Global, regional, and national burden of early-onset kidney cancer in adolescents and young adults aged 15-39 years from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021

Global, regional, and national burden of early-onset kidney cancer in adolescents and young adults aged 15-39 years from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Global, regional, and national burden of early-onset kidney cancer in adolescents and young adults aged 15-39 years from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021 Chi Zhang, Lei He, Chaojie Xu, Ziyang Guo, Yihan Wang, Kaiwei Yang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7464519/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Kidney cancer occurring in adolescents and young adults is increasingly recognized as a significant global health concern. However, its long-term epidemiological patterns remain underexplored. Aim To evaluate global, regional, and national burdens and trends of early-onset kidney cancer (EOKC) from 1990 to 2021 to support the development of targeted prevention and intervention strategies. Methods Data were obtained from the Global Burden of Disease (GBD) 2021 database. Analyses focused on individuals aged 15–39 years, assessing global and regional incidence, mortality, and disability-adjusted life years (DALYs) using age-standardized rates (ASRs) to adjust for demographic variability. Temporal trends were assessed using estimated annual percentage change (EAPC) and average annual percentage change (AAPC). The Bayesian age-period-cohort (BAPC) model was employed for forecasting. Results Globally, 17,622 new EOKC cases were reported in 2021, with the highest incidence in Southern Latin America and the largest case numbers in East Asia. From 1990 to 2021, global EOKC incidence increased by 31.6%, driven primarily by high and middle SDI regions. DALYs showed an inverted U-shaped relationship with SDI, peaking in moderately developed settings. High body mass index was the leading attributable risk factor, followed by tobacco use and occupational exposures. BAPC projections suggest continued increases in incidence but declining mortality and DALYs by 2035. Conclusions EOKC poses a growing and uneven global burden, particularly in rapidly developing regions. Targeted prevention strategies addressing modifiable risk factors and improved resource allocation are essential to mitigate future impact. Kidney cancer Adolescents young adults Obesity Epidemiological trends Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Kidney cancer constitutes a major global health burden, ranking among the ten most common malignancies worldwide, with both incidence and mortality exhibiting sustained increases over recent decades [ 1 ]. Although historically associated with older adults—peaking between ages 60 and 70—emerging epidemiological data highlight a rising prevalence among adolescents and young adults (AYAs) [ 2 , 3 ]. This demographic shift necessitates a nuanced understanding of disease burden and clinical characteristics in younger populations. Early-onset kidney cancer (EOKC) demonstrates distinct epidemiological, genetic, and pathological profiles relative to the late-onset cases [ 4 ]. Studies have shown that it is more frequently diagnosed at localized stages, often associated with smaller, organ-confined tumors, and a predominance of hereditary subtypes [ 5 , 6 ]. Compared to older individuals, patients with EOKC tend to have more favorable prognoses. The Global Burden of Disease (GBD) study reports a substantial increase in EOKC incidence, with approximately 8,600 additional cases recorded in 2021 compared to 1990 [ 7 ]. This trend may reflect both advances in diagnostic practices and the escalating prevalence of modifiable risk factors, particularly obesity. In 2021, elevated body mass index (BMI) was responsible for an estimated 16.49% of global kidney cancer mortality and 16.19% of related DALYs. Additional contributors include environmental toxins and genetic susceptibilities, which collectively exacerbate mortality risk and economic burden [ 8 , 9 ]. The growing impact of EOKC positions it as a priority in global non-communicable disease control strategies targeting AYAs. Early detection remains pivotal to reducing disease burden and optimizing clinical outcomes [ 10 ]. The epidemiology of kidney cancer is intricately linked to global health transitions, notably the increasing prevalence of metabolic risk factors [ 11 ]. As these factors continue to evolve, continuous reassessment of EOKC trends is imperative to inform evidence-based prevention and long-term management strategies [ 12 ]. Despite increasing awareness, longitudinal analyses of global EOKC trends remain limited [ 13 ]. To address this gap, the present study leveraged data from the GBD 2021 framework to systematically evaluate EOKC burden from 1990 to 2021 and forecast future trends. Insights derived from these analyses support the development of targeted prevention and therapeutic approaches aimed at mitigating the rising health impact of EOKC among AYAs. 2. Methods 2.1 Data Sources This analysis utilized data from the GBD 2021 database, which offers comprehensive estimates of the global and regional burden of 371 diseases and injuries, and 88 risk factors across 204 countries and territories from 1990 to 2021. Kidney cancer classification followed the International Classification of Diseases (ICD) coding, with C64 (malignant neoplasm of the kidney, excluding renal pelvis) and C65 (malignant neoplasm of the renal pelvis) as defined codes [ 14 ]. Given the rarity of kidney cancer in pediatric populations [ 15 ], the study focused on cases with onset between ages 15–39, designated as EOKC. Extracted metrics included incidence, mortality, and disability-adjusted life years (DALYs), stratified by age, sex, and geographic region, along with DALYs attributable to specific risk factors. To ensure comparability across regions and time periods, age-standardized rates (ASRs) were calculated using the Segi-Doll world standard population [ 16 ]. This standardization minimizes the confounding effects of demographic shifts, particularly aging, and enhances interpretability of temporal trends. All data were obtained via the Global Health Data Exchange (GHDx) platform ( http://ghdx.healthdata.org/gbd-results-tool ). Definitions of key indicators and methodological parameters are detailed in Supplementary Table 1 . 2.2 Global and Regional Burden Analysis To assess the global distribution and regional disparities in the burden of EOKC, world maps were generated, and region-specific comparative analyses were performed. Data were aggregated according to the 21 geographical regions defined in the GBD study. Visualization of incidence, mortality, and DALYs was conducted using R software with the ggplot2 and sf packages. For a more detailed analysis, data were stratified into five age groups (15–19, 20–24, 25–29, 30–34, 35–39 years) for both males and females. This stratification provided insights into how the impact of EOKC differs across distinct segments of the young adult population. 2.3 Temporal Trend Analysis Temporal trends in incidence, mortality, and DALYs were assessed using estimated annual percentage change (EAPC) and average annual percent change (AAPC). EAPC was derived from joinpoint regression to estimate annual trend slopes over defined periods, while AAPC represented a weighted average of EAPCs over multiple intervals, capturing overarching long-term trends. Trend analyses were conducted using the Segment and broom R packages, with 95% confidence intervals (CIs) employed to determine statistical significance. 2.4 Socio-demographic Index (SDI) Analysis SDI data were utilized to evaluate the influence of socioeconomic development on the burden of EOKC, with higher scores indicating greater development [ 17 ]. Age-standardized DALY rates (ASDRs) were calculated across the SDI continuum to characterize the association between development level and disease burden. Based on SDI values, countries and territories were stratified into quintiles: high, high-middle, middle, low-middle, and low SDI ( Supplementary Table 2 ). Data manipulation and visualization were performed using the dplyr and ggplot2 R packages, while Spearman’s rank correlation was applied to assess the monotonic relationship between SDI and ASDR. Annual SDI values from 1990 to 2021 are presented in Supplementary Table 3 . 2.5 Attributable Risk Factors Analysis DALYs were employed as a composite measure of disease burden, integrating years of life lost (YLL) due to premature mortality and years lived with disability (YLD) resulting from illness or impairment. Attributable DALYs quantify the disease burden linked to specific risk factors, thereby elucidating each factor’s contribution to the overall EOKC burden. Risk-attributable DALYs were estimated using data from the GBD 2021 database. Forest plots, generated via the ggplot2 R package, visualized the proportional impact of individual risk factors on total DALYs. 