastric and esophageal cancer each year 46 . The prevalence of Helicobacter pylori infection is one of the most important causative factors of gastric cancer, and the infection rate of the Chinese population has long been higher than 42.8%, and can even reach more than 60% in the rural and underdeveloped areas 47 , 48 . Differences in dietary habits are also a key factor in determining the gap in the incidence of gastric cancer between the two countries. The traditional diet of Chinese residents is high in salt, pickled and smoked foods, and they often consume salted fish, pickles, salted meat and other foods rich in nitrosamines, which have been shown to be highly carcinogenic 49 . Although CRC and stomach cancers have different disease progression patterns, they share some common risk factors, such as dietary patterns, alcohol consumption, smoking, and being overweight and obese 50 . Both China and the US should recognize the significant impact of CRC and stomach cancer on early-onset cancer and implement effective measures based on current burden trends. Prevention of digestive cancers such as CRC and gastric cancer should advocate for a whole-grain diet, reduced intake of sugary beverages, increased physical activity, smoking cessation, and alcohol abstinence, as well as strengthen community-based early screening and health education to effectively identify and prevent early-onset CRC, stomach cancer, and other diseases. These measures will improve early diagnosis rates and treatment outcomes, forming a comprehensive prevention strategy to address the rising challenges of digestive diseases in both China and the US 51 , 52 .

Studies on the incidence of early-onset liver and lung cancers are important because of their similarities and differences. The major risk factors for both types of cancer are relatively well defined and controllable 53 .The incidence of tracheal, bronchial, and lung cancers from 1990 to 2021 has been remarkably controlled in the US, due in large part to a series of long-term and systematic comprehensive measures in the US. The US has been highly effective in improving air quality, and the implementation of laws such as the Clean Air Act has dramatically reduced industrial and motor vehicle emissions and lowered the public’s risk of exposure to cancer-causing pollutants 54 . In addition, the level of early screening and diagnosis and treatment of lung cancer has been continuously improved, especially the promotion of low-dose spiral CT screening for high-risk groups, which has improved the early detection rate and prolonged the survival period of patients. The wide application of new treatment methods, such as targeted therapy and immunotherapy, has also effectively improved the effectiveness of treatment 55 .

Since 2000, the ASIR of early-onset liver cancer in China has shown a slight downward trend, decreasing from 5.87 per 100,000 in 2000 to 4.28 per 100,000 in 2006, which was mainly attributed to the effective control of hepatitis B virus (HBV) and hepatitis C virus (HCV) 56 .The large-scale promotion of hepatitis B vaccination in China in the late 1990s significantly reduced the rate of hepatitis B infections in neonates and young populations, which in turn lowered the risk of hepatocellular carcinoma in the future. At the same time, the use of oral antiviral drugs has led to significant progress in the treatment of HCV as health conditions and medical care have improved. Together, these measures have contributed to the decline in the incidence of liver cancer 57 . However, after 2006, the incidence of early-onset liver cancer fluctuated and showed a increase. This is mainly related to the excessive use of tobacco and alcohol and the increasing prevalence of metabolic diseases such as obesity and diabetes. Metabolic diseases are emerging as important new causes of liver cancer, offsetting the positive impact of viral hepatitis control, making it difficult to completely eliminate liver cancer and leading to a certain degree of resurgence 58 .

China is not a high-incidence region for testicular cancer, whereas in 2021, the ASIR in the US reached 6.44 per 100,000—approximately ten times higher than that in China—highlighting the substantial disparity between the two countries. Studies have shown that the pattern of early-onset Testicular cancer pathogenesis is highly consistent with its genetics. Testicular cancer has a clear genetic predisposition, with a significantly higher risk of development, especially in those with a family history or carrying specific genetic markers 59 . In addition, the incidence of early-onset testicular cancer is strongly associated with health care expenditures, appropriate diagnostic and treatment services. The US invests more in health and has more advanced treatments and diagnostic methods. Although the U.S. incidence of testicular cancer in the study has increased almost 1.5-fold in 2021 compared with 1990, the U.S. testicular cancer mortality rate has remained stable, reflecting significant advances in the therapeutic management of testicular cancer 60 .

