Research in context Evidence before this study We systematically searched PubMed using the terms (1) “childhood” or “pediatric”; (2) “cancer,” “neoplasm,” “malignancy,” or “tumour”; (3) “incidence,” “epidemiology,” or “burden”; and (4) “subtype”, “classification”, “histology”, “morphology”, “topography” or “ICD-O” for studies up to August 14, 2025. Most available data come from high-income countries, and comprehensive, subtype-specific epidemiological studies are lacking, particularly in low- and middle-income countries with limited cancer registry infrastructure. However, there is no global study that has provided a thorough, subtype-specific assessment of childhood cancer incidence, underscoring the gap that this research seeks to fill. Added value of this study To our knowledge, this study provides the first global estimates of childhood cancer burden disaggregated into 34 types of childhood cancer, based on 211,080 new cases and 78,441 deaths in 2022. We show that ALL comprises 66.73% of leukaemia, brain tumours account for 45.00% of central nervous system cancers, and Burkitt lymphoma dominates non-Hodgkin lymphoma, with the highest incidence in sub-Saharan Africa. Subtype-specific incidence rises with stronger universal health-coverage scores, indicating substantial under-diagnosis where health systems are weaker and establishing a detailed baseline for tracking progress toward WHO's 2030 survival target. Implications of all the available evidence The global epidemiological overview of childhood cancer subtypes, based on real-world, population-based cancer registry data, showed that incidence patterns vary markedly across regions, reflecting disparities in data quality, healthcare access, and diagnostic capacity. However, data quality and coverage remain limited in many regions, particularly in low- and middle-income countries, and case numbers for some subtypes and areas are small. These limitations may affect the precision and generalizability of the findings, highlighting the need to strengthen global childhood cancer surveillance systems.
Introduction
Childhood cancer is a concerning global health issue threatening the lives and health of children and adolescents, defined as a group of cancer that arises between birth and 19 years of age by World Health Organization (WHO). 1 According to the WHO estimates, 13.7 million cases will be diagnosed and 11.1 million children will die of childhood cancer in the next 30 years. 2 , 3 Childhood cancer showed distinguished characteristics from cancer diagnosed in other age groups regarding cancer types, risk factors, tumour biology, and prognosis and survivorship. 4 The most common types of childhood cancers include leukaemias, brain cancers, and lymphomas.
In 2018 WHO launched, with the support of St. Jude Children's Research Hospital, the Global Initiative for Childhood Cancer, to provide leadership and technical assistance to governments to support them in building and sustaining high-quality childhood cancer programmes. 5 The goal is to achieve at least 60% survival for all children with cancer by 2030. This represents an approximate doubling of the current cure rate and will save an additional one million lives over the next decade. The Global Initiative for Childhood Cancer is part of the response to the World Health Assembly Resolution Cancer Prevention and Control through an Integrated Approach (WHA70.12), focused on the reduction of premature mortality from non-communicable diseases (NCDs) and the achievement of universal health coverage. 6
Accurate epidemiology data regarding the childhood cancer is the fundamental basis to develop standards and tools to guide the planning and implementation of interventions for early diagnosis, treatment and palliative and survivorship care. 7 A 2025 editorial in The Lancet highlighted that population-based cancer registries serve as the gold standard for assessing national cancer burdens and informing priority-setting in health policy development. However, low- and middle-income countries (LMICs) experiencing the highest cancer burdens demonstrate limited availability of high-quality registry data, particularly regarding detailed epidemiological characterization of childhood cancers. 8 , 9 In this study, by using the global cancer registry data, we provided a detailed estimation for global incidence of childhood cancer by subtypes in 2022, describe the unique social determinants of childhood cancer burden, and put forward priorities and implications to inform policy and practice in global childhood cancer actions with the aim of achieving at least 60% survival for all children with cancer by 2030.