2.6 Bayesian Age-Period-Cohort (BAPC) Model for Forecasting To project future EOKC burden, the BAPC model was implemented using the INLA and BAPC R packages [ 18 ]. This model accounted for age, period, and cohort effects to estimate and forecast trends in age-standardized incidence rate (ASIR), mortality rate (ASMR), and ASDR through 2035. The BAPC framework incorporated demographic and temporal dynamics, offering a statistically rigorous approach for anticipating the trajectory of EOKC. 2.7 Statistical Analysis All statistical analyses and visualizations were conducted using R software. Descriptive statistics were computed for key variables, with results presented as means accompanied by 95% uncertainty intervals (UIs). Statistical tests were two-sided, and a p-value < 0.05 was considered statistically significant. 3. Results 3.1 Global and regional distribution of EOKC in 2021 Based on GBD 2021 estimates, 17,622 new cases of EOKC were reported globally in 2021, with East Asia accounting for the largest share of incident cases. The global ASIR was 0.58 per 100,000, with the highest incidence observed in Southern Latin America (3.83 per 100,000) and the lowest in Oceania (0.07 per 100,000). In terms of mortality, an estimated 3,261 deaths were attributed to EOKC in 2021, with East Asia reporting the highest number of fatalities. The global ASMR was 0.11 per 100,000, ranging from 0.02 per 100,000 in Oceania to 0.38 per 100,000 in Southern Latin America. DALYs reached 197,665 years in 2021, with East Asia contributing the largest proportion. The global ASDR was 6.50 per 100,000, ranging from 1.36 per 100,000 in Oceania to 24.93 per 100,000 in Southern Latin America. A complete breakdown of ASIRs, ASMRs, and ASDRs across 204 countries and territories is presented in Fig. 1 , with detailed values summarized in Table 1 . Age stratification revealed distinct patterns of EOKC incidence (Fig. 2 A), with individuals aged 35–39 consistently representing the highest proportion of cases, indicating that the disease predominantly affects the older segment of the adolescent and young adult population. Gender-specific analysis identified clear disparities across global and regional levels (Fig. 2 B). Males exhibited a global ASIR of 0.67 per 100,000—approximately 1.43 times higher than that of females (0.47 per 100,000)—suggesting a male predominance in EOKC incidence. The relationship between age and gender further demonstrated an age-dependent rise in EOKC incidence, particularly after age 25 (Fig. 2 C). Comparative analyses between 1990 and 2021 highlighted an overall upward trajectory in global EOKC incidence, although regional patterns varied substantially (Fig. 2 D). 3.2 Temporal trends in EOKC from 1990 to 2021 From 1990 to 2021, the global incidence of EOKC followed a sustained upward trajectory, with a pronounced acceleration post-2000 and a modest plateauing after 2018. In contrast, global mortality rates and DALY burdens associated with EOKC declined through the early 2000s, followed by a mild but consistent downward trend in subsequent years (Fig. 3 A). The temporal percentage change in EOKC incidence across 204 countries and territories is illustrated in Supplementary Fig. 1A , revealing a global increase of 31.6% since 1990. EAPC values were calculated for each country and visualized in Supplementary Fig. 1B . On average, global incidence has increased by approximately 1% annually (Fig. 3 B). East Asia recorded the highest EAPC (3.88), whereas Oceania showed the slowest rise (EAPC, 0.09). Regions with high and middle SDI scores experienced the most rapid increases in incidence, while low SDI regions exhibited comparatively slower growth. Analysis of AAPC revealed consistent long-term trends across regions (Fig. 3 C; Supplementary Fig. 1C ). Comprehensive statistics on percentage change, EAPC, and AAPC by region are summarized in Supplementary Table 4 . Stratified analysis by SDI level confirmed a general upward trend in EOKC incidence across all five SDI quintiles from 1990 to 2021. High and high-middle SDI regions demonstrated the most substantial increases, while low SDI regions remained relatively stable (Fig. 3 D). Age-specific trends revealed notable heterogeneity, with the 35–39 year cohort showing the highest growth rate in incidence (Fig. 3 E). 3.3 Relationship between EOKC disease burden and SDI In assessing the relationship between EOKC burden and socio-demographic development, ASDRs were compared across 204 countries stratified by SDI levels in 2021. A positive overall correlation was observed between SDI and ASDR, with higher-SDI countries generally exhibiting greater EOKC burden (Spearman’s correlation coefficient, r = 0.466, p < 0.01). Notably, ASDR followed an inverted U-shaped distribution across the SDI spectrum, peaking in countries with moderate SDI values and declining in both low- and high-SDI settings (Fig. 4 A). This non-linear pattern persisted at the regional level, as evidenced by a similar inverted U-shaped trend across the 21 regions (Spearman’s correlation coefficient, r = 0.595, p < 0.01) (Fig. 4 B). The association between EAPC and both DALYs and SDI was also examined (Fig. 4 C). No significant correlation was found between EAPC and DALYs (Spearman’s correlation coefficient, r = 0.017, p = 0.81), indicating that the pace of change in EOKC incidence does not align closely with existing disease burden levels. However, a significant negative correlation was identified between EAPC and SDI (r = − 0.39, p < 0.01), suggesting that higher levels of social development are associated with slower recent increases in incidence rates. 3.4 Proportion of DALYs attributable to risk factors In 2021, the distribution of EOKC DALYs attributable to specific risk factors indicated substantial contributions from high BMI, tobacco use, and occupational risk (Fig. 5 A; Supplementary Table 5 ). High BMI was the leading global risk factor, responsible for an estimated 16.2% (95% UI: 6.3–26.1) of DALYs. Tobacco use accounted for approximately 1.5% (95% UI: 0.9–2.1), while occupational exposure to trichloroethylene contributed about 0.1% (95% UI: 0.0–0.1). Temporal analysis from 1990 to 2021 (Fig. 5 B) demonstrated a pronounced global increase in the burden attributable to high BMI. By contrast, the contribution of tobacco use declined steadily over time, and occupational risk levels remained largely unchanged. Marked regional variation was observed in the influence of these risk factors (Fig. 5 C). 3.5 Bayesian Age-Period-Cohort Model for predictions of EOKC burden Projections from the Bayesian APC model suggest a continued escalation in EOKC incidence over the next decade ( Supplementary Fig. 2A ). In contrast, both the ASMR and ASDR have declined steadily over the past thirty years, a trend anticipated to persist and further intensify in the post-2021 period ( Supplementary Fig. 2B and 2C ). 4. Discussion This study presents a detailed evaluation of EOKC among individuals aged 15–39 years, offering global, regional, and national perspectives spanning 1990 to 2021. By concentrating on AYAs—a demographic historically underrepresented in oncology research—this analysis contributes critical insights into the shifting epidemiological landscape of kidney cancer in younger populations. The upward trajectory in incidence within this age group necessitates the development and implementation of age-specific strategies that effectively address the emerging burden. Regional, sex, and age differences in the burden of early-onset kidney cancer Analysis of GBD 2021 data uncovered pronounced heterogeneity in EOKC incidence, mortality, and DALYs across regions, sexes, and age brackets. In 2021, East Asia bore the highest absolute burden, while Southern Latin America exhibited the highest standardized rates, contrasting with consistently low levels in Oceania. These regional disparities align with previous evidence suggesting that kidney cancer burden tends to be elevated in high-income or rapidly developing regions, likely driven by variations in lifestyle, environmental exposures, healthcare access, and screening infrastructure [ 19 , 20 ]. The distribution of EOKC burden within the 15–39 age range appeared skewed toward older subgroups, likely reflecting cumulative exposure to metabolic and environmental risk factors. Male predominance in EOKC incidence may stem from a higher prevalence of modifiable risk factors among men, including tobacco and alcohol use, suboptimal dietary habits, and increased occupational exposure to nephrotoxic agents [ 21 ]. Moreover, biological mechanisms, particularly the influence of androgen receptors, have been implicated in the pathogenesis of kidney cancer [ 22 ]. The gender gap widens notably after age 25, suggesting a compounding effect of age-related hormonal, behavioral, and genetic risk factors [ 23 ]. Temporal trend in the burden of early-onset kidney cancer The persistent global rise in EOKC incidence over the past three decades likely stems from a complex interplay of environmental and biological factors. Rapid urbanization and industrial expansion—especially in high and middle SDI regions—have significantly increased population-level exposure to environmental carcinogens, including airborne