We analyzed the attributable risk factors for several early-onset cancers found that smoking, HFPG, and dietary risks are the main causes of multiple early-onset cancers. By 2021, the DALYs rate attributed to smoking and dietary risks had significantly decreased, while the DALYs rate associated with HFPG showed a slight upward trend. HFPG is closely related to diabetes and often occurs in prediabetes, setting off a series of “chain reactions” that increase the risk of developing early-onset cancers. Studies have shown that HFPG has become a major contributor to the increasing burden of various cancers globally, a burden that is expected to continue to rise in the future 61 , 62 . Given the growing negative impact of HFPG on early-onset cancer, we suggests that adjusting to a healthier diet and increasing daily exercise can help prevent and improve fasting blood glucose levels, thereby reducing the risk of cancer and alleviating the burden of disease to some extent.

Conclusion

The burden of early-onset cancer is a significant concern for both China and the US. While there are some similarities between the two countries in terms of early-onset cancer burden, notable differences also exist. In China, the burden of early-onset stomach cancer, liver cancer, and TBL cancer is particularly prominent, like a sword of Damocles hanging overhead. In the US, NMSC and testicular cancer represent more pressing issues. The impact of early-onset cancer varies significantly between the two countries, driven by factors such as disease types, social culture, and dietary habits. Given these differences, both China and the US should take targeted intervention measures and emergency actions based on the differences in the development trends of early-onset cancer, to effectively control the disease burden.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rui Ye and Yang Cao contributed equally to this work.

Author contributions

R.Y and Y. C: design research, data organization, data analysis, visualization, writing the original manuscript, writing—review and editing. A.Q: formal analysis, funding acquisition, supervision, writing—review and editing. X.Z and Z.R: formal analysis, writing—review and editing. All authors contributed to the article and approved the submitted.

Funding

This work was supported by the National Social Science Foundation of China (No.20BTQ053).

Data availability

Data is provided within the manuscript or supplementary information files.

Declarations

Competing interests

The authors declare no competing interests.

References

1. GBD 2017 Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 392 , 1736–88 (2018). 10.1016/S0140-6736(18)32203-7 10.1016/S0140-6736(18)32203-7 PMC6227606 30496103

2. Ugai T Is early-onset cancer an emerging global epidemic? Current evidence and future implications Nat. Rev. Clin. Oncol. 2022 19 656 673 10.1038/s41571-022-00672-8 36068272 PMC9509459 Ugai, T. et al. Is early-onset cancer an emerging global epidemic? Current evidence and future implications. Nat. Rev. Clin. Oncol. 19 , 656–673. 10.1038/s41571-022-00672-8 (2022). 36068272 10.1038/s41571-022-00672-8 PMC9509459

3. Chen S Estimates and projections of the global economic cost of 29 cancers in 204 countries and territories from 2020 to 2050 JAMA Oncol. 2023 9 465 472 10.1001/jamaoncol.2022.7826 36821107 PMC9951101 Chen, S. et al. Estimates and projections of the global economic cost of 29 cancers in 204 countries and territories from 2020 to 2050. JAMA Oncol. 9 , 465–472. 10.1001/jamaoncol.2022.7826 (2023). 36821107 10.1001/jamaoncol.2022.7826 PMC9951101

4. Mooney-Somers J Lewis P Kerridge I Discursive constructions of youth cancer: findings from creative methods research with healthy young people J. Cancer Surviv 2016 10 427 436 10.1007/s11764-015-0488-1 26563950 Mooney-Somers, J., Lewis, P. & Kerridge, I. Discursive constructions of youth cancer: findings from creative methods research with healthy young people. J. Cancer Surviv . 10 , 427–436. 10.1007/s11764-015-0488-1 (2016). 26563950 10.1007/s11764-015-0488-1

5. Miller KD Cancer statistics for adolescents and young adults, 2020 CA Cancer J. Clin. 2020 70 443 459 10.3322/caac.21637 32940362 Miller, K. D. et al. Cancer statistics for adolescents and young adults, 2020. CA Cancer J. Clin. 70 , 443–459. 10.3322/caac.21637 (2020). 32940362 10.3322/caac.21637

6. Yoshida K Tobacco smoking and somatic mutations in human bronchial epithelium Nature 2020 578 266 272 10.1038/s41586-020-1961-1 31996850 PMC7021511 Yoshida, K. et al. Tobacco smoking and somatic mutations in human bronchial epithelium. Nature 578 , 266–272. 10.1038/s41586-020-1961-1 (2020). 31996850 10.1038/s41586-020-1961-1 PMC7021511

