Tracking and analysis of testicular cancer burden in adolescents and young adults globally in Asia and in China: 1990–2021 epidemiological trends

Introduction

Testicular cancer (TC) is relatively rare among malignant tumors, yet it has the highest incidence rate among males aged 15 to 39 years and ranks third among cancers in children under 5 years old (1,2). The causes of TC are complex, involving genetic, environmental, and lifestyle factors. Cryptorchidism is one of the most significant risk factors, and hypospadias, oligospermia, and family history are also considered to be associated with the development of TC (3,4). In recent years, a combination of surgery and platinum-based chemotherapy has significantly improved the survival rate of patients with TC (5). However, the economic and psychological burden of TC are still considerable, and the incidence of TC continues to rise, particularly in regions with medium or high Human Development Index (HDI) (6).

The Global Burden of Disease (GBD) study has become a key tool for gaining an understanding of global health issues. By integrating the multidimensional data related to the incidence, prevalence, and disability-adjusted life years (DALYs) across different time periods, regions, and age groups, the GBD study provides support for a comprehensive assessment of the global disease burden (7-9). Recent research indicates an increasing global burden of TC among adolescents and young adults (AYAs) (10), particularly in China and Asia (11). There are significant differences in medical conditions and health awareness across countries in Asia, which affect the early diagnosis and treatment outcomes for TC. Early diagnostic methods mainly include serum tumor marker tests, computed tomography scans, and pathological examinations (12). In economically developed countries, cancer screening and treatment investment are substantial, resulting in higher early diagnosis rates and better treatment outcomes. However, in some developing countries, delays in diagnosis, insufficient treatment, high mortality rates, and heavy disease burden persist. In addition, demographics and lifestyles are changing rapidly in Asia, and accelerated urbanization, worsening environmental pollution, and the popularity of unhealthy lifestyles may increase the risk of TC (5).

There are relatively few studies of TC in AYAs in the high-risk age group of 15 to 39 years old (13-15). AYAs aged 15 to 39 years play an important role in socioeconomic activities and population growth, with AYAs aged 25–29 years being a group with relatively high fertility rates (16). TC often severely affects the fertility, mental health, and overall quality of life of young patients (17,18). An in-depth study of the disease burden of TC among AYAs globally, in Asia, and in China is critical to characterizing the epidemiologic trends and developing effective preventative measures.

This is the first study to combine the analysis of previously published literature and the GBD 2021 database to assess the current status and trends in the research on TC among AYAs through joinpoint regression analysis, decomposition analysis, age-period-cohort modeling using the intrinsic estimation modeling, Nordpred predictive analysis, and bibliometrics. We present this article in accordance with the STROBE reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-394/rc).

Methods

Data resources

The data in this study were obtained from the GBD 2021 database through the Global Health Data Exchange query tool on the official GBD website (https://vizhub.healthdata.org/gbd-results/). GBD 2021 used standardized and reproducible methods to comprehensively and scientifically assess the health losses due to 371 disease injuries and 88 risk factors in 204 countries and territories across the world (7,8). In addition, this study focused on three main indicators: incidence, prevalence, and mortality with DALY and the corresponding age-standardized rates (ASRs). We defined the age range for AYA as 15–39 years old. The diagnosis of TC in this study was strictly classified according to the 9th International Classification of Diseases (ICD-9) and the 10th edition (ICD-10). The codes for TC included C62-C62.9, 186-186.9 (7). This study strictly followed the Guidelines of Accurate and Transparent Health Assessment Reporting (GATHER) (19). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Sociodemographic index (SDI)

The SDI value is a key indicator of socioeconomic development level that integrates the sociodemographic characteristics of the region. The SDI takes values ranging from 0 to 1 and integrates key factors, such as per capita income, average educational attainment, and fertility rate for each region in the GBD study (8-10). The SDI divides regions into five classes: low SDI, low-middle SDI, middle SDI, high-medium SDI, and high SDI. The higher the SDI value is, the better the socioeconomic conditions of the region.

Statistical analysis

Direct standardization was used to calculate ASRs, including the age-standardized death rate (ASDR), age-standardized incidence rate (ASIR), and age-standardized DALY rate. The formula for calculating the ASR is as follows:

ASR=∑i=1nRi⋅Wi[1]

where R_i denotes the age group i-specific rate, W_i denotes the weight given to age group i in the standardized population (the proportion of the population in that age group to the total standardized population), and n denotes the total number of age groups (20,21). The ASDR is based on the death rate per 100,000 population and is calculated as a weighted average of the crude death rate based on the weight of each age group to the standard population.