pollutants, heavy metals, and endocrine-disrupting compounds, all of which are implicated in renal carcinogenesis [ 24 ]. Concurrently, escalating prevalence of obesity, metabolic syndrome, and sedentary lifestyles among AYAs contributes to systemic inflammation and metabolic dysregulation, creating a pro-tumorigenic environment [ 25 ]. Enhanced access to imaging technologies and improved healthcare availability have also facilitated the incidental detection of asymptomatic renal tumors, further contributing to rising incidence figures [ 26 ]. In contrast to the upward incidence trend, the sustained decline in EOKC-related mortality and DALYs over the same period reflects considerable progress in clinical care. Key drivers include earlier detection, broader application of minimally invasive surgical techniques, advancements in targeted therapies, and the growing adoption of multidisciplinary treatment approaches [ 27 ]. Marked regional variation in the pace of EOKC incidence escalation further highlights the influence of socioeconomic development, environmental exposure, and healthcare infrastructure. The more pronounced incidence increases in high and middle SDI regions, relative to low SDI counterparts, may in part be driven by superior diagnostic infrastructure and surveillance systems that enable earlier and more frequent detection of renal malignancies [ 28 ]. Sociodemographic differences in the burden of early-onset kidney cancer The inverted U-shaped association between national EOKC burden and socio-demographic development may reflect a transitional phase wherein rising income and development initially enhance access to healthcare and diagnostic capabilities but concurrently introduce population-level exposures that elevate cancer risk. These exposures include urbanization, increasingly sedentary lifestyles, widespread consumption of processed foods, and a growing prevalence of obesity and metabolic disorders [ 29 – 32 ]. Despite the rising incidence of EOKC in high SDI regions, a corresponding increase in DALYs has not been observed. This decoupling likely results from the presence of mature healthcare infrastructures that facilitate earlier detection, improve treatment outcomes, and reduce YLL due to premature mortality [ 33 ]. These observations highlight the critical role of robust health systems not only in cancer detection but also in mitigating disease burden through improved survival and long-term management [ 34 ]. The significant negative correlation between EAPC and SDI suggests that as nations advance socioeconomically, the rate of increase in EOKC incidence tends to decelerate. This inverse trend may be attributed to enhanced healthcare infrastructure, widespread health education, and the adoption of preventive strategies that collectively mitigate key risk factors such as obesity, tobacco use, and environmental pollution [ 35 ]. Risk factors in the burden of early-onset kidney cancer High BMI, tobacco use, and occupational exposures emerged as the leading contributors to the global burden of EOKC. The dominant role of high BMI across all socio-demographic strata underscores the pervasive impact of the global obesity epidemic and its direct oncogenic implications, particularly within high-income regions [ 36 – 38 ]. In High-income North America, for instance, more than a quarter of EOKC-related DALYs were attributable to elevated BMI. This strong association is supported by multiple biological mechanisms, including elevated pro-inflammatory cytokines (e.g., TNF-α, IL-6), activation of the insulin-like growth factor-1 (IGF-1) signaling pathway, dysregulated adipokine secretion and increased estrogen synthesis via aromatase activity in adipose tissue [ 39 ]. Although smoking prevalence has declined overall, its residual impact continues to shape kidney cancer burden, particularly in high-income settings [ 40 ]. In low socio-demographic regions, observed reductions in tobacco-attributable burden may reflect the cumulative effect of targeted cessation programs and broader public health initiatives aimed at reducing tobacco consumption [ 41 ]. These findings underscore the necessity of preserving and strengthening tobacco control measures as a means to further mitigate the preventable burden of kidney cancer across diverse socio-economic contexts. Occupational exposures accounted for a relatively small proportion of the measured global EOKC burden. This low figure may reflect systematic under-detection or under-reporting of occupational cancers, particularly in low and middle socio-demographic regions, where regulatory oversight is often limited, exposure monitoring infrastructure remains inadequate, and data on occupational carcinogens are frequently incomplete or inaccessible [ 42 ]. Prioritizing occupational cancer prevention through regulatory reforms, exposure assessment, and protective interventions is essential to address region-specific environmental and workplace-related cancer risks. Projected Trends and Strategic Implications Projections derived from the BAPC model forecast a continued rise in the incidence of EOKC, accompanied by sustained improvements in mortality and DALY outcomes. This divergence highlights a dual challenge in disease control: the increasing burden of diagnosis and surveillance, alongside the imperative to preserve and enhance advances in clinical outcomes. Addressing this challenge requires a multifaceted and adaptive strategy encompassing both upstream prevention and downstream clinical care. This effort necessitate comprehensive public health programs, including school-based health education, nutritional initiatives, urban planning that facilitates active lifestyles, and robust regulatory frameworks to limit harmful exposures—particularly in rapidly urbanizing, high-risk settings. Concurrently, investment in cancer surveillance infrastructure is essential to support accurate case detection, timely diagnosis, and dynamic monitoring of epidemiological trends at national and regional levels [ 43 ]. Given the higher prevalence of hereditary subtypes (e.g., von Hippel–Lindau, Birt–Hogg–Dubé, and fumarate hydratase deficiency) in early-onset cases, genetic counseling and family screening may be warranted [ 44 ]. Clinically, maintaining and expanding access to advanced treatment modalities—such as targeted therapies, immunotherapies, precision oncology, and minimally invasive surgical techniques—will be vital for sustaining declines in mortality and disability associated with EOKC [ 45 , 46 ]. Multidisciplinary management approaches should be reinforced, especially for younger patients who face distinct survivorship challenges. These include long-term follow-up for late treatment effects, psychosocial support, fertility preservation, and integration of survivorship care into standard oncology practice [ 47 ]. Limitations Our study had several limitations. Firstly, this study relies on the GBD 2021 database, whose estimates are based on national cancer registries, death reports, and modeling projections. For low- to medium SDI regions, due to incomplete cancer registries or missing data, the results may be subject to uncertainty and the risk of underestimation or overestimation. Secondly, The analysis only includes quantifiable risk factors within the GBD framework (e.g., BMI, smoking, occupational exposure), and does not incorporate detailed indicators related to genetics (e.g., VHL, FH mutations), family history, dietary patterns, or environmental pollution. Therefore, it cannot fully elucidate the etiology of early-onset kidney cancer. Thirdly, we primarily relied on modelling processes for the estimates in this study, and the choice of models and parameter settings could have influenced the results. 5. Conclusions Over the past 30 years, EOKC has exhibited a persistent and concerning increase in incidence and associated burden. Stark disparities across geographic regions, sexes, and age groups—coupled with the influence of socio-demographic factors—demand urgent, targeted public health responses and strategic resource mobilization. A comprehensive, integrated framework is imperative to curtail the growing public health and socioeconomic impact of EOKC globally. Abbreviations AAPC (Average Annual Percent Change) APC (Age-Period-Cohort) ASDR (Age-Standardized Disability-Adjusted Life Years Rate) ASIR (Age-Standardized Incidence Rate) ASMR (Age-Standardized Mortality Rate) AYA (Adolescents and Young Adults) BAPC (Bayesian Age-Period-Cohort), BMI (Body Mass Index) CIs (Confidence Intervals), DALYs (Disability-Adjusted Life Years) EAPC (Estimated Annual Percentage Change) EOKC (Early-Onset Kidney Cancer), GBD (Global Burden of Disease) GHDx (Global Health Data Exchange) ICD (International Classification of Diseases) IGF-1 (Insulin-like Growth Factor 1), IL-6 (Interleukin-6) INLA (Integrated Nested Laplace Approximation) SDI (Socio-Demographic Index) TNF-α (Tumor Necrosis Factor Alpha) UI (Uncertainty Interval) WHO (World Health Organization) YLD (Years Lived with Disability) YLL (Years of Life Lost) Declarations Acknowledgements We would like to thank the researchers and participants of