7. Danpanichkul P The global burden of Alcohol-associated cirrhosis and Cancer in young and Middle-aged adults Clin. Gastroenterol. Hepatol. 2024 22 1947 1949e3 10.1016/j.cgh.2024.02.011 38428708 PMC11344661 Danpanichkul, P. et al. The global burden of Alcohol-associated cirrhosis and Cancer in young and Middle-aged adults. Clin. Gastroenterol. Hepatol. 22 , 1947–1949e3. 10.1016/j.cgh.2024.02.011 (2024). 38428708 10.1016/j.cgh.2024.02.011 PMC11344661

8. Haedenkamp TM Antimicrobial drug use and the risk of glioma: A case-control study Cancer Med. 2023 12 3684 3695 10.1002/cam4.5222 36066038 PMC9939229 Haedenkamp, T. M. et al. Antimicrobial drug use and the risk of glioma: A case-control study. Cancer Med. 12 , 3684–3695. 10.1002/cam4.5222 (2023). 36066038 10.1002/cam4.5222 PMC9939229

9. Turner, M. C. et al. Outdoor air pollution and cancer: An overview of the current evidence and public health recommendations. CA Cancer J. Clin. 25 10.3322/caac.21632 (2020). 10.3322/caac.21632 PMC7904962 32964460

10. GBD 2019 Adolescent Young Adult Cancer Collaborators The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the global burden of disease study 2019 Lancet Oncol. 2022 23 27 52 10.1016/S1470-2045(21)00581-7 34871551 PMC8716339 GBD 2019 Adolescent Young Adult Cancer Collaborators. The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the global burden of disease study 2019. Lancet Oncol. 23 , 27–52. 10.1016/S1470-2045(21)00581-7 (2022). 34871551 10.1016/S1470-2045(21)00581-7 PMC8716339

11. Bray F Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries CA Cancer J. Clin. 2024 74 229 263 10.3322/caac.21834 38572751 Bray, F. et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 74 , 229–263. 10.3322/caac.21834 (2024). 38572751 10.3322/caac.21834

12. 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 Commun. (Lond) 2021 41 1037 1048 10.1002/cac2.12197 34288593 PMC8504144 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 Commun. (Lond) . 41 , 1037–1048. 10.1002/cac2.12197 (2021). 34288593 10.1002/cac2.12197 PMC8504144

13. Cao W Chen HD Yu YW Li N Chen WQ Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020 Chin. Med. J. (Engl) 2021 134 783 791 10.1097/CM9.0000000000001474 33734139 PMC8104205 Cao, W., Chen, H. D., Yu, Y. W., Li, N. & Chen, W. Q. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020. Chin. Med. J. (Engl) . 134 , 783–791. 10.1097/CM9.0000000000001474 (2021). 33734139 10.1097/CM9.0000000000001474 PMC8104205

14. Xia C Cancer statistics in China and united states, 2022: profiles, trends, and determinants Chin. Med. J. (Engl) 2022 135 584 590 10.1097/CM9.0000000000002108 35143424 PMC8920425 Xia, C. et al. Cancer statistics in China and united states, 2022: profiles, trends, and determinants. Chin. Med. J. (Engl) . 135 , 584–590. 10.1097/CM9.0000000000002108 (2022). 35143424 10.1097/CM9.0000000000002108 PMC8920425

15. Maomao C Current cancer burden in China: epidemiology, etiology, and prevention Cancer Biol. Med. 2022 19 1121 1138 10.20892/j.issn.2095-3941.2022.0231 36069534 PMC9425189 Maomao, C. et al. Current cancer burden in China: epidemiology, etiology, and prevention. Cancer Biol. Med. 19 , 1121–1138. 10.20892/j.issn.2095-3941.2022.0231 (2022). 36069534 10.20892/j.issn.2095-3941.2022.0231 PMC9425189

16. Liang, Y. et al. Distributions and trends of the global burden of colorectal Cancer attributable to dietary risk factors over the past 30 years. Nutrients 16 (132). 10.3390/nu16010132 (2023). 10.3390/nu16010132 PMC10780867 38201962

17. Jung YS Yoon SJ Burden of Cancer due to cigarette smoking and alcohol consumption in Korea Int. J. Environ. Res. Public. Health 2022 19 3493 10.3390/ijerph19063493 35329179 PMC8950006 Jung, Y. S. & Yoon, S. J. Burden of Cancer due to cigarette smoking and alcohol consumption in Korea. Int. J. Environ. Res. Public. Health . 19 , 3493. 10.3390/ijerph19063493 (2022). 35329179 10.3390/ijerph19063493 PMC8950006