ASDR=∑i=1n(DiPi⋅Wi)×100,000[2]

The ASIR is based on the incidence rate per 100,000 population and is calculated as a weighted average of the crude incidence rate based on the weighting of each age group to the standard population weight.

ASYR=∑i=1n(CiPi⋅Wi)×100,000[3]

Age-standardized DALY rate is based on the DALY rate per 100,000 population and is calculated as a weighted average of the crude DALYs for each age group and the standard population weights.

Age-standardizedDALYrate=∑i=1n(DALYiPi⋅Wi)×100,000[4]

Trends in the burden of TC in Asia and worldwide were analyzed via joinpoint regression model (CommandLine version 5.2.0) (22). The joinpoint regression model can analyze the trends of disease burden-related indicators over time, such as incidence, mortality, and disability-adjusted life years. The optismal model for the joinpoint regression was established by the Monte Carlo permutation test. The annual percent change (APC) and average annual percent change (AAPC) calculated by the optimal model were used to quantify the trend in rates from 1990 to 2021. The APC was calculated as follows: APC = (eβ−1) × 100%, where β is the regression coefficient of the log-linear model (lny = β × x). The AAPC was the average sum of the APCs of the segments weighted by the span of the segmented intervals w and represented the overall trend of the prevalence trend from 1990 to 2021 (21). The intrinsic estimator method (IEM) was used to decompose the age, period, and cohort effects of the epidemic trend. The APC model was constructed within the framework of traditional probability theory, with the Nordpred model serving as a specific implementation of the APC model (23). Decomposition analysis was conducted according to Das Gupta’s decomposition analysis method (24). All statistical analyses and graphing were performed with R statistical software version 4.4.1 (The R Foundation for Statistical Computing). A two-sided P value <0.05 was used as the significance threshold.

Results

The number of deaths from TC in AYAs in 2021 was 5,698 [95% uncertainty interval (UI): 5,287–6,155], with an ASDR of 0.37 per 100,000 people [95% confidence interval (CI): 0.35–0.40] worldwide. The global burden of TC deaths in AYAs has progressively decreased since 1990 (AAPC: −0.28; 95% CI: −0.43 to −0.14), indicating a progressive reduction in the burden of TC. The AAPC of the ASIR, age-standardized prevalence rate (ASPR), and ASDR increased more sharply in high-SDI regions than in other regions. The fastest growth in ASIR, ASPR, and ASDR was observed in the middle-SDI countries, demonstrating an upward trend in the TC burden in these countries. The ASIR and ASPR in East Asia showed the most significant increase in Asia over the 1990–2021 period. Except for Southeast Asia, the ASDR showed a decreasing trend in all regions of Asia. Both the ASIR and ASPR showed an extreme growth AAPC of 3.74 (95% UI: 3.08–4.41) and 7.29 (95% UI: 6.65–7.93) during the 1990–2021, whereas the opposite was observed for the ASDR, with an AAPC of −1.48 (95% UI: −2.31 to −0.83) in China (Tables 1-3).

The ASDR is a key indicator of the lethality of TC and reflects the extent to which TC threatens the health and life of the population. Joinpoint regression analysis revealed a significant decline in the ASDR for AYAs with TC from 1990 to 1994 and from 1999 to 2007. However, the decrease slowed slightly between 1994 and 1999, followed by a gradual increase from 2007 to 2012. A sharp rise in mortality occurred between 2012 and 2019, after which a declining trend was observed. Overall, the global ASDR for TC declined from 1990 to 2021 (AAPC: −0.28) (Figure 1A). From 1990 to 2021, the ASDR in Central Asian countries increased slightly (AAPC: 0.07) (Figure 1B), while it decreased in South Asia (AAPC: −0.36) (Figure 1C). In Southeast Asia, the ASDR showed a significant increase (AAPC: 0.40) (Figure 1D). In East Asia, the ASDR declined significantly (AAPC: −1.46) (Figure 1E). In China, the ASDR for TC in AYAs declined slowly from 1990 to 1997, with the rate of decline accelerating from 1997 to 2004, peaking between 2004 and 2007. The rate of decline slowed again from 2007 to 2012, followed by an increase in the ASDR from 2012 to 2016, and then a gradual decline after 2016. Overall, the ASDR for TC in China declined significantly from 1990 to 2021 (AAPC: −1.48) (Figure 1F).