the GBD. Funding This research was funded by the National Natural Science Foundation of China (82273135) and the National Key R&D Program of China (2023YFC2415500) . Author information Chi Zhang and Lei He made equal contributions. Authors and Affiliations Department of Urology, Peking University First Hospital, Peking University, Beijing 100035, China. Chi Zhang, Lei He, Chaojie Xu, Ziyang Guo, Yihan Wang, Kaiwei Yang, Han Hao & Lin Yao. Contributions Chi Zhang and Lei He analyzed the data, performed the statistical analyses and drafted the manuscript. Chaojie Xu, Ziyang Guo and Yihan Wang collected the related references and participated in discussion. Lin Yao, Han Hao and Kaiwei Yang conceived and designed this project, and revised the manuscript. All authors read and approved the final manuscript. Corresponding authors Correspondence to Lin Yao ( [email protected] ), Han Hao ( [email protected] ) and Kaiwei Yang ( [email protected] ). Competing interests The authors declare that they have no competing interests. Ethics approval and consent to participate This study adhered to the Helsinki Declaration (2013 revision). This study was a retrospective, observational cohort analysis based entirely on publicly available, therefore ethical approval and informed consent were waived. Consent for publication Not applicable. Data Availability All data used in the study were from the publicly available GBD database (https://www.ncbi.nlm.nih.gov/gbd/). Informed consent forms are not required for patient data extracted from public databases. Clinical trial number: not applicable. References Zi H, Liu M-Y, Luo L-S, et al. Global burden of benign prostatic hyperplasia, urinary tract infections, urolithiasis, bladder cancer, kidney cancer, and prostate cancer from 1990 to 2021. Mil Med Res . 2024;11(1):64. doi:10.1186/s40779-024-00569-w Cirillo L, Innocenti S, Becherucci F. Global epidemiology of kidney cancer. 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Global trends and projections of occupational trichloroethylene (TCE) exposure-associated kidney cancer: Insights of the Global Burden of Disease (GBD) Study 2021 from 1990 to 2021 and prediction to 2050. Ecotoxicol Environ Saf . 2024;287:117252. doi:10.1016/j.ecoenv.2024.117252 Platz EA. Reducing Cancer Burden in the Population: An Overview of Epidemiologic Evidence to Support Policies, Systems, and Environmental Changes. Epidemiol Rev . 2017;39(1)doi:10.1093/epirev/mxx009 Shuch B, Vourganti S, Ricketts CJ, et al. Defining early-onset kidney cancer: implications for germline and somatic mutation testing and clinical management. J Clin Oncol. 2014;32(5):431-437. doi:10.1200/JCO.2013.50.8192 Barata PC, Rini BI. Treatment of renal cell carcinoma: Current status and future directions. CA Cancer J Clin . 2017;67(6):507-524. doi:10.3322/caac.21411 Wang Y, Suarez ER, Kastrunes G, et al. Evolution of cell therapy for renal cell carcinoma. Mol Cancer . 2024;23(1):8. doi:10.1186/s12943-023-01911-x Li Z, Xu H, Yu L, et al. Patient-derived renal cell carcinoma organoids for personalized cancer therapy. Clin Transl Med . 2022;12(7):e970. doi:10.1002/ctm2.970 Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.xlsx SupplementaryTable1.xlsx SupplementaryTable2.xlsx SupplementaryTable3.xlsx SupplementaryTable4.xlsx SupplementaryTable5.xlsx SupplementaryFigure1.tif SupplementaryFigure2.tif Additionalfile.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7464519","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":530668431,"identity":"0999ba1b-2f31-4e23-8924-18fa4c418e0d","order_by":0,"name":"Chi 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12:32:04","extension":"png","order_by":37,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":297304,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/434b76890840a1077ee59a4a.png"},{"id":93777222,"identity":"9a7dbe0b-27ad-48ab-a723-59db07e63e9e","added_by":"auto","created_at":"2025-10-17 12:40:04","extension":"xml","order_by":38,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":117486,"visible":true,"origin":"","legend":"","description":"","filename":"3c57fb12d316466380c609d93c507a4c1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/433b88674413a45d0954583c.xml"},{"id":93778778,"identity":"cfaed693-16e3-43ff-803e-e4056bfaae52","added_by":"auto","created_at":"2025-10-17 12:48:04","extension":"html","order_by":39,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":129423,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/d164aaac256269a35d1a5ff1.html"},{"id":93775550,"identity":"7b028fa5-760c-4e5d-a2ea-ce67a796221f","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":4482596,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal distribution of EOKC across 204 countries and territories in 2021. (A) Age-standardized incidence rate (ASIR); (B) Age-standardized mortality rate (ASMR); (C) Age-standardized disability-adjusted life years rate (ASDR). EOKC: early-onset kidney cancer; DALYs: disability-adjusted life years.\u003c/p\u003e","description":"","filename":"Figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/3f417737ab8cf271fa4d1b92.jpg"},{"id":93775552,"identity":"9cd9c71e-a19c-4724-aa07-031dfb21b3fc","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5443440,"visible":true,"origin":"","legend":"\u003cp\u003eVariation in EOKC incidence by age group, sex, and time period. (A) Age-specific incidence across 21 GBD regions in 2021; (B) Sex-specific incidence across 21 GBD regions in 2021; (C) Incidence by combined age and sex subgroups; (D) Temporal changes in EOKC incidence from 1990 to 2021. EOKC: early-onset kidney cancer.\u003c/p\u003e","description":"","filename":"Figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/9fd2032216814efe9ddc2fd2.jpg"},{"id":93775553,"identity":"570b4746-3725-445f-bdbd-66952d557e3b","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4355026,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal dynamics of EOKC burden from 1990 to 2021. (A) Global trends in incidence, mortality, and DALYs; (B) EAPC in incidence by SDI levels and regions; (C) AAPC in incidence by SDI levels and regions; (D) Age-specific trends in EOKC incidence; (E) Comparative incidence trajectories across SDI categories. EOKC: early-onset kidney cancer; DALYs: disability-adjusted life years; EAPC: estimated annual percentage change; AAPC: average annual percent change.\u003c/p\u003e","description":"","filename":"Figure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/de615794d0a70324bdff8abc.jpg"},{"id":93778774,"identity":"a7c615b4-36ed-4019-8587-63cd4b2cb58c","added_by":"auto","created_at":"2025-10-17 12:48:03","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5964947,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between EOKC burden and socio-demographic development. (A) DALYs versus SDI across 204 countries; (B) DALYs versus SDI in global and regional contexts. EOKC: early-onset kidney cancer; SDI: socio-demographic index; DALYs: disability-adjusted life years.\u003c/p\u003e","description":"","filename":"Figure4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/6799712a766a336d44f33472.jpg"},{"id":93775559,"identity":"09a57cb4-1a1a-4572-9992-293190ccde3f","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3415983,"visible":true,"origin":"","legend":"\u003cp\u003eRisk factor attribution for EOKC DALYs across regions and over time. (A) Proportional DALY contributions of three major risk factors: high body mass index (yellow), occupational exposures (blue), and tobacco use (gray); (B) Temporal trends in risk factor-associated EOKC burden from 1990 to 2021; (C) Regional variation in DALYs contributions by risk factor. EOKC: early-onset kidney cancer; SDI: socio-demographic index; DALYs: disability-adjusted life years.\u003c/p\u003e","description":"","filename":"Figure5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/38c073d0fa176d4fce2c2ca7.jpg"},{"id":96366586,"identity":"e2f76652-2442-416b-b5e7-1db811084890","added_by":"auto","created_at":"2025-11-20 10:11:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":24733458,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/02d25436-be38-4be6-a413-7a7530946aca.pdf"},{"id":93775546,"identity":"9808d400-3d91-4be5-bdca-7eca357d782e","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13843,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/c66f338c0536a326906e9787.xlsx"},{"id":93775548,"identity":"69ffe8dd-0358-4dce-9895-6789677d970f","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10950,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/0cfce837e7fcf3a833210501.xlsx"},{"id":93777201,"identity":"7be941cb-9740-4a35-a95d-70dbe9cdc697","added_by":"auto","created_at":"2025-10-17 12:40:03","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":9550,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/9d3e8bb1f92ea39b63b09147.xlsx"},{"id":93777205,"identity":"0756ce3c-71b1-4d95-b8f1-bf597c1fc839","added_by":"auto","created_at":"2025-10-17 12:40:03","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2122778,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/0057882d94058bb083225a2b.xlsx"},{"id":93778775,"identity":"06f4fe34-d407-46c1-9fc3-80e6343862df","added_by":"auto","created_at":"2025-10-17 