18. Ohno S Chen Y Sakamaki H Matsumaru N Tsukamoto K A population-based study of the humanistic burden among cancer patients in Japan J. Med. Econ. 2020 23 429 441 10.1080/13696998.2019.1707213 31856614 Ohno, S., Chen, Y., Sakamaki, H., Matsumaru, N. & Tsukamoto, K. A population-based study of the humanistic burden among cancer patients in Japan. J. Med. Econ. 23 , 429–441. 10.1080/13696998.2019.1707213 (2020). 31856614 10.1080/13696998.2019.1707213

19. Wang L Prostate Cancer incidence and mortality: global status and Temporal trends in 89 countries from 2000 to 2019 Front. Public. Health 2022 10 811044 10.3389/fpubh.2022.81104 35252092 PMC8888523 Wang, L. et al. Prostate Cancer incidence and mortality: global status and Temporal trends in 89 countries from 2000 to 2019. Front. Public. Health . 10 , 811044. 10.3389/fpubh.2022.81104 (2022). 35252092 10.3389/fpubh.2022.811044 PMC8888523

20. Gong Y Jiang Q Zhai M Tang T Liu S Thyroid cancer trends in China and its comparative analysis with G20 countries: projections for 2020–2040 J. Glob Health 2024 14 04131 10.7189/jogh.14.0413 38873786 PMC11177899 Gong, Y., Jiang, Q., Zhai, M., Tang, T. & Liu, S. Thyroid cancer trends in China and its comparative analysis with G20 countries: projections for 2020–2040. J. Glob Health . 14 , 04131. 10.7189/jogh.14.0413 (2024). 38873786 10.7189/jogh.14.04131 PMC11177899

21. Wu SL Zhang Y Fu Y Li J Wang JS Gastric cancer incidence, mortality and burden in adolescents and young adults: a time-trend analysis and comparison among China, South korea, Japan and the USA BMJ Open. 2022 12 e061038 10.1136/bmjopen-2022-061038 35863834 PMC9310161 Wu, S. L., Zhang, Y., Fu, Y., Li, J. & Wang, J. S. Gastric cancer incidence, mortality and burden in adolescents and young adults: a time-trend analysis and comparison among China, South korea, Japan and the USA. BMJ Open. 12 , e061038. 10.1136/bmjopen-2022-061038 (2022). 35863834 10.1136/bmjopen-2022-061038 PMC9310161

22. Bai X Yi M Dong B Zheng X Wu K The global, regional, and National burden of kidney cancer and attributable risk factor analysis from 1990 to 2017 Exp. Hematol. Oncol. 2020 9 27 10.1186/s40164-020-00181-3 33005476 PMC7525971 Bai, X., Yi, M., Dong, B., Zheng, X. & Wu, K. The global, regional, and National burden of kidney cancer and attributable risk factor analysis from 1990 to 2017. Exp. Hematol. Oncol. 9 , 27. 10.1186/s40164-020-00181-3 (2020). 33005476 10.1186/s40164-020-00181-3 PMC7525971

23. Murray, C.J.L. & GBD 2021 Collaborators. Findings from the global burden of disease study 2021. Lancet 403 , 2259–2262. 10.1016/S0140-6736(24)00769-4 (2024). 10.1016/S0140-6736(24)00769-4 38762327

24. GBD 2021 Risk Factors Collaborators Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the global burden of disease study 2021 Lancet 2024 403 10440 2162 2203 10.1016/S0140-6736(24)00933-4 38762324 PMC11120204 GBD 2021 Risk Factors Collaborators. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the global burden of disease study 2021. Lancet 403 (10440), 2162–2203. 10.1016/S0140-6736(24)00933-4 (2024). 38762324 10.1016/S0140-6736(24)00933-4 PMC11120204

25. , G. B. D. D. I. C. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: A systematic analysis for the global burden of disease study 2021. Lancet 403 (2133–2161). 10.1016/S0140-6736(24)00757-8 (2024). 10.1016/S0140-6736(24)00757-8 PMC11122111 38642570

26. Wiseman M The second World Cancer Research Fund/American Institute for Cancer Research expert report Food, nutrition, physical activity, and the prevention of cancer: a global perspective Proc. Nutr. Soc. 2008 67 253 256 10.1017/S002966510800712X 18452640 Wiseman, M. & The second World Cancer Research Fund/American Institute for Cancer Research expert report. Food, nutrition, physical activity, and the prevention of cancer: a global perspective. Proc. Nutr. Soc. 67 , 253–256. 10.1017/S002966510800712X (2008). 18452640 10.1017/S002966510800712X