Figure 1 Joinpoint regression analysis of AYAs with TC (ASDR for 1990–2021). (A) ASDR of AYAs globally. (B) ASDR of AYAs in Central Asia. (C) ASDR of AYAs in South Asia. (D) ASDR of AYAs in Southeast Asia. (E) ASDR of AYAs in East Asia. (F) ASDR of AYAs in China. AAPC, average annual percent change; APC, annual percent change; ASDR, age-standardized death rate; AYAs, adolescents and young adults; TC, testicular cancer.

Trends in burden by country

Monaco had the highest ASIR and prevalence rate (ASPR) among AYAs, both at 86.36 (95% CI: 39.00–167.51) (Figure 2A,2B). Mexico had the highest ASDR (2.31; 95% CI: 2.06–2.57) and age-standardized DALY (149.33; 95% CI: 133.44–166.20) among AYAs (Figure 2C,2D), while Palau had the lowest values for all indicators.

Figure 2 ASRs of AYAs with TC in 204 countries and territories in 2021. (A) ASIR. (B) ASPR. (C) ASDR. (D) Age-standardized DALY. ASDR, age-standardized death rate; ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; ASRs, age-standardized rate; AYAs, adolescents and young adults; DALY, disability-adjusted life year; TC, testicular cancer.

From 1990 to 2021, Puerto Rico showed the fastest increase in ASIR, while Switzerland had the largest decrease. Ecuador had the greatest increase in ASPR, while the United Kingdom demonstrated the most significant decrease. Belize experienced the fastest rise in both ASDR and DALY, while Luxembourg saw the most rapid decline. Among Asian countries, Japan had the highest ASIR, ASPR, ASDR, and age-standardized DALY, with Georgia and India having the highest incidence rates and China having the highest prevalence rate.

In Asia, ASIR and ASPR increased in all countries from 1990 to 2021. Iran showed the fastest rise in ASIR, while China had the largest increase in ASPR. Japan experienced the slowest growth in both ASIR and ASPR (AAPC =0.35). Turkmenistan had the fastest rise in ASDR and DALY, while South Korea had the most significant decrease. In China, the ASIR, ASPR, ASDR, and age-standardized DALY for AYAs were 1.22 (95% CI: 0.91–1.63), 10.50 (95% CI: 7.78–14.12), 0.12 (95% CI: 0.09–0.15), and 8.04 (95% CI: 6.16–10.13) per 100,000 population, respectively. From 1990 to 2021, the AAPC for ASIR, ASPR, ASDR, and DALY were 3.74 (95% CI: 3.08–4.41), 7.29 (95% CI: 6.65–7.93), −1.48 (95% CI: −2.13 to −0.83), and −1.27 (95% CI: −1.91 to −0.62), respectively. While ASIR and ASPR showed significant increases, ASDR and DALY exhibited a downward trend.

Decomposition analysis of China and other regions

This study performed a decomposition analysis of the ASIR, ASPR, ASDR, and age-standardized DALY rates. The results showed that, compared to 1990, new TC cases increased by 33,097.5, and the prevalence of cases increased by 263,953.88 in 2021. Epidemiological changes were the primary driver of these increases, accounting for 55.5% and 57.48%, respectively. Population growth contributed 40.3% and 38.05%, while changes in age structure accounted for 4.3% and 4.46%, respectively. In Asia, the increase in incidence and prevalence was mainly due to epidemiological changes, while the rise in death rates and DALYs was primarily attributed to population growth.

In China, from 2019 to 2021, the number of new TC cases increased by 2,082, and the number of patients grew by 23,967. Epidemiological changes accounted for 106.3% and 103.39% of these increases, respectively, while population growth contributed −16.4% and 10.32%. Between 1990 and 2021, the number of deaths from TC in AYAs increased by 1,298, and the number of DALYs grew by 93,927. Population growth accounted for 119.8% and 107.86% of these changes, while epidemiological changes accounted for −33% and −16.37%. In China, the number of deaths decreased by 221.42, and DALYs decreased by 13,062.23 person-years, primarily driven by epidemiological changes, which contributed 87.74% and 80.79%, respectively (Figure 3).