Methods
Data sources
This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) reporting guidelines. 10
Childhood cancer cases, defined as cancers occurring in individuals aged 0–19 years, categorized by subtype were obtained from the Cancer Incidence in Five Continents (CI5) Volumes XII, which was submitted by 670 population-based cancer registries worldwide at the national or subnational level covering the period 2013–2017. 11 A total of 34 childhood cancers were selected for this study. Tumour classification in this study followed the International Agency for Research on Cancer (IARC) CI5 coding framework, which is based on third edition of the International Classification of Diseases for Oncology (ICD-O-3) morphology and topography codes. This standardized coding was applied consistently across registries to ensure global comparability, 12 and detailed coding forms were listed in Supplemental Table S1 . Based on this framework, we classified subtypes using the smallest predefined units listed under each tumour category in the CI5 dataset. These subtype names were provided by the IARC and used directly without further regrouping. When the number of cases for a specific subtype was too small to report separately, we grouped them into other specified subtype within the corresponding major cancer type. This approach maximized the granularity of available data while preserving reporting stability. To ensure the robustness and reliability, we selected the 10 most prevalent childhood cancer types to conduct the subtype analysis. Then proportion by subtypes among the top 10 childhood cancers were estimated using the population-based cancer registry database. The estimated national numbers and rate of new childhood cancer cases in 2022 by sex, 5-year age group, and region were obtained from the Global Cancer Observatory (GLOBOCAN) 2022 database. GLOBOCAN 2022 database was developed by the IARC, and provides estimates of cancer incidence and mortality for 185 countries, drawing primarily from population-based cancer registries where available. The quality of these data varies by country and is assessed by IARC in terms of completeness, comparability, and validity. Detailed documentation of data sources and quality indicators for each country is available through the IARC Cancer Today platform. GLOBOCAN estimates are periodically updated (previous editions include 2012, 2018, and 2020), with the 2022 dataset being the most recent release at the time of analysis. 13 The subtypes of Childhood cancer as described in the CI5 volumes in Supplemental Table S1 .
Ethics
This study used de-identified, aggregated data obtained from publicly accessible sources, including the CI5 and the GLOBOCAN 2022 databases, both developed by the IARC. All data were originally collected by population-based cancer registries worldwide under local regulatory and ethical frameworks. As this study involved secondary analysis of publicly available, non-identifiable data, ethical approval and informed consent were not required.
Subtype case estimation
We estimated each childhood cancer subtype based on the third edition of the ICD-O-3 codes, and excluded cancer registry data with a prevalence of each childhood cancer with unspecified of ≥75% at the national level in each stratum. Countries which met the inclusion criteria were included in the analysis, and national-level proportions of main subtype, other, and unspecified cases were calculated by 5-year age group ( Supplementary Table S2 ).
In the main analysis, we assumed that unspecified cases would likely be the main specific subtypes and reallocated them to these subtypes as per their relative proportions. Country specific subtype proportions were then applied to the incidence and number of new childhood cancer cases by 5-year age group, as estimated in GLOBOCAN 2022. For the remaining countries that did not provide country-specific childhood cancer registry data or met the exclusion criteria, sub regional average proportions of main specific subtypes and other specified subtype was calculated by aggregating the number of childhood cancer cases in the individual countries. Subregions were classified using the United Nations definitions, as follows: the Caribbean, Central, America, Eastern Asia, Eastern Europe, North America, Northern Africa, Northern Europe, Oceania, South America, South-Central Asia, South-Eastern Asia, Southern Europe, Sub-Saharan Africa, Western Asia, and Western Europe. 14 According to the standard adopted by the CI5, age-standardised rates (ASRs) of each main specific subtype and other specified subtype per 100,000 people years were calculated for each country and region in 2022 using the direct method and the World Standard Population. 15 Age trends of the crude rate of cervical cancer incidence were estimated separately by subtypes and by world regions.