27. Global Burden of Disease 2019 Cancer Collaboration Cancer incidence, mortality, years of life lost, years lived with disability, and Disability-Adjusted life years for 29 Cancer groups from 2010 to 2019: A systematic analysis for the global burden of disease study 2019 JAMA Oncol. 2022 8 420 444 10.1001/jamaoncol.2021.6987 34967848 PMC8719276 Global Burden of Disease 2019 Cancer Collaboration 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: A systematic analysis for the global burden of disease study 2019. JAMA Oncol. 8 , 420–444. 10.1001/jamaoncol.2021.6987 (2022). 34967848 10.1001/jamaoncol.2021.6987 PMC8719276

28. Lin L Global, regional, and National cancer incidence and death for 29 cancer groups in 2019 and trends analysis of the global cancer burden, 1990–2019 J. Hematol. Oncol. 2021 14 197 10.1186/s13045-021-01213-z 34809683 PMC8607714 Lin, L. et al. Global, regional, and National cancer incidence and death for 29 cancer groups in 2019 and trends analysis of the global cancer burden, 1990–2019. J. Hematol. Oncol. 14 , 197. 10.1186/s13045-021-01213-z (2021). 34809683 10.1186/s13045-021-01213-z PMC8607714

29. Qi J National and subnational trends in cancer burden in China, 2005-20: an analysis of National mortality surveillance data Lancet Public. Health 2023 8 e943 e955 10.1016/S2468-2667(23)00211-6 38000889 Qi, J. et al. National and subnational trends in cancer burden in China, 2005-20: an analysis of National mortality surveillance data. Lancet Public. Health . 8 , e943–e955. 10.1016/S2468-2667(23)00211-6 (2023). 38000889 10.1016/S2468-2667(23)00211-6

30. Liu W Burden of lymphoma in China, 2006–2016: an analysis of the global burden of disease study 2016 J. Hematol. Oncol. 2019 12 115 10.1186/s13045-019-0785-7 31744509 PMC6862726 Liu, W. et al. Burden of lymphoma in China, 2006–2016: an analysis of the global burden of disease study 2016. J. Hematol. Oncol. 12 , 115. 10.1186/s13045-019-0785-7 (2019). 31744509 10.1186/s13045-019-0785-7 PMC6862726

31. GBD 2019 Demographics Collaborators. Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: A comprehensive demographic analysis for the Global Burden of Disease Study 2019. Lancet 396 , 1160–203. 10.1016/s0140-6736(20)30977-6 (2020). 10.1016/S0140-6736(20)30977-6 PMC7566045 33069325

32. GBD 2019 Diseases and Injuries Collaborators. 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. Lancet 396 , 1204–1222 10.1016/ s0140-6736(20)30925-9 (2020). 10.1016/S0140-6736(20)30925-9 PMC7567026 33069326

33. Liang X Wang J Lin B Cao X Si Y China’s outward direct investment in the united states: from the perspective of agglomeration economies PLoS One 2022 17 e0269602 10.1371/journal.pone.0269602 35687568 PMC9187097 Liang, X., Wang, J., Lin, B., Cao, X. & Si, Y. China’s outward direct investment in the united states: from the perspective of agglomeration economies. PLoS One . 17 , e0269602. 10.1371/journal.pone.0269602 (2022). 35687568 10.1371/journal.pone.0269602 PMC9187097

34. Mousa, A. M., Enk, A. H., Hassel, J. C. & Reschke, R. Immune checkpoints and cellular landscape of the tumor microenvironment in non-melanoma skin cancer (NMSC). Cells 13 , 1615 10.3390/cells13191615 (2024). 10.3390/cells13191615 PMC11475876 39404378

35. Perez MI Skin Cancer in Hispanics in the united States J. Drugs Dermatol. 2019 18 s117 120 30909356 Perez, M. I. Skin Cancer in Hispanics in the united States. J. Drugs Dermatol. 18 , s117–120 (2019). 30909356

36. Sol S Boncimino F Todorova K Waszyn SE Mandinova A Therapeutic approaches for Non-Melanoma skin cancer: standard of care and emerging modalities Int. J. Mol. Sci. 2024 25 7056 10.3390/ijms25137056 39000164 PMC11241167 Sol, S., Boncimino, F., Todorova, K., Waszyn, S. E. & Mandinova, A. Therapeutic approaches for Non-Melanoma skin cancer: standard of care and emerging modalities. Int. J. Mol. Sci. 25 , 7056. 10.3390/ijms25137056 (2024). 39000164 10.3390/ijms25137056 PMC11241167