Figure 3 Changes in testicular cancer incidence, prevalence, mortality, and DALYs in AYAs between 1990 and 2021 analyzed according to factors of population growth, aging, and epidemiological changes. (A) Incidence, (B) prevalence, (C) deaths, and (D) DALYs. AYAs, adolescents and young adults; DALYs, disability-adjusted life years; SDI, sociodemographic index.

APC-ie and Nordpred models

The increasing incidence of TC in AYAs in China has led to a rising disease burden. Age-based analysis revealed that both incidence and prevalence increased across all age groups over time, with the most significant rise observed in the 30- to 34-year age group, although other age groups also showed upward trends (Figure 4A,4B, line I). In contrast, death rates and DALYs generally decreased and then increased. For instance, in the 20- to 24-year age group, mortality and DALYs decreased between 2007 and 2011, then increased from 2017 to 2021 (Figure 4C,4D, line I).

Figure 4 Trends in age-specific, period, and birth cohort changes in testicular cancer incidence, prevalence, mortality, and DALYs among Chinese AYAs. (A) Incidence, (B) prevalence, (C) deaths, and (D) DALYs. I, age & period; II, birth cohort & age; III, birth cohort & period. AYAs, adolescents and young adults; DALYs, disability-adjusted life years.

Time-effect analysis showed an upward trend in incidence and prevalence across age groups for men in different birth cohorts. The 1977–1981 cohort showed a notable increase in incidence and prevalence at ages 35–39 years, with similar trends observed in younger cohorts, where the rise in incidence and prevalence was more pronounced (Figure 4A,4B, line II). Most birth cohorts also showed an increase in mortality and DALYs, with the 1977–1981 cohort showing higher mortality and DALYs at ages 30–34 years, from 0.14 and 10.11 in 1992–1996 to 0.17 and 10.32 in 2007–2011, respectively. At ages 35–39 years, mortality and DALYs decreased between 2012 and 2016 (Figure 4C,4D, line II). Birth cohort effect analysis showed a consistent increase in incidence and prevalence over time, with a decrease in mortality and DALYs, particularly for cohorts born after 2002–2006 (Figure 4C,4D, line III).

Nordpred model predictions

The Nordpred model predicts an increasing trend in ASIR, ASPR, and age-standardized DALYs across all age groups, with particularly significant growth in the 30- to 34-year and 35- to 39-year age groups. For the 15- to 19-year age group, new cases, prevalence, deaths, and DALYs are expected to peak in 2032, after which these indicators will decline. However, ASIR, ASPR, ASDR, and age-standardized DALYs for this group will steadily rise from 2021 to 2045. The 20- to 24-year age group is projected to see peaks in prevalence, deaths, and DALYs in 2037, with a subsequent decline. ASIR, ASPR, and age-standardized DALYs will continue to rise until 2045, while ASDR is expected to reach its lowest point in 2024 and then fluctuate. For the 25- to 29-year age group, new cases, prevalence, deaths, and DALYs will peak in 2042, after which these indicators will decline, while ASIR, ASPR, ASDR, and age-standardized DALYs will steadily rise until 2045. In the 30- to 34-year age group, new cases and prevalence will continue to increase until 2045, while deaths and DALYs are expected to decline to a minimum in 2034 before rising again. ASIR, ASPR, and age-standardized DALYs will steadily increase, with ASDR peaking in 2029 and then declining by 2045. In the 35- to 39-year age group, new cases and prevalence will peak in 2028, with fluctuations afterward. Deaths and DALYs will peak in 2026, then decrease to their lowest point in 2039, with subsequent fluctuations. ASIR, ASPR, and age-standardized DALYs will rise steadily until 2045, while ASDR is projected to peak in 2029, with other time periods showing dynamic fluctuations (Figure 5).

Figure 5 Predicted trends of testicular cancer in Chinese AYAs from 1990 to 2045 (based on the Nordpred model). (A) Incidence and ASIR. (B) Prevalence and ASPR. (C) Deaths and ASDR. (D) DALYs and age-standardized DALYs. ASDR, age-standardized death rate; ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; AYAs, adolescents and young adults; DALYs, disability-adjusted life years.