12:48:03","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":13023,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/e7151ba88c1cc332b3df20be.xlsx"},{"id":93775602,"identity":"85bf2fbb-dff8-4da1-a7ad-d8742c78a3aa","added_by":"auto","created_at":"2025-10-17 12:32:04","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":8490943,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/2d8b34b2fd069d7b46fe1d9a.xlsx"},{"id":93778780,"identity":"6fe037e6-244d-40f9-97dd-7b7c816bedf9","added_by":"auto","created_at":"2025-10-17 12:48:04","extension":"tif","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":4237252,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/558bb980ff3dd793edb12d7f.tif"},{"id":93778776,"identity":"31edf49e-a218-4a61-96db-3dcef4855ba5","added_by":"auto","created_at":"2025-10-17 12:48:03","extension":"tif","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":2992186,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/2d26d4e5f2b0c3a1e65627b2.tif"},{"id":93775564,"identity":"51404cd8-3b2f-45b5-a18e-22bfc256ec51","added_by":"auto","created_at":"2025-10-17 12:32:03","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":14569,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-7464519/v1/b517000546413b9ec48238bb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global, regional, and national burden of early-onset kidney cancer in adolescents and young adults aged 15-39 years from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eKidney cancer constitutes a major global health burden, ranking among the ten most common malignancies worldwide, with both incidence and mortality exhibiting sustained increases over recent decades [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although historically associated with older adults\u0026mdash;peaking between ages 60 and 70\u0026mdash;emerging epidemiological data highlight a rising prevalence among adolescents and young adults (AYAs) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This demographic shift necessitates a nuanced understanding of disease burden and clinical characteristics in younger populations.\u003c/p\u003e\u003cp\u003eEarly-onset kidney cancer (EOKC) demonstrates distinct epidemiological, genetic, and pathological profiles relative to the late-onset cases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Studies have shown that it is more frequently diagnosed at localized stages, often associated with smaller, organ-confined tumors, and a predominance of hereditary subtypes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Compared to older individuals, patients with EOKC tend to have more favorable prognoses. The Global Burden of Disease (GBD) study reports a substantial increase in EOKC incidence, with approximately 8,600 additional cases recorded in 2021 compared to 1990 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This trend may reflect both advances in diagnostic practices and the escalating prevalence of modifiable risk factors, particularly obesity. In 2021, elevated body mass index (BMI) was responsible for an estimated 16.49% of global kidney cancer mortality and 16.19% of related DALYs. Additional contributors include environmental toxins and genetic susceptibilities, which collectively exacerbate mortality risk and economic burden [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The growing impact of EOKC positions it as a priority in global non-communicable disease control strategies targeting AYAs. Early detection remains pivotal to reducing disease burden and optimizing clinical outcomes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The epidemiology of kidney cancer is intricately linked to global health transitions, notably the increasing prevalence of metabolic risk factors [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As these factors continue to evolve, continuous reassessment of EOKC trends is imperative to inform evidence-based prevention and long-term management strategies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite increasing awareness, longitudinal analyses of global EOKC trends remain limited [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To address this gap, the present study leveraged data from the GBD 2021 framework to systematically evaluate EOKC burden from 1990 to 2021 and forecast future trends. Insights derived from these analyses support the development of targeted prevention and therapeutic approaches aimed at mitigating the rising health impact of EOKC among AYAs.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data Sources\u003c/h2\u003e\u003cp\u003eThis analysis utilized data from the GBD 2021 database, which offers comprehensive estimates of the global and regional burden of 371 diseases and injuries, and 88 risk factors across 204 countries and territories from 1990 to 2021. Kidney cancer classification followed the International Classification of Diseases (ICD) coding, with C64 (malignant neoplasm of the kidney, excluding renal pelvis) and C65 (malignant neoplasm of the renal pelvis) as defined codes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Given the rarity of kidney cancer in pediatric populations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], the study focused on cases with onset between ages 15\u0026ndash;39, designated as EOKC. Extracted metrics included incidence, mortality, and disability-adjusted life years (DALYs), stratified by age, sex, and geographic region, along with DALYs attributable to specific risk factors. To ensure comparability across regions and time periods, age-standardized rates (ASRs) were calculated using the Segi-Doll world standard population [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This standardization minimizes the confounding effects of demographic shifts, particularly aging, and enhances interpretability of temporal trends. All data were obtained \u003cem\u003evia\u003c/em\u003e the Global Health Data Exchange (GHDx) platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ghdx.healthdata.org/gbd-results-tool\u003c/span\u003e\u003cspan address=\"http://ghdx.healthdata.org/gbd-results-tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Definitions of key indicators and methodological parameters are detailed in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Global and Regional Burden Analysis\u003c/h2\u003e\u003cp\u003eTo assess the global distribution and regional disparities in the burden of EOKC, world maps were generated, and region-specific comparative analyses were performed. Data were aggregated according to the 21 geographical regions defined in the GBD study. Visualization of incidence, mortality, and DALYs was conducted using R software with the ggplot2 and sf packages. For a more detailed analysis, data were stratified into five age groups (15\u0026ndash;19, 20\u0026ndash;24, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;39 years) for both males and females. This stratification provided insights into how the impact of EOKC differs across distinct segments of the young adult population.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Temporal Trend Analysis\u003c/h2\u003e\u003cp\u003eTemporal trends in incidence, mortality, and DALYs were assessed using estimated annual percentage change (EAPC) and average annual percent change (AAPC). EAPC was derived from joinpoint regression to estimate annual trend slopes over defined periods, while AAPC represented a weighted average of EAPCs over multiple intervals, capturing overarching long-term trends. Trend analyses were conducted using the Segment and broom R packages, with 95% confidence intervals (CIs) employed to determine statistical significance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Socio-demographic Index (SDI) Analysis\u003c/h2\u003e\u003cp\u003eSDI data were utilized to evaluate the influence of socioeconomic development on the burden of EOKC, with higher scores indicating greater development [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Age-standardized DALY rates (ASDRs) were calculated across the SDI continuum to characterize the association between development level and disease burden. Based on SDI values, countries and territories were stratified into quintiles: high, high-middle, middle, low-middle, and low SDI (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). Data manipulation and visualization were performed using the dplyr and ggplot2 R packages, while Spearman\u0026rsquo;s rank correlation was applied to assess the monotonic relationship between SDI and ASDR. Annual SDI values from 1990 to 2021 are presented in \u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Attributable Risk Factors Analysis\u003c/h2\u003e\u003cp\u003eDALYs were employed as a composite measure of disease burden, integrating years of life lost (YLL) due to premature mortality and years lived with disability (YLD) resulting from illness or impairment. Attributable DALYs quantify the disease burden linked to specific risk factors, thereby elucidating each factor\u0026rsquo;s contribution to the overall EOKC burden. Risk-attributable DALYs were estimated using data from the GBD 2021 database. Forest plots, generated \u003cem\u003evia\u003c/em\u003e the ggplot2 R package, visualized the proportional impact of individual risk factors on total DALYs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Bayesian Age-Period-Cohort (BAPC) Model for Forecasting\u003c/h2\u003e\u003cp\u003eTo project future EOKC burden, the BAPC model was implemented using the INLA and BAPC R packages [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This model accounted for age, period, and cohort effects to estimate and forecast trends in age-standardized incidence rate (ASIR), mortality rate (ASMR), and ASDR through 2035. The BAPC framework incorporated demographic and temporal dynamics, offering a statistically rigorous approach for anticipating the trajectory of EOKC.