37. Hu W Fang L Ni R Zhang H Pan G Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years BMC Cancer 2022 22 1 836 10.1186/s12885-022-09940-3 35907848 PMC9339183 Hu, W., Fang, L., Ni, R., Zhang, H. & Pan, G. Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years. BMC Cancer . 22 (1), 836. 10.1186/s12885-022-09940-3 (2022). 35907848 10.1186/s12885-022-09940-3 PMC9339183

38. Rogers HW Incidence estimate of nonmelanoma skin cancer in the united states, 2006 Arch. Dermatol. 2010 146 3 283 287 10.1001/archdermatol.2010.19 20231499 Rogers, H. W. et al. Incidence estimate of nonmelanoma skin cancer in the united states, 2006. Arch. Dermatol. 146 (3), 283–287. 10.1001/archdermatol.2010.19 (2010). 20231499 10.1001/archdermatol.2010.19

39. Wang Z Bao J Yu C Wang J Li C Secular trends of breast Cancer in China, South korea, Japan and the united states: application of the Age-Period-Cohort analysis Int. J. Environ. Res. Public. Health 2015 12 15409 15418 10.3390/ijerph121214993 26690183 PMC4690929 Wang, Z., Bao, J., Yu, C., Wang, J. & Li, C. Secular trends of breast Cancer in China, South korea, Japan and the united states: application of the Age-Period-Cohort analysis. Int. J. Environ. Res. Public. Health . 12 , 15409–15418. 10.3390/ijerph121214993 (2015). 26690183 10.3390/ijerph121214993 PMC4690929

40. Song QK Age of diagnosis of breast cancer in China: almost 10 years earlier than in the United States and the European Union Asian Pac. J. Cancer Prev. 2014 15 10021 10025 10.7314/apjcp.2014.15.22.10021 25520063 Song, Q. K. et al. Age of diagnosis of breast cancer in China: almost 10 years earlier than in the United States and the European Union. Asian Pac. J. Cancer Prev. 15 , 10021–10025. 10.7314/apjcp.2014.15.22.10021 (2014). 25520063 10.7314/apjcp.2014.15.22.10021

41. Bhandari KC Htay A Parvin ZW Murakami R Abe M Prevalence of breast Cancer screening in asia: systematic review and Meta-Analysis Asian Pac. J. Cancer Prev. 2024 25 3379 3391 10.31557/APJCP.2024.25.10.3379 39471004 PMC11711340 Bhandari, K. C., Htay, A., Parvin, Z. W., Murakami, R. & Abe, M. Prevalence of breast Cancer screening in asia: systematic review and Meta-Analysis. Asian Pac. J. Cancer Prev. 25 , 3379–3391. 10.31557/APJCP.2024.25.10.3379 (2024). 39471004 10.31557/APJCP.2024.25.10.3379 PMC11711340

42. Liao Y Status and influencing factors of knowledge, attitudes and practices relating to screening for breast and cervical cancer among rural women aged 40–65 years in China: a cross-sectional study BMJ Open. 2024 14 e080945 10.1136/bmjopen-2023-080945 39414306 PMC11481149 Liao, Y. et al. Status and influencing factors of knowledge, attitudes and practices relating to screening for breast and cervical cancer among rural women aged 40–65 years in China: a cross-sectional study. BMJ Open. 14 , e080945. 10.1136/bmjopen-2023-080945 (2024). 39414306 10.1136/bmjopen-2023-080945 PMC11481149

43. Chen, C. et al. Characteristics of breast cancer in Central China, literature review and comparison with USA. Breast . 30:208–213. (2016). 10.1016/j.breast.2016.01.004 10.1016/j.breast.2016.01.004 27017410

44. Kopans DB More than a half century of misinformation about breast Cancer screening Radiol. Clin. North. Am. 2024 62 993 1002 10.1016/j.rcl.2024.04.001 39393857 Kopans, D. B. More than a half century of misinformation about breast Cancer screening. Radiol. Clin. North. Am. 62 , 993–1002. 10.1016/j.rcl.2024.04.001 (2024). 39393857 10.1016/j.rcl.2024.04.001

45. Walker, B. et al. Does a Western lifestyle confer a higher burden of colorectal cancer? A comparison of EU15 + Countries versus global trends between 1990 and 2019. Cancers (Basel) 16 , 2277 (2024). 10.3390/cancers16122277 10.3390/cancers16122277 PMC11201493 38927980