Socioeconomic association
We conducted an ecological association analysis at the country level, examining the relationship between childhood cancer incidence by subtype and selected potential risk factors using aggregated national-level data. This approach aims to identify broad population-level patterns rather than establish individual-level causal relationships. The following variables were taken using the most recent available data for each country. 16 The sources, definitions, units, and years are detailed in Supplemental Table S103 . The Human Development Index (HDI) and the Gender Inequality Index (GII) were taken from the United Nations Development Programme. The Sociodemographic Index (SDI) and the Healthcare Access and Quality Index (HAQI) were sourced from the Global Burden of Disease Study 2021. The Universal Health Coverage (UHC) service coverage index, the number of physicians per 1000 population, nurses and midwives per 1000 population, and hospital beds per 10,000 population were obtained from the WHO's Global Health Observatory Indicator database. Gross domestic product (GDP) per capita (adjusted to 2022 USD), current health expenditure as a percentage of GDP (CHE [%GDP]), and out-of-pocket spending as a percentage of current health expenditure (OOP [%CHE]) were extracted from the WHO Global Health Expenditure Database (GHED). The number of radiotherapy cancer centers was taken from the Directory of Radiotherapy Centres, 17 and population data were used to derive number of radiotherapy centers per 1000 population. In multivariable linear regression analysis, beta coefficients ( β ) and the corresponding 95% confidence intervals ( CI s) were generated correspondingly from the regression.
Sensitivity analysis
For the sensitivity analyses, we used an alternative reallocation scheme. Cases with unspecified subtype in each childhood cancer were assigned to the main specific subtype and other specified subtype according to their relative proportions. The number and rate of the incident cases by the subtypes were estimated under this assumption.
Role of the funding source
The study sponsor had no role in study design, data analysis and interpretation of data, the writing of manuscript, or the decision to submit the paper for publication. All authors had full access to the data in the study. YJ had final responsibility for the decision to submit for publication.
Results
Global childhood cancer incidence and mortality description
In 2022, 211,080 new cases of childhood tumours and 78,441 deaths emerged globally. The top 10 leading causes of incident childhood cancer were leukaemia, brain and central nervous system (BCNS) tumours, non-Hodgkin's lymphoma (NHL), Hodgkin's lymphoma, kidney, thyroid, testis, liver and intrahepatic bile ducts, ovary, and colorectum ( Fig. 1 and Supplemental Table S124 ). The leading causes of deaths in childhood cancer listed as follows: Leukaemia, BCNS tumours, NHL, kidney, liver and intrahepatic bile ducts, Hodgkin's lymphoma, Kaposi sarcoma, ovary, nasopharynx, and trachea, bronchus and lung. Leukaemia is the leading cause of childhood cancer incidence and mortality in 2022, with 77,660 newly diagnosed cases and 31,106 deaths, according for 36.79% of the total incident cases and 39.66% of total deaths due to childhood cancers. The second leading causes of deaths was BCNS tumours, with 30,868 newly diagnosed cases and 15,541 deaths, according for 14.62% of the total incident cases and 19.81% of total deaths due to childhood cancers. Fig. 1 Global incidence and mortality cases from childhood cancers as estimated by Global Cancer Observatory 2022.
Different composition patterns were observed for boys and girls. The number of new childhood cancer cases was generally higher in boys than in girls, with 118,555 incident cases in boys and 92,525 incident cases in girls, and the pattern was observed for leukaemia, BCNS tumours, NHL, hodgkin lymphoma, kidney, liver and intrahepatic bile ducts, nasopharynx, colorectum, kaposi sarcoma, non-melanoma skin cancer, lip, oral cavity, trachea, bronchus and lung, stomach, bladder, oropharynx, oesophagus, multiple myeloma, larynx, and hypopharynx. Similarly, the number of childhood cancer deaths was higher in boys, with 45,942 incident cases in boys and 32,499 incident cases in girls, and the pattern was observed for leukaemia, BCNS tumours, NHL, hodgkin lymphoma, kidney, liver and intrahepatic bile ducts, nasopharynx, Kaposi sarcoma, trachea, bronchus and lung, colorectum, stomach, lip, oral cavity, non-melanoma skin cancer, oesophagus, multiple myeloma, bladder, larynx, and hypopharynx.