Discussion

The key findings of this study highlight several important trends. The number of new cases, deaths, and overall burden of TC in AYAs has increased, while the death rate and overall health burden relative to the population have decreased. Regional differences were observed, with Southeast Asian countries showing a significant increase, Central Asian countries remaining stable, and South and East Asian countries experiencing varying declines. In China, both the number of new cases and deaths have increased faster than the global average, but the death rate has dropped significantly. The burden of TC is influenced by factors such as population aging, growth, and changes in health dynamics across different regions. Among AYAs in China, the incidence and prevalence of TC have increased in later birth cohorts, while the death rate and health burden have decreased. Looking ahead, the incidence and prevalence of TC in AYAs in China are expected to rise, while deaths and health-related burdens are projected to decrease.

The results of the decomposition analysis showed that epidemiologic changes were the main drivers of the increase in the incidence and prevalence globally, while the increase in deaths and DALYs was mainly driven by population growth. In China, epidemiologic changes were the main drivers of the increase in new TC cases and prevalence and of the decrease in deaths and DALYs. This suggests that while advancements in medical technology have improved diagnostic tools for TC, early screening for TC in the AYA population is not yet a standard practice in China. Therefore, the increase in TC incidence may be more plausibly attributed to factors such as environmental changes, better cancer registration. One study reported miR-371a-3p to be a sensitive and specific biomarker for testicular germ cell tumors (TGCTs) (25). Serum tumor marker assessment and advances in imaging tools (e.g., the use of 18-fluoro-deoxyglucose positron emission tomography) (26,27) have greatly contributed to the rate of early diagnosis for TC and are among the reasons why epidemiological changes are driving the increase in TC case numbers. Moreover, the continued increase in fertility in the Sub-Saharan region, which has resulted in a sustained increase in the population aged 15 to 39 years, has driven the increase in deaths with DALYs (28). In addition, the significant improvement in the efficacy of drug therapy for TC can be attributed to the use of platinum-based chemotherapy regimens, which have significantly improved the survival of patients with TC, with 5-year survival rates having risen from less than 30% in the 1950s to over 95% now (29). With the development of comprehensive, multidisciplinary treatment for TC and the continuous improvement in the level of surgery, radiotherapy, and chemotherapy, the prognosis of patients with different stages and types of TC has been improved (30). The early diagnosis and treatment of TC has reduced its mortality rate, and the 5-year survival rate of patients with TC diagnosed as stage I is close to 100% (31). These factors have led to a decrease in the ASDR for TC in AYAs globally. ASDR is a key parameter for assessing cancer burden and developing public health intervention strategies. Through joinpoint regression analysis of ASDR, we could identify the differences in the threat of TC to the health of populations in different regions and thus provide a more targeted basis for resource allocation and the development of prevention and control strategies. We found that ASDR showed a rising trend in low-SDI regions, which is closely related to the deficiency in local medical services. Therefore, there is an urgent need to strengthen medical assistance to these areas, support the construction of basic medical facilities, improve the accessibility of medical services, and strengthen health and education to address the inequality in access to medical services.