46. Wei W Cancer registration in China and its role in cancer prevention and control Lancet Oncol. 2020 21 7 e342 e349 10.1016/S1470-2045(20)30073-5 32615118 Wei, W. et al. Cancer registration in China and its role in cancer prevention and control. Lancet Oncol. 21 (7), e342–e349. 10.1016/S1470-2045(20)30073-5 (2020). 32615118 10.1016/S1470-2045(20)30073-5

47. Lee, Y. C. et al. Association between Helicobacter pylori eradication and gastric Cancer incidence: A systematic review and Meta-analysis. Gastroenterology . 150 (5):1113–1124e5. (2016). 10.1053/j.gastro.2016.01.028 10.1053/j.gastro.2016.01.028 26836587

48. Xie L Prevalence of Helicobacter pylori infection in China from 2014–2023: A systematic review and meta-analysis World J. Gastroenterol. 2024 30 43 4636 4656 10.3748/wjg.v30.i43.4636 39575409 PMC11572641 Xie, L. et al. Prevalence of Helicobacter pylori infection in China from 2014–2023: A systematic review and meta-analysis. World J. Gastroenterol. 30 (43), 4636–4656. 10.3748/wjg.v30.i43.4636 (2024). 39575409 10.3748/wjg.v30.i43.4636 PMC11572641

49. Jiang Q Burdens of stomach and esophageal cancer from 1990 to 2019 and projection to 2030 in China: findings from the 2019 global burden of disease study J. Glob Health 2024 14 04025 10.7189/jogh.14.04025 38180951 PMC10769142 Jiang, Q. et al. Burdens of stomach and esophageal cancer from 1990 to 2019 and projection to 2030 in China: findings from the 2019 global burden of disease study. J. Glob Health . 14 , 04025. 10.7189/jogh.14.04025 (2024). 38180951 10.7189/jogh.14.04025 PMC10769142

50. Li J Chinese National clinical practice guidelines on prevention, diagnosis and treatment of early colorectal cancer Chin. Med. J. (Engl 2024 137 2017 2039 10.1097/CM9.0000000000003253 39104005 PMC11374253 Li, J. et al. Chinese National clinical practice guidelines on prevention, diagnosis and treatment of early colorectal cancer. Chin. Med. J. (Engl . 137 , 2017–2039. 10.1097/CM9.0000000000003253 (2024). 39104005 10.1097/CM9.0000000000003253 PMC11374253

51. Liu SC Zhang H Early diagnostic strategies for colorectal cancer World J. Gastroenterol. 2024 30 3818 3822 10.3748/wjg.v30.i33.3818 39351429 PMC11438623 Liu, S. C. & Zhang, H. Early diagnostic strategies for colorectal cancer. World J. Gastroenterol. 30 , 3818–3822. 10.3748/wjg.v30.i33.3818 (2024). 39351429 10.3748/wjg.v30.i33.3818 PMC11438623

52. Wang YX Wang KJ Who should be screened for colorectal cancer and how can it be prevented more effectively? World J. Gastrointest. Oncol. 2024 16 3741 3746 10.4251/wjgo.v16.i9.3741 39350975 PMC11438779 Wang, Y. X. & Wang, K. J. Who should be screened for colorectal cancer and how can it be prevented more effectively? World J. Gastrointest. Oncol. 16 , 3741–3746. 10.4251/wjgo.v16.i9.3741 (2024). 39350975 10.4251/wjgo.v16.i9.3741 PMC11438779

53. Zhang M Cancer burden variations and convergences in globalization: A comparative study on the tracheal, bronchus, and lung (TBL) and liver Cancer burdens among WHO regions from 1990 to 2019 J. Epidemiol. Glob Health 2023 13 4 696 724 10.1007/s44197-023-00144-x 37639192 PMC10686938 Zhang, M. et al. Cancer burden variations and convergences in globalization: A comparative study on the tracheal, bronchus, and lung (TBL) and liver Cancer burdens among WHO regions from 1990 to 2019. J. Epidemiol. Glob Health . 13 (4), 696–724. 10.1007/s44197-023-00144-x (2023). 37639192 10.1007/s44197-023-00144-x PMC10686938

54. Loomis D The effect of occupational exposure to welding fumes on trachea, bronchus and lung cancer: A systematic review and meta-analysis from the WHO/ILO joint estimates of the Work-related burden of disease and injury Environ. Int. 2022 170 107565 10.1016/j.envint.2022.107565 36402034 Loomis, D. et al. The effect of occupational exposure to welding fumes on trachea, bronchus and lung cancer: A systematic review and meta-analysis from the WHO/ILO joint estimates of the Work-related burden of disease and injury. Environ. Int. 170 , 107565. 10.1016/j.envint.2022.107565 (2022). 36402034 10.1016/j.envint.2022.107565

55. Yang D Liu Y Bai C Wang X Powell CA Epidemiology of lung cancer and lung cancer screening programs in China and the united States Cancer Lett. 2020 468 82 87 10.1016/j.canlet.2019.10.009 31600530 Yang, D., Liu, Y., Bai, C., Wang, X. & Powell, C. A. Epidemiology of lung cancer and lung cancer screening programs in China and the united States. Cancer Lett. 468 , 82–87. 10.1016/j.canlet.2019.10.009 (2020). 31600530 10.1016/j.canlet.2019.10.009

56. Falade-Nwulia O Oral Direct-Acting agent therapy for hepatitis C virus infection: A systematic review Ann. Intern. Med. 2017 166 9 637 648 10.7326/M16-2575 28319996 PMC5486987 Falade-Nwulia, O. et al. Oral Direct-Acting agent therapy for hepatitis C virus infection: A systematic review. Ann. Intern. Med. 166 (9), 637–648. 10.7326/M16-2575 (2017). 28319996 10.7326/M16-2575 PMC5486987

57. Ginzberg D Wong RJ Gish R Global HBV burden: guesstimates and facts Hepatol. Int. 2018 12 4 315 329 10.1007/s12072-018-9884-8 30054801 Ginzberg, D., Wong, R. J. & Gish, R. Global HBV burden: guesstimates and facts. Hepatol. Int. 12 (4), 315–329. 10.1007/s12072-018-9884-8 (2018). 30054801 10.1007/s12072-018-9884-8

58. Shi JF Is it possible to halve the incidence of liver cancer in China by 2050? Int. J. Cancer 2021 148 5 1051 1065 10.1002/ijc.33313 32997794 Shi, J. F. et al. Is it possible to halve the incidence of liver cancer in China by 2050? Int. J. Cancer . 148 (5), 1051–1065. 10.1002/ijc.33313 (2021). 32997794 10.1002/ijc.33313

59. Trabert B Chen J Devesa SS Bray F McGlynn KA International patterns and trends in testicular cancer incidence, overall and by histologic subtype, 1973–2007 Andrology 2015 3 1 4 12 10.1111/andr.293 25331326 PMC4410839 Trabert, B., Chen, J., Devesa, S. S., Bray, F. & McGlynn, K. A. International patterns and trends in testicular cancer incidence, overall and by histologic subtype, 1973–2007. Andrology 3 (1), 4–12. 10.1111/andr.293 (2015). 25331326 10.1111/andr.293 PMC4410839

60. Zhou X Trends in the global, regional, and National burden of testicular cancer from 1990 to 2019: an observational study with 30-year global data Int. J. Surg. 2024 110 8 4633 4647 10.1097/JS9.0000000000001603 38759694 PMC11325982 Zhou, X. et al. Trends in the global, regional, and National burden of testicular cancer from 1990 to 2019: an observational study with 30-year global data. Int. J. Surg. 110 (8), 4633–4647. 10.1097/JS9.0000000000001603 (2024). 38759694 10.1097/JS9.0000000000001603 PMC11325982

61. Safiri S Global, regional and National burden of cancers attributable to high fasting plasma glucose in 204 countries and territories, 1990–2019 Front. Endocrinol. (Lausanne) 2022 13 879890 10.3389/fendo.2022.879890 35966097 PMC9366927 Safiri, S. et al. Global, regional and National burden of cancers attributable to high fasting plasma glucose in 204 countries and territories, 1990–2019. Front. Endocrinol. (Lausanne) . 13 , 879890. 10.3389/fendo.2022.879890 (2022). 35966097 10.3389/fendo.2022.879890 PMC9366927

62. Xie J Global, regional, and National time trends in cancer mortality attributable to high fasting plasma glucose: an age-period cohort analysis BMC Public. Health 2023 23 1361 10.1186/s12889-023-16076-x 37454041 PMC10349485 Xie, J. et al. Global, regional, and National time trends in cancer mortality attributable to high fasting plasma glucose: an age-period cohort analysis. BMC Public. Health . 23 , 1361. 10.1186/s12889-023-16076-x (2023). 37454041 10.1186/s12889-023-16076-x PMC10349485