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Statistical Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses and visualizations were conducted using R software. Descriptive statistics were computed for key variables, with results presented as means accompanied by 95% uncertainty intervals (UIs). Statistical tests were two-sided, and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Global and regional distribution of EOKC in 2021\u003c/h2\u003e\u003cp\u003eBased on GBD 2021 estimates, 17,622 new cases of EOKC were reported globally in 2021, with East Asia accounting for the largest share of incident cases. The global ASIR was 0.58 per 100,000, with the highest incidence observed in Southern Latin America (3.83 per 100,000) and the lowest in Oceania (0.07 per 100,000). In terms of mortality, an estimated 3,261 deaths were attributed to EOKC in 2021, with East Asia reporting the highest number of fatalities. The global ASMR was 0.11 per 100,000, ranging from 0.02 per 100,000 in Oceania to 0.38 per 100,000 in Southern Latin America. DALYs reached 197,665 years in 2021, with East Asia contributing the largest proportion. The global ASDR was 6.50 per 100,000, ranging from 1.36 per 100,000 in Oceania to 24.93 per 100,000 in Southern Latin America. A complete breakdown of ASIRs, ASMRs, and ASDRs across 204 countries and territories is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with detailed values summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eAge stratification revealed distinct patterns of EOKC incidence (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), with individuals aged 35\u0026ndash;39 consistently representing the highest proportion of cases, indicating that the disease predominantly affects the older segment of the adolescent and young adult population. Gender-specific analysis identified clear disparities across global and regional levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Males exhibited a global ASIR of 0.67 per 100,000\u0026mdash;approximately 1.43 times higher than that of females (0.47 per 100,000)\u0026mdash;suggesting a male predominance in EOKC incidence. The relationship between age and gender further demonstrated an age-dependent rise in EOKC incidence, particularly after age 25 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Comparative analyses between 1990 and 2021 highlighted an overall upward trajectory in global EOKC incidence, although regional patterns varied substantially (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Temporal trends in EOKC from 1990 to 2021\u003c/h2\u003e\u003cp\u003eFrom 1990 to 2021, the global incidence of EOKC followed a sustained upward trajectory, with a pronounced acceleration post-2000 and a modest plateauing after 2018. In contrast, global mortality rates and DALY burdens associated with EOKC declined through the early 2000s, followed by a mild but consistent downward trend in subsequent years (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The temporal percentage change in EOKC incidence across 204 countries and territories is illustrated in \u003cb\u003eSupplementary Fig.\u0026nbsp;1A\u003c/b\u003e, revealing a global increase of 31.6% since 1990. EAPC values were calculated for each country and visualized in \u003cb\u003eSupplementary Fig.\u0026nbsp;1B\u003c/b\u003e. On average, global incidence has increased by approximately 1% annually (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). East Asia recorded the highest EAPC (3.88), whereas Oceania showed the slowest rise (EAPC, 0.09). Regions with high and middle SDI scores experienced the most rapid increases in incidence, while low SDI regions exhibited comparatively slower growth. Analysis of AAPC revealed consistent long-term trends across regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC; \u003cb\u003eSupplementary Fig.\u0026nbsp;1C\u003c/b\u003e). Comprehensive statistics on percentage change, EAPC, and AAPC by region are summarized in \u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eStratified analysis by SDI level confirmed a general upward trend in EOKC incidence across all five SDI quintiles from 1990 to 2021. High and high-middle SDI regions demonstrated the most substantial increases, while low SDI regions remained relatively stable (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Age-specific trends revealed notable heterogeneity, with the 35\u0026ndash;39 year cohort showing the highest growth rate in incidence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Relationship between EOKC disease burden and SDI\u003c/h2\u003e\u003cp\u003eIn assessing the relationship between EOKC burden and socio-demographic development, ASDRs were compared across 204 countries stratified by SDI levels in 2021. A positive overall correlation was observed between SDI and ASDR, with higher-SDI countries generally exhibiting greater EOKC burden (Spearman\u0026rsquo;s correlation coefficient, r\u0026thinsp;=\u0026thinsp;0.466, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Notably, ASDR followed an inverted U-shaped distribution across the SDI spectrum, peaking in countries with moderate SDI values and declining in both low- and high-SDI settings (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). This non-linear pattern persisted at the regional level, as evidenced by a similar inverted U-shaped trend across the 21 regions (Spearman\u0026rsquo;s correlation coefficient, r\u0026thinsp;=\u0026thinsp;0.595, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The association between EAPC and both DALYs and SDI was also examined (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). No significant correlation was found between EAPC and DALYs (Spearman\u0026rsquo;s correlation coefficient, r\u0026thinsp;=\u0026thinsp;0.017, p\u0026thinsp;=\u0026thinsp;0.81), indicating that the pace of change in EOKC incidence does not align closely with existing disease burden levels. However, a significant negative correlation was identified between EAPC and SDI (r = \u0026minus;\u0026thinsp;0.39, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that higher levels of social development are associated with slower recent increases in incidence rates.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Proportion of DALYs attributable to risk factors\u003c/h2\u003e\u003cp\u003eIn 2021, the distribution of EOKC DALYs attributable to specific risk factors indicated substantial contributions from high BMI, tobacco use, and occupational risk (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; \u003cb\u003eSupplementary Table\u0026nbsp;5\u003c/b\u003e). High BMI was the leading global risk factor, responsible for an estimated 16.2% (95% UI: 6.3\u0026ndash;26.1) of DALYs. Tobacco use accounted for approximately 1.5% (95% UI: 0.9\u0026ndash;2.1), while occupational exposure to trichloroethylene contributed about 0.1% (95% UI: 0.0\u0026ndash;0.1). Temporal analysis from 1990 to 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) demonstrated a pronounced global increase in the burden attributable to high BMI. By contrast, the contribution of tobacco use declined steadily over time, and occupational risk levels remained largely unchanged. Marked regional variation was observed in the influence of these risk factors (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Bayesian Age-Period-Cohort Model for predictions of EOKC burden\u003c/h2\u003e\u003cp\u003eProjections from the Bayesian APC model suggest a continued escalation in EOKC incidence over the next decade (\u003cb\u003eSupplementary Fig.\u0026nbsp;2A\u003c/b\u003e). In contrast, both the ASMR and ASDR have declined steadily over the past thirty years, a trend anticipated to persist and further intensify in the post-2021 period (\u003cb\u003eSupplementary Fig.\u0026nbsp;2B and 2C\u003c/b\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study presents a detailed evaluation of EOKC among individuals aged 15\u0026ndash;39 years, offering global, regional, and national perspectives spanning 1990 to 2021. By concentrating on AYAs\u0026mdash;a demographic historically underrepresented in oncology research\u0026mdash;this analysis contributes critical insights into the shifting epidemiological landscape of kidney cancer in younger populations. The upward trajectory in incidence within this age group necessitates the development and implementation of age-specific strategies that effectively address the emerging burden.