Proportion of subtypes among the leading childhood cancers
With the population-based cancer registry data, the proportion of subtypes among the top 10 leading childhood cancers was estimated and presented in Fig. 2 . For leukaemia, acute lymphoblastic leukaemia (ALL), chronic lymphoid leukaemia (CLL), acute myeloid leukaemia (AML), and chronic myeloid leukaemia (CML) accounted for about 66.73%, 0.25%, 17.46%, and 2.97% of the incidence new cases. For BCNS tumours, brain tumour was the leading subtypes (45.00%), followed by Astrocytic tumours (16.81%). Burkitt Lymphoma accounted for 17.64% of NHL, and renal cell carcinoma accounted for 8.35% of kidney tumours. Nodular sclerosis was the most common type of hodgkin lymphoma, representing more than 55.50% of cases. Non-seminomatous germ cell tumours (76.43%), germ cell tumours (69.22%), papillary carcinoma (86.72%), hepatoblastoma (63.16%), and appendix (80.28%) were identified as the most prevalent subtypes in testis, ovary, thyroid, liver, and colorectum, respectively. Fig. 2 Global proportion of different subtypes of childhood cancer in 2022. (A) Leukaemia. (B) Brain and central nervous system tumour. (C) Non-Hodgkin lymphoma. (D) Hodgkin lymphoma. (E) Kidney and renal pelvis. (F) Thyroid. (G) Testis. (H) Liver. (I) Ovary. (J) Colorectum.
Disease burden according to childhood cancer subtypes
The disease burden was estimated based on the total childhood cancer burden and the proportion by the subtypes. The disease burden of the top 3 leading causes of deaths in childhood cancer (leukaemia, BCNS tumours, and NHL) was listed in the main text, and others were listed in the Supplemental Materials due to the space constrains.
Leukaemia
In 2022, an estimated 56,695 (73.05%) new cases of ALL were diagnosed worldwide, alongside 218 (0.28%) cases of CLL, 14,901 (19.11%) cases of AML, 2598 (3.25%) cases of CML, and 3268 (4.31%) cases of other specified subtypes, resulting in an ASR of 2.04, 0.01, 0.53, 0.09, and 0.12 per 100,000 population, separately. Boys and girls showed distinguished patterns in the incidence of leukaemia subtypes. The ASR of ALL reached 1.69 per 100,000 population for girls, and 2.34 per 100,000 population for boys. Geographic variations were observed. The highest number of cases was reported for all major subtypes in South-Central Asia, with 15,280 cases of ALL, 69 cases of CLL, 4101 cases of AML, and 875 cases of CML. Regarding the age-standardized rates, Central America had the highest ASR for ALL at 3.98 per 100,000 population, Eastern Europe exhibited the highest ASR for CLL at 0.03 per 100,000 population. South-Eastern Asia showed the highest ASR for both AML (1.13 per 100,000 population) and CML (0.18 per 100,000 population). At the national level, India reported the highest number of ALL cases with 9858 incident cases, while Peru had the highest ASR for ALL at 6.29 per 100,000 population. For CLL, China recorded the largest number of cases (59 incident cases), but Malta exhibited the highest ASR of 0.35 per 100,000 population. In the case of AML, China reported the highest cases (3216 incident cases), while Brunei Darussalam had the highest ASR at 2.16 per 100,000 population. Regarding CML, India led with the highest number of cases (599 incident cases), whereas Malta again showed the highest ASR for this subtype at 0.70 per 100,000 population. ( Fig. 3 and Supplementary Materials ). Fig. 3 Age-standardised incidence rate (ASR) of leukaemia by subtype per 100,000 person-years. (A) Acute lymphoblastic leukaemia. (B) Chronic lymphoid leukaemia. (C) Acute myeloid leukaemia. (D) Chronic myeloid leukaemia.