At the regional and national level, there are significant geographic differences in the burden of disease for TC in AYAs. The ASIR and ASDR for TC were consistently high in Europe, North America, and Australia between 1990 and 2021. A previous study has shown that TC is more prevalent in high-SDI countries, such as Norway and Denmark (6), which is closely related to genetic factors. It has been noted that genetic factors dominate the incidence of TC, accounting for more than 40% of incidence. However, it is also important to consider that improvements in cancer registration, diagnostic practices, and the availability of screening programs in these countries may contribute to the higher reported prevalence of TC. In addition, non-Hispanic White ethnicity is associated with the highest incidence of TC (32), and advanced early medical screening tools, diagnostic techniques, and well-established tumor registries in countries with predominantly White populations like the United States and Nordic countries have contributed in part to the higher reported incidence (5). However, the most recent data from our study showed that in 2021, ASIR in medium- and low-SDI countries such as Morocco, Chile, Turkey, Montenegro, and Slovakia ranked among the top five globally. This phenomenon is consistent with previous findings that the gap between high and low prevalence regions is narrowing (19). The reason for this change may be related to the adoption of newer and more expensive interventions in developed countries, such as the provision of genomic testing services, and the emphasis on maternal and child care, which has effectively controlled the incidence of TC (33,34). Meanwhile, in developing countries, with the development of medical technology and the increasing use of ultrasound diagnosis, puncture biopsy, tumor markers, and other techniques, the early screening rate for TC risen (35). Tumor registries have also gradually improved, resulting in a subsequent increase in the detection rate and reported incidence of TC. The incidence of TC in East Aisa and Southeast Asia has increased significantly over the past three decades, with a high mean AAPC. This is closely related to the environmental pollution that occurs during industrialization and urbanization in these regions, which includes organochlorine pesticides, polyvinyl chloride, and other endocrine disrupting chemicals (EDCs), which significantly increase the risk of TC (36,37). In addition, drug proliferation is a serious problem in Southeast Asia, with a large number of AYAs smoking or being exposed to drugs. One study showed that after the legalization of marijuana in Thailand, its use has been on the rise, particularly among young people (38). Cannabis use adversely affects the human endocannabinoid and reproductive systems and is significantly associated with the development of nonseminomatous TGCTs, significantly increasing the incidence and mortality of TC among AYAs in Southeast Asian countries (39). In contrast, in less drug-affected East Asian countries, such as China, Japan, and South Korea, a significant decrease in ASDR was observed despite an increase in the ASIR for TC. In China, the rising incidence of TC is closely related to economic and social development, heightened health awareness among the population, and the popularization of health checkups. Meanwhile, the establishment of cancer service organizations has played an important role in prevention and control (40). In addition, AYAs’ westernized dietary habits, lifestyles, and sedentary behaviors also increase the risk of TC to some extent (41,42). Owing to the implementation of China’s 13th Five-Year Plan for Health and Wellness and Healthy China 2030 (43), patients with TC have been able to receive better quality and more favorable medical services and have been treated with more advanced and effective methods, which have improved their prognosis and effectively reduced their mortality rate.

In our study, the Nordpred model predicted that from 2022 to 2045, the burden of disease for TC in different age groups in Chinese AYAs will be slightly different, but on the whole, the ASIR, ASPR, ASDR, and DALY will decrease over time in all age groups. Particularly in the age group of 30 to 39 years, the number of new cases will significantly increase, but the number of deaths and DALY will decrease. However, according to a recent study, the ASIR, ASPR, and DALYs for AYAs with TC worldwide will all decrease over the next 10 years and beyond (11). This indicates that the disease burden of AYAs TC in China will continue to increase in the next 20 years, and disease prevention and control will face significant challenges. There remains a need to further strengthen the methods for preventing TC, early screening, and the dissemination of disease-related knowledge. TC is characterized by an early age of onset and relatively good prognosis, so a prolonged survival period and increased psychological and economic hardship may be key reasons for a heightened disease burden (44). With the prolongation of survival period, the cycle of disease treatment is also extended—especially for patients with advanced TC receiving multiple cycles of chemotherapy—the costs required for treatment and the loss of income will also gradually rise, resulting in an increase in the direct and indirect economic burdens of patients (45). In the younger population (15 to 19 years of age), a more pronounced decline in the number of new cases and in the number of patients with the disease is expected to continue until 2045. This trend may be attributable in part to effective public health interventions and advances in cancer treatment.

This study involved certain limitations that should be acknowledged. First, there are variations in data collection methods among healthcare systems in different regions, with varying levels of data quality, which could have affected the accuracy of the analysis. Second, there is a lack of global data on different pathologic subtypes and clinical stages of TC in the GBD database, which did not allow for a more in-depth analysis of disease burden. Finally, the accuracy of Nordpred model predictions is affected by the quality of GBD data and is susceptible to emergent factors such as wars and global epidemics in the formulation of long-term predictions, potentially reducing their accuracy.

Conclusions

This study clearly demonstrated the continued increase in the disease burden of TC among AYAs globally, in Asia, and in China and characterized the network of international collaboration in TC research. The incidence and prevalence of TC in AYAs are on the rise globally, but the mortality and DALYs have declined. China has made significant progress in early screening and treatment, but the disease burden will remain a considerable challenge in the future. The extensive coverage of the international collaboration network has provided important support for global TC research. Prevention, early screening, and international collaboration need to be further strengthened to address the increasing disease burden and improve patient prognosis.

Acknowledgments

The authors would like to express their appreciation to the contributors of GBD 2021.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-394/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2025-394/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2025-394/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Ghazarian AA, Kelly SP, Altekruse SF, et al. Future of testicular germ cell tumor incidence in the United States: Forecast through 2026. Cancer 2017;123:2320-8. [Crossref] [PubMed]
2. Miller KD, Fidler-Benaoudia M, Keegan TH, et al. Cancer statistics for adolescents and young adults, 2020. CA Cancer J Clin 2020;70:443-59. [Crossref] [PubMed]
3. Rajpert-De Meyts E, McGlynn KA, Okamoto K, et al. Testicular germ cell tumours. Lancet 2016;387:1762-74. [Crossref] [PubMed]
4. Lip SZ, Murchison LE, Cullis PS, et al. A meta-analysis of the risk of boys with isolated cryptorchidism developing testicular cancer in later life. Arch Dis Child 2013;98:20-6. [Crossref] [PubMed]
5. Cheng L, Albers P, Berney DM, et al. Testicular cancer. Nat Rev Dis Primers 2018;4:29. [Crossref] [PubMed]
6. Znaor A, Lortet-Tieulent J, Jemal A, et al. International variations and trends in testicular cancer incidence and mortality. Eur Urol 2014;65:1095-106. [Crossref] [PubMed]
7. Yamashita S, Koyama J, Goto T, et al. Trends in Age and Histology of Testicular Cancer from 1980-2019: A Single-Center Study. Tohoku J Exp Med 2020;252:219-24. [Crossref] [PubMed]
8. Yu S, Guo Z, Qiu Z, et al. Global burden and trends of testicular cancer in adolescents and young adults from 1990 to 2021, with predictions to 2035. Sci Rep 2024;14:31787. [Crossref] [PubMed]
9. Chovanec M, Cheng L. Advances in diagnosis and treatment of testicular cancer. BMJ 2022;379:e070499. [Crossref] [PubMed]
10. Zhou X, Zhang Z, Ruan C, 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 2024;110:4633-47. [Crossref] [PubMed]
11. Pishgar F, Haj-Mirzaian A, Ebrahimi H, et al. Global, regional and national burden of testicular cancer, 1990-2016: results from the Global Burden of Disease Study 2016. BJU Int 2019;124:386-94. [Crossref] [PubMed]
12. Xu Y, Xie S, Zhou C, et al. Time trends in the mortality of testicular cancer across the BRICS: an age-period-cohort analysis for the GBD 2019. Sci Rep 2024;14:12740. [Crossref] [PubMed]
13. van Basten JP, Hoekstra HJ, van Driel MF, et al. Sexual dysfunction in nonseminoma testicular cancer patients is related to chemotherapy-induced angiopathy. J Clin Oncol 1997;15:2442-8. [Crossref] [PubMed]
14. Wiechno P, Demkow T, Kubiak K, et al. The quality of life and hormonal disturbances in testicular cancer survivors in Cisplatin era. Eur Urol 2007;52:1448-54. [Crossref] [PubMed]
15. van Raan A. Measuring Science: Basic Principles and Application of Advanced Bibliometrics. In: Glänzel W, Moed HF, Schmoch U, et al. editors. Springer Handbook of Science and Technology Indicators. Cham: Springer International Publishing; 2019:237-80.
16. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:2100-32. [Crossref] [PubMed]
17. 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;403:2162-203. [Crossref] [PubMed]
18. 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 2024;403:2133-61. [Crossref] [PubMed]
19. Fay MP, Feuer EJ. Confidence intervals for directly standardized rates: a method based on the gamma distribution. Stat Med 1997;16:791-801. [Crossref] [PubMed]
20. Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950-2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:1989-2056. [Crossref] [PubMed]
21. Kim HJ, Fay MP, Feuer EJ, et al. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med 2000;19:335-51. [Crossref] [PubMed]
22. Das Gupta P. A general method of decomposing a difference between two rates into several components. Demography 1978;15:99-112.
23. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010;84:523-38. [Crossref] [PubMed]
24. Chevan A, Sutherland M. Revisiting Das Gupta: refinement and extension of standardization and decomposition. Demography 2009;46:429-49. [Crossref] [PubMed]
25. Ditonno F, Franco A, Manfredi C, et al. The Role of miRNA in Testicular Cancer: Current Insights and Future Perspectives. Medicina (Kaunas) 2023;59:2033. [Crossref] [PubMed]
26. Stephenson A, Eggener SE, Bass EB, et al. Diagnosis and Treatment of Early Stage Testicular Cancer: AUA Guideline. J Urol 2019;202:272-81. [Crossref] [PubMed]
27. Leão R, Albersen M, Looijenga LHJ, et al. Circulating MicroRNAs, the Next-Generation Serum Biomarkers in Testicular Germ Cell Tumours: A Systematic Review. Eur Urol 2021;80:456-66. [Crossref] [PubMed]
28. Global fertility in 204 countries and territories, 1950-2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021. Lancet 2024;403:2057-99. [Crossref] [PubMed]
29. Kerns SL, Fung C, Monahan PO, et al. Cumulative Burden of Morbidity Among Testicular Cancer Survivors After Standard Cisplatin-Based Chemotherapy: A Multi-Institutional Study. J Clin Oncol 2018;36:1505-12. [Crossref] [PubMed]
30. Smith ZL, Werntz RP, Eggener SE. Testicular Cancer: Epidemiology, Diagnosis, and Management. Med Clin North Am 2018;102:251-64. [Crossref] [PubMed]
31. Huyghe E, Muller A, Mieusset R, et al. Impact of diagnostic delay in testis cancer: results of a large population-based study. Eur Urol 2007;52:1710-6. [Crossref] [PubMed]
32. Zaid MA, Gathirua-Mwangi WG, Fung C, et al. Clinical and Genetic Risk Factors for Adverse Metabolic Outcomes in North American Testicular Cancer Survivors. J Natl Compr Canc Netw 2018;16:257-65. [Crossref] [PubMed]
33. Li Y, Lu Q, Wang Y, et al. Racial differences in testicular cancer in the United States: descriptive epidemiology. BMC Cancer 2020;20:284. [Crossref] [PubMed]
34. de Souza JA, Hunt B, Asirwa FC, et al. Global Health Equity: Cancer Care Outcome Disparities in High-, Middle-, and Low-Income Countries. J Clin Oncol 2016;34:6-13. [Crossref] [PubMed]
35. Zhang Y, Graubard BI, Klebanoff MA, et al. Maternal hormone levels among populations at high and low risk of testicular germ cell cancer. Br J Cancer 2005;92:1787-93. [Crossref] [PubMed]
36. Ilic D, Misso ML. Screening for testicular cancer. Cochrane Database Syst Rev 2011;CD007853. [Crossref] [PubMed]
37. Bräuner EV, Lim YH, Koch T, et al. Endocrine Disrupting Chemicals and Risk of Testicular Cancer: A Systematic Review and Meta-analysis. J Clin Endocrinol Metab 2021;106:e4834-60. [Crossref] [PubMed]
38. McGlynn KA, Trabert B. Adolescent and adult risk factors for testicular cancer. Nat Rev Urol 2012;9:339-49. [Crossref] [PubMed]
39. Kalayasiri R, Boonthae S. Trends of cannabis use and related harms before and after legalization for recreational purpose in a developing country in Asia. BMC Public Health 2023;23:911. [Crossref] [PubMed]
40. Daling JR, Doody DR, Sun X, et al. Association of marijuana use and the incidence of testicular germ cell tumors. Cancer 2009;115:1215-23. [Crossref] [PubMed]
41. Littman AJ, Doody DR, Biggs ML, et al. Physical activity in adolescence and testicular germ cell cancer risk. Cancer Causes Control 2009;20:1281-90. [Crossref] [PubMed]
42. Cargnelutti F, Di Nisio A, Pallotti F, et al. Risk factors on testicular function in adolescents. J Endocrinol Invest 2022;45:1625-39. [Crossref] [PubMed]
43. Fu W, Zhao S, Zhang Y, et al. Research in health policy making in China: out-of-pocket payments in Healthy China 2030. BMJ 2018;360:k234. [Crossref] [PubMed]
44. Znaor A, Skakkebaek NE, Rajpert-De Meyts E, et al. Global patterns in testicular cancer incidence and mortality in 2020. Int J Cancer 2022;151:692-8. [Crossref] [PubMed]
45. Nezu K, Yamashita S, Kakimoto K, et al. Association of financial toxicity with quality of life in testicular cancer survivors. Int J Urol 2022;29:1526-34. [Crossref] [PubMed]