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRegional, sex, and age differences in the burden of early-onset kidney cancer\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnalysis of GBD 2021 data uncovered pronounced heterogeneity in EOKC incidence, mortality, and DALYs across regions, sexes, and age brackets. In 2021, East Asia bore the highest absolute burden, while Southern Latin America exhibited the highest standardized rates, contrasting with consistently low levels in Oceania. These regional disparities align with previous evidence suggesting that kidney cancer burden tends to be elevated in high-income or rapidly developing regions, likely driven by variations in lifestyle, environmental exposures, healthcare access, and screening infrastructure [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The distribution of EOKC burden within the 15\u0026ndash;39 age range appeared skewed toward older subgroups, likely reflecting cumulative exposure to metabolic and environmental risk factors. Male predominance in EOKC incidence may stem from a higher prevalence of modifiable risk factors among men, including tobacco and alcohol use, suboptimal dietary habits, and increased occupational exposure to nephrotoxic agents [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Moreover, biological mechanisms, particularly the influence of androgen receptors, have been implicated in the pathogenesis of kidney cancer [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The gender gap widens notably after age 25, suggesting a compounding effect of age-related hormonal, behavioral, and genetic risk factors [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eTemporal trend in the burden of early-onset kidney cancer\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe persistent global rise in EOKC incidence over the past three decades likely stems from a complex interplay of environmental and biological factors. Rapid urbanization and industrial expansion\u0026mdash;especially in high and middle SDI regions\u0026mdash;have significantly increased population-level exposure to environmental carcinogens, including airborne pollutants, heavy metals, and endocrine-disrupting compounds, all of which are implicated in renal carcinogenesis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Concurrently, escalating prevalence of obesity, metabolic syndrome, and sedentary lifestyles among AYAs contributes to systemic inflammation and metabolic dysregulation, creating a pro-tumorigenic environment [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Enhanced access to imaging technologies and improved healthcare availability have also facilitated the incidental detection of asymptomatic renal tumors, further contributing to rising incidence figures [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In contrast to the upward incidence trend, the sustained decline in EOKC-related mortality and DALYs over the same period reflects considerable progress in clinical care. Key drivers include earlier detection, broader application of minimally invasive surgical techniques, advancements in targeted therapies, and the growing adoption of multidisciplinary treatment approaches [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Marked regional variation in the pace of EOKC incidence escalation further highlights the influence of socioeconomic development, environmental exposure, and healthcare infrastructure. The more pronounced incidence increases in high and middle SDI regions, relative to low SDI counterparts, may in part be driven by superior diagnostic infrastructure and surveillance systems that enable earlier and more frequent detection of renal malignancies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSociodemographic differences in the burden of early-onset kidney cancer\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe inverted U-shaped association between national EOKC burden and socio-demographic development may reflect a transitional phase wherein rising income and development initially enhance access to healthcare and diagnostic capabilities but concurrently introduce population-level exposures that elevate cancer risk. These exposures include urbanization, increasingly sedentary lifestyles, widespread consumption of processed foods, and a growing prevalence of obesity and metabolic disorders [\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Despite the rising incidence of EOKC in high SDI regions, a corresponding increase in DALYs has not been observed. This decoupling likely results from the presence of mature healthcare infrastructures that facilitate earlier detection, improve treatment outcomes, and reduce YLL due to premature mortality [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These observations highlight the critical role of robust health systems not only in cancer detection but also in mitigating disease burden through improved survival and long-term management [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The significant negative correlation between EAPC and SDI suggests that as nations advance socioeconomically, the rate of increase in EOKC incidence tends to decelerate. This inverse trend may be attributed to enhanced healthcare infrastructure, widespread health education, and the adoption of preventive strategies that collectively mitigate key risk factors such as obesity, tobacco use, and environmental pollution [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eRisk factors in the burden of early-onset kidney cancer\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHigh BMI, tobacco use, and occupational exposures emerged as the leading contributors to the global burden of EOKC. The dominant role of high BMI across all socio-demographic strata underscores the pervasive impact of the global obesity epidemic and its direct oncogenic implications, particularly within high-income regions [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In High-income North America, for instance, more than a quarter of EOKC-related DALYs were attributable to elevated BMI. This strong association is supported by multiple biological mechanisms, including elevated pro-inflammatory cytokines (e.g., TNF-α, IL-6), activation of the insulin-like growth factor-1 (IGF-1) signaling pathway, dysregulated adipokine secretion and increased estrogen synthesis via aromatase activity in adipose tissue [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Although smoking prevalence has declined overall, its residual impact continues to shape kidney cancer burden, particularly in high-income settings [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In low socio-demographic regions, observed reductions in tobacco-attributable burden may reflect the cumulative effect of targeted cessation programs and broader public health initiatives aimed at reducing tobacco consumption [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These findings underscore the necessity of preserving and strengthening tobacco control measures as a means to further mitigate the preventable burden of kidney cancer across diverse socio-economic contexts. Occupational exposures accounted for a relatively small proportion of the measured global EOKC burden. This low figure may reflect systematic under-detection or under-reporting of occupational cancers, particularly in low and middle socio-demographic regions, where regulatory oversight is often limited, exposure monitoring infrastructure remains inadequate, and data on occupational carcinogens are frequently incomplete or inaccessible [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Prioritizing occupational cancer prevention through regulatory reforms, exposure assessment, and protective interventions is essential to address region-specific environmental and workplace-related cancer risks.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProjected Trends and Strategic Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProjections derived from the BAPC model forecast a continued rise in the incidence of EOKC, accompanied by sustained improvements in mortality and DALY outcomes. This divergence highlights a dual challenge in disease control: the increasing burden of diagnosis and surveillance, alongside the imperative to preserve and enhance advances in clinical outcomes. Addressing this challenge requires a multifaceted and adaptive strategy encompassing both upstream prevention and downstream clinical care. This effort necessitate comprehensive public health programs, including school-based health education, nutritional initiatives, urban planning that facilitates active lifestyles, and robust regulatory frameworks to limit harmful exposures\u0026mdash;particularly in rapidly urbanizing, high-risk settings. Concurrently, investment in cancer surveillance infrastructure is essential to support accurate case detection, timely diagnosis, and dynamic monitoring of epidemiological trends at national and regional levels [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Given the higher prevalence of hereditary subtypes (e.g., von Hippel\u0026ndash;Lindau, Birt\u0026ndash;Hogg\u0026ndash;Dub\u0026eacute;, and fumarate hydratase deficiency) in early-onset cases, genetic counseling and family screening may be warranted [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Clinically, maintaining and expanding access to advanced treatment modalities\u0026mdash;such as targeted therapies, immunotherapies, precision oncology, and minimally invasive surgical techniques\u0026mdash;will be vital for sustaining declines in mortality and disability associated with EOKC [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Multidisciplinary management approaches should be reinforced, especially for younger patients who face distinct survivorship challenges. These include long-term follow-up for late treatment effects, psychosocial support, fertility preservation, and integration of survivorship care into standard oncology practice [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur study had several limitations. Firstly, this study relies on the GBD 2021 database, whose estimates are based on national cancer registries, death reports, and modeling projections. For low- to medium SDI regions, due to incomplete cancer registries or missing data, the results may be subject to uncertainty and the risk of underestimation or overestimation. Secondly, The analysis only includes quantifiable risk factors within the GBD framework (e.g., BMI, smoking, occupational exposure), and does not incorporate detailed indicators related to genetics (e.g., VHL, FH mutations), family history, dietary patterns, or environmental pollution. Therefore, it cannot fully elucidate the etiology of early-onset kidney cancer. Thirdly, we primarily relied on modelling processes for the estimates in this study, and the choice of models and parameter settings could have influenced the results.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOver the past 30 years, EOKC has exhibited a persistent and concerning increase in incidence and associated burden. Stark disparities across geographic regions, sexes, and age groups\u0026mdash;coupled with the influence of socio-demographic factors\u0026mdash;demand urgent, targeted public health responses and strategic resource mobilization. A comprehensive, integrated framework is imperative to curtail the growing public health and socioeconomic impact of EOKC globally.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAAPC (Average Annual Percent Change)\u003c/p\u003e\n\u003cp\u003eAPC (Age-Period-Cohort)\u003c/p\u003e\n\u003cp\u003eASDR (Age-Standardized Disability-Adjusted Life Years Rate)\u003c/p\u003e\n\u003cp\u003eASIR (Age-Standardized Incidence Rate)\u003c/p\u003e\n\u003cp\u003eASMR (Age-Standardized Mortality Rate)\u003c/p\u003e\n\u003cp\u003eAYA (Adolescents and Young Adults)\u003c/p\u003e\n\u003cp\u003eBAPC (Bayesian Age-Period-Cohort), BMI (Body Mass Index)\u003c/p\u003e\n\u003cp\u003eCIs (Confidence Intervals), DALYs (Disability-Adjusted Life Years)\u003c/p\u003e\n\u003cp\u003eEAPC (Estimated Annual Percentage Change)\u003c/p\u003e\n\u003cp\u003eEOKC (Early-Onset Kidney Cancer), GBD (Global Burden of Disease)\u003c/p\u003e\n\u003cp\u003eGHDx (Global Health Data Exchange)\u003c/p\u003e\n\u003cp\u003eICD (International Classification of Diseases)\u003c/p\u003e\n\u003cp\u003eIGF-1 (Insulin-like Growth Factor 1), IL-6 (Interleukin-6)\u003c/p\u003e\n\u003cp\u003eINLA (Integrated Nested Laplace Approximation)\u003c/p\u003e\n\u003cp\u003eSDI (Socio-Demographic Index)\u003c/p\u003e\n\u003cp\u003eTNF-\u0026alpha; (Tumor Necrosis Factor Alpha)\u003c/p\u003e\n\u003cp\u003eUI (Uncertainty Interval)\u003c/p\u003e\n\u003cp\u003eWHO (World Health Organization)\u003c/p\u003e\n\u003cp\u003eYLD (Years Lived with Disability)\u003c/p\u003e\n\u003cp\u003eYLL (Years of Life Lost)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the researchers and participants of the GBD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Natural Science Foundation of China (82273135) and the National Key R\u0026amp;D Program of China (2023YFC2415500) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChi Zhang and Lei He made equal contributions.\u003c/p\u003e\n\u003ch3\u003eAuthors and Affiliations\u003c/h3\u003e\n\u003cp\u003eDepartment of Urology, Peking University First Hospital, Peking University, Beijing 100035, China.\u003c/p\u003e\n\u003cp\u003eChi Zhang, Lei He, Chaojie Xu, Ziyang Guo, Yihan Wang, Kaiwei Yang, Han Hao \u0026amp; Lin Yao.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChi Zhang and Lei He analyzed the data, performed the statistical analyses and drafted the manuscript. Chaojie Xu, Ziyang Guo and Yihan Wang collected the related references and participated in discussion. Lin Yao, Han Hao and Kaiwei Yang conceived and designed this project, and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Lin Yao ([email protected]), Han Hao ([email protected]) and Kaiwei Yang ([email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhered to the Helsinki Declaration (2013 revision). This study was a retrospective, observational cohort analysis based entirely on publicly available, therefore ethical approval and informed consent were waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used in the study were from the publicly available GBD database (https://www.ncbi.nlm.nih.gov/gbd/). Informed consent forms are not required for patient data extracted from public databases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZi H, Liu M-Y, Luo L-S, et al. 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Treatment of renal cell carcinoma: Current status and future directions. \u003cem\u003eCA Cancer J Clin\u003c/em\u003e. 2017;67(6):507-524. doi:10.3322/caac.21411\u003c/li\u003e\n\u003cli\u003eWang Y, Suarez ER, Kastrunes G, et al. Evolution of cell therapy for renal cell carcinoma. \u003cem\u003eMol Cancer\u003c/em\u003e. 2024;23(1):8. doi:10.1186/s12943-023-01911-x\u003c/li\u003e\n\u003cli\u003eLi Z, Xu H, Yu L, et al. Patient-derived renal cell carcinoma organoids for personalized cancer therapy. \u003cem\u003eClin Transl Med\u003c/em\u003e. 2022;12(7):e970. doi:10.1002/ctm2.970\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Kidney cancer, Adolescents, young adults, Obesity, Epidemiological trends","lastPublishedDoi":"10.21203/rs.3.rs-7464519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7464519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eKidney cancer occurring in adolescents and young adults is increasingly recognized as a significant global health concern. However, its long-term epidemiological patterns remain underexplored.\u003c/p\u003e\u003ch2\u003eAim\u003c/h2\u003e\u003cp\u003eTo evaluate global, regional, and national burdens and trends of early-onset kidney cancer (EOKC) from 1990 to 2021 to support the development of targeted prevention and intervention strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eData were obtained from the Global Burden of Disease (GBD) 2021 database. Analyses focused on individuals aged 15\u0026ndash;39 years, assessing global and regional incidence, mortality, and disability-adjusted life years (DALYs) using age-standardized rates (ASRs) to adjust for demographic variability. Temporal trends were assessed using estimated annual percentage change (EAPC) and average annual percentage change (AAPC). The Bayesian age-period-cohort (BAPC) model was employed for forecasting.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eGlobally, 17,622 new EOKC cases were reported in 2021, with the highest incidence in Southern Latin America and the largest case numbers in East Asia. From 1990 to 2021, global EOKC incidence increased by 31.6%, driven primarily by high and middle SDI regions. DALYs showed an inverted U-shaped relationship with SDI, peaking in moderately developed settings. High body mass index was the leading attributable risk factor, followed by tobacco use and occupational exposures. BAPC projections suggest continued increases in incidence but declining mortality and DALYs by 2035.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eEOKC poses a growing and uneven global burden, particularly in rapidly developing regions. Targeted prevention strategies addressing modifiable risk factors and improved resource allocation are essential to mitigate future impact.\u003c/p\u003e","manuscriptTitle":"Global, regional, and national burden of early-onset kidney cancer in adolescents and young adults aged 15-39 years from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 12:31:58","doi":"10.21203/rs.3.rs-7464519/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"006ca0ad-3e58-4454-8ea1-78ebfcf77d9e","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-19T14:09:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-17 12:31:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7464519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7464519","identity":"rs-7464519","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}