Brain and central nervous system (BCNS) tumour
In BCNS tumour, an estimated 14,659 (47.32%) incident cases of brain tumour were diagnosed worldwide, alongside 5537 (17.68%) cases of astrocytic tumours, 1371 (4.52%) cases of ependymal tumours, 2978 (9.66%) cases of gliomas of uncertain origin, 2584 (8.42%) cases of medulloblastoma, 1062 (3.63%) cases of other embryonal tumours, and 2680 (8.77%) cases of other specified subtype of BCNS tumours, resulting in an ASR of 0.56, 0.21, 0.05, 0.11, 0.10, 0.04, and 0.10 per 100,000 population, separately. Sex-based differences were observed in subtype distribution. The ASR of brain tumour reached 0.50 per 100,000 population for girls aged 0–19 years, and 0.62 per 100,000 population for boys. Geographic variations were observed. The highest number of incident cases was reported in South-Central Asia: 3583 cases of brain, 872 cases of astrocytic tumours, 311 cases of ependymal tumours, 613 cases of gliomas of uncertain origin, 742 cases of medulloblastoma, and 402 cases of other embryonal tumours. Regarding age-standardized rates, North America had the highest ASR for brain tumour (1.46 per 100,000 population), astrocytic tumours (0.76 per 100,000 population), ependymal tumours (0.13 per 100,000 population), and gliomas of uncertain origin (0.36 per 100,000 population). At the national level, China reported the highest number of brain tumour cases (2976 incident cases in 2022), while Montenegro had the highest ASR for brain tumour at 1.71 per 100,000 population. For astrocytic tumours, United States recorded the largest number of cases (636 incident cases) and the highest ASR of 0.78 per 100,000 population. For gliomas of uncertain origin, India reported the highest cases (420 incident numbers), while Portugal had the highest ASR at 0.64 per 100,000 population ( Fig. 4 and Supplementary Materials ). Fig. 4 Age-standardised incidence rate (ASR) of brain and central nervous system tumours by subtype per 100,000 person-years. (A) Astrocytic tumours. (B) Ependymal tumours. (C) Gliomas of uncertain origin. (D) Medulloblastoma. (E) Other embryonal tumours. (F) Brain.
Non-hodgkin lymphoma (NHL)
Burkitt lymphoma is the leading subtype of NHL, resulted in 4353 incident cases worldwide in 2022, and an ASR of 0.17 per 100,000 population. Boys experienced a higher incidence of NHL than girls, with an ASR of 0.26 per 100,000 population for boys aged 0–19 years compared with the rate of 0.07 per 100,000 population for girls. Sub-Saharan Africa reported the highest number of incident cases including 1948 cases of Burkitt lymphoma, and 5843 cases of other specified subtype, followed by South-Central Asia with 447 Burkitt lymphoma cases, 13 immunoproliferative diseases and 3537 other specified subtype cases. Northern Africa was with the highest ASR of Burkitt lymphoma at 0.41 per 100,000 population, with several other regions surpassing an ASR of 0.30: Central America (0.31), Southern Europe (0.35), sub-Saharan Africa (0.32), and Western Asia (0.32). At the national level, India reported the highest number of Burkitt lymphoma (280 incident cases) and other specified subtype (2287 incident cases), of which boys accounted for 235 (83.93%) and 1575 (68.87%) cases respectively. Malawi had the highest ASR for Burkitt lymphoma (2.30 per 100,000 population) and other specified subtype (5.11 per 100,000 population). This disparity persisted across sexes in Malawi, with boys showing notably higher rates (Burkitt lymphoma ASR 2.95; other subtypes 6.47 per 100,000 population) compared to girls (Burkitt lymphoma ASR 1.65; other subtypes 3.78 per 100,000 population) ( Fig. 5 and Supplementary Materials ). Fig. 5 Age-standardised incidence rate (ASR) of non-hodgkin lymphoma by subtype per 100,000 person-years. (A) Burkitt lymphoma. (B) Immunoproliferative diseases. (C) Other non-Hodgkin lymphoma.
Socioeconomic association
The association between socioeconomic status and the incidence by subtypes was explored and listed in Fig. 6 and Supplementary Tables S103–S122 ). On univariable analysis, UHC was significantly associated with leukaemia (ALL: β = 0.0592, p < 0.0001; CLL: β = 0.0004, p = 0.0021; AML: β = 0.0098, p < 0.0001), BCNS tumours (astrocytic tumours: β = 0.0057, p < 0.0001; ependymal tumours: β = 0.0022, p < 0.0001; gliomas of uncertain origin: β = 0.0031, p < 0.0001; medulloblastoma: β = 0.0040, p < 0.0001; other embryonal tumours: β = 0.0011, p < 0.0001; brain tumours: β = 0.0166, p < 0.0001), NHL (immunoproliferative diseases: β = 0.0002, p < 0.0001), Hodgkin lymphoma (nodular lymphocytic predominance: β = 0.0015, p < 0.0001; nodular sclerosis subtype, β = 0.0129, p < 0.0001), testis (seminomas: β = 0.0038, p < 0.0001; non-seminomatous germ cell tumours, β = 0.0220, p < 0.0001), ovary (serous carcinoma: β = 0.0002, p = 0.0039), thyroid cancer (follicular carcinoma, β = 0.0009, p < 0.0001; papillary carcinoma, β = 0.0115, p < 0.0001), liver and intrahepatic bile ducts (hepatocellular carcinoma, β = −0.0025, p < 0.0001), and colorectum (appendix, β = 0.0036, p < 0.0001). Other metrics also demonstrated varying levels of association with different childhood cancer subtypes and are detailed in Supplementary Tables S103–S112 . To address potential multicollinearity, all available metrics were initially included in the multivariable model. Variance inflation factor (VIF) analysis revealed a high degree of collinearity between HDI and other metrics, with HDI exhibiting the highest VIF (VIF > 20). Given this finding and the conceptual overlap between HDI and SDI, HDI was excluded from the final model. After exclusion, all remaining metrics had VIF values below 10, indicating an acceptable level of multicollinearity. The adjusted model retained high explanatory power. To further explore the independent associations between key health system indicators and childhood cancer incidence by subtype, we selected three metrics for visualization: HAQI, CHE (%GDP), and UHC. These metrics demonstrated the most consistent and statistically significant associations ( P < 0.05) across multiple subtypes in the final model. Fig. 6 presents the associations of these three metrics with the top ten childhood cancers and their subtypes based on multivariable regression analyses. Detailed results are provided in Supplementary Tables S113–S122 . Fig. 6 Multivariable analyses of associations between UHC, HAQI, and CHE (%GDP) and the incidence of childhood cancer subtypes. Note: UHC, Universal Health Coverage service coverage index; HAQI, Healthcare Access and Quality Index; CHE (%GDP), Current health expenditure as a percentage of gross domestic product; OR, Odds ratio; CI, Confidence interval. Only three core indicators (UHC, HAQI, and CHE [%GDP]) were selected for visualization.
Sensitivity analysis
In the alternative scenario, we allocated cases with unspecified subtypes in each childhood cancer to the main specific subtype and other specified subtype groups of each childhood cancer according to their relative proportions. Robust results were identified compared with the main analysis. For leukaemia, ALL, AML, CLL and CML took the proportion of 72.75%, 0.28%, 19.03%, and 3.24% separately. The ASR for these subtypes were 2.03, 0.01, 0.53, and 0.09 per 100,000 population, separately. Brain cancer was the leading subtype in BCNS tumours, which is robust with the main analysis, comprising 47.11% of all cases, with an ASR of 0.56 per 100,000 population. Detailed information of the incident cases and age-standardized rate of other specified subtypes of the childhood cancer in the alternative scenario could be found in the Supplemental Materials .
Discussion
Cancer is a leading cause of death for children and adolescents. WHO launched the Global Initiative for Childhood Cancer, aimed to achieve at least 60% survival for all children with cancer by 2030. 5 In this study, we described the incidence of childhood cancer by subtypes, sex, geographic regions and socioeconomic levels, by using the high-quality population-based cancer registry data. The estimation from this study would have implications for the resource allocation to motivate the global cooperation on childhood cancer.
Leukaemia remains the leading cause of childhood cancer incidence and mortality worldwide, accounting for 36.79% of all newly diagnosed cases and 39.66% of cancer-related deaths among children. In this study, ALL was the predominant subtype, comprising 66.73% of all leukaemia cases. ALL is a haematological malignancy characterised by the uncontrolled proliferation of immature lymphoid precursor cells. Although it occurs in both children and adults, its incidence peaks between the ages of 1 and 4 years. 18 The pathogenesis of ALL is driven by chromosomal abnormalities and genetic alterations affecting lymphoid cell differentiation and proliferation. Over the past decades, significant advances in understanding the molecular biology of ALL have led to remarkable improvements in its diagnosis, treatment, and monitoring. Several risk factors and predisposing conditions for ALL have been identified. These include male sex, Caucasian ethnicity, a family history of leukaemia, and environmental exposures such as ionizing radiation, prior chemotherapy or radiotherapy, and toxins including mycotoxins and hydrocarbons such as benzene. 19 Risk stratification and the implementation of intensified chemotherapy regimens have substantially improved survival outcomes, particularly among children with cancer. 20 Screening for ALL remains a challenge due to the absence of well-established early detection programmes. Currently, there are no universal screening guidelines for ALL, since population-based screening is not feasible given the disease's relatively low incidence and lack of specific pre-leukaemic markers. Advances in genomic technologies have facilitated the identification of predisposing mutations, offering potential avenues for early detection in high-risk populations. Further research is required to evaluate the clinical utility, cost-effectiveness, and accessibility of such targeted screening approaches, particularly in resource-limited settings where disparities in outcomes persist.
Sex difference was observed for BCNS tumours, as reported that boys showing a slightly higher incidence of brain tumours (ASR: 0.62 per 100,000 population) compared to girls (ASR: 0.50 per 100,000 population). This finding aligns with previous research, which consistently reports a higher male-to-female ratio in BCNS tumours, with brain tumours being more frequent in males (58%) than in females (41%). 21 Sex differences were also evident in treatment outcomes and prognosis. A Surveillance, Epidemiology, and End Results (SEER) analysis of patients with glioblastoma treated surgically between 2000 and 2008 reported a longer survival in women, with a 5-year cancer-specific survival of 8.3% compared with 6.8% in men. 22 This survival advantage for women was further confirmed in the National Cancer Institute SEER programme. 23 The observed sex disparity in BCNS tumours is likely influenced by biological and socioeconomic factors. Sex-specific genetic risk factors and tumour-specific sex biology have been implicated, alongside environmental and developmental influences. High birth weight, non-chromosomal structural birth defects, and higher socioeconomic position have been identified as risk factors for BCNS tumours in children. 24 In adults, increased leukocyte telomere length, European ancestry proportion, higher socioeconomic status, and certain HLA haplotypes are associated with an elevated risk of malignant brain tumours, whereas immune-related factors appear protective. Experimental studies suggest that male astrocytes exhibit a stronger response to neoplastic transformation, and immunosuppressive myeloid-derived suppressor cells may contribute to the increased susceptibility of males to brain cancer. 25 , 26
NHL is another prominent childhood cancer, with Burkitt lymphoma being the most common subtype, exhibiting notable geographic variation globally. In this study, we observed the highest number of incident cases emerging in sub-Saharan Africa, which was of significant difference from other childhood cancers. Burkitt lymphoma has played a pivotal role in advancing the understanding of tumourigenesis. It was the first human tumour linked to a virus, 27 among the first cancers shown to involve a chromosomal translocation activating an oncogene, 28 and the first lymphoma reported to be associated with HIV infection. 29 The disease is highly prevalent in regions where malaria is holoendemic, such as equatorial Africa, Brazil, and Papua New Guinea. 30 The so-called Burkitt lymphoma belt spans central Africa, extending 15° north and south of the equator, where the climate is hot and wet. Epidemiological studies have demonstrated a strong overlap between malaria-endemic areas and Burkitt lymphoma incidence. 30 Burkitt lymphoma is strongly associated with Epstein–Barr virus infection and is characterised by chromosomal translocations involving the MYC oncogene. 31 In non-endemic regions, Burkitt lymphoma incidence is significantly elevated in immunosuppressed individuals, particularly those with HIV infection. 32 Intensive chemotherapy has markedly improved survival rates in children with cancer, and success of therapy is highly dependent on comprehensive supportive care, which is often suboptimal in low-income settings. 33 In many resource-limited regions, treatment protocols are less aggressive than those employed in high-income countries, contributing to inferior survival rates. Strengthening health systems—through improved access to chemotherapy, expansion of the oncological workforce, and comprehensive community-based healthcare—is essential to improving survival and long-term quality of life for affected children.
The ecological correlations observed in this study provide insights into potential population-level determinants of childhood cancer incidence across countries. Childhood cancer incidence is higher in countries with stronger socioeconomic conditions, particularly those with a higher GDP per capita, and UHC service index. 34 This trend is consistent with the notion that improved healthcare infrastructure, advanced diagnostic capabilities, and greater access to treatment contribute to higher reported incidence rates. Notably, higher levels of UHC and HAQI were significantly associated with increased incidence of childhood cancers. Two possible explanations were raised. First, more complete and accurate cancer registration in these countries likely reduces underreporting, particularly for rarer subtypes, making incidence appear higher compared with LMICs where registry coverage and diagnostic capacity are limited. 8 , 35 Second, genuine differences in risk may also contribute, reflecting environmental exposures, lifestyle factors, genetic predispositions, or other underlying determinants that vary by region. Both factors should be considered when interpreting observed correlations between UHC and subtype-specific cancer incidence, and caution is needed in attributing higher incidence solely to reporting completeness.
We attempted to examine temporal trends in childhood cancer subtypes, but inconsistent and incomplete registry data in many countries prevented robust analyses. These limitations underscore the need to strengthen global childhood cancer registries by improving data completeness, continuity, and diagnostic precision to support monitoring and evidence-based policy. In response to global disparities in childhood cancer outcomes, the WHO launched the Global Initiative for Childhood Cancer in 2018, with support from St. Jude Children's Research Hospital (USA), the International Agency for Research on Cancer (IARC), and other international partners. The initiative aims to achieve at least 60% survival for children with cancer globally by 2030. As part of this effort, IARC leads the ChildGICR (Targeting Childhood Cancer through the Global Initiative for Cancer Registry Development) project, which seeks to improve the quality and availability of childhood cancer data, particularly in resource-limited settings.
This study's main strength lies in its use of high-quality, population-based cancer registry data, which allows for a comprehensive and global analysis of childhood cancer incidence. The large sample size and diverse geographical coverage enhance the generalizability of the findings. However, there are several limitations to consider. First, accuracy of the data may vary across countries, particularly in regions with less-developed healthcare infrastructure. For many low- and middle-income countries, incidence estimates are derived using hierarchical modeling approaches based on partial or proxy data, and uncertainty intervals are not provided in the GLOBOCAN dataset. Therefore, caution should be exercised when interpreting national estimates. Second, the tumour groupings presented reflect the IARC CI5 coding system rather than a clinically tailored pediatric oncology classification. While this approach enables standardized comparisons across countries and cancer registries, it may result in categories that are less intuitive from a clinical standpoint. These differences should be considered when interpreting site-specific incidence patterns in children. Third, although our study provides subtype-specific estimates across 34 childhood cancer types, the diagnostic granularity and completeness of registry data may vary across settings. Some cancer cases may lack detailed subtype assignment or be classified based on limited clinical information, particularly in lower-resource regions. These limitations may affect the robustness of subtype-level incidence estimates and should be acknowledged when interpreting the results. Fourth, due to data limitations, this study estimates only incidence patterns, while corresponding survival outcomes related to the WHO goal require further evaluation. Finally, while these findings help generate hypotheses for future research, they should be interpreted with caution given the limitations inherent to country-level ecological designs, including the inability to infer causality at the individual level.
In conclusion, this study highlights the urgent need for a high-quality childhood cancer registry platform to conduct a precision-based childhood cancer prevention programme. Regional variations in incidence reflect the complex interplay of healthcare access, socioeconomic conditions, and environmental exposures. Strengthening healthcare systems, enhancing cancer registries, and increasing public awareness through international collaboration are essential to achieving equitable outcomes for all children with cancer. However, the analysis is limited by incomplete or low-quality registry data, particularly in LMICs, which may affect the accuracy of incidence estimates and hinder international comparability. These collective efforts are crucial to advancing survival and quality of life, aligning with the WHO's Global Initiative for Childhood Cancer goal of achieving at least a 60% survival rate for all children with cancer by 2030.
Contributors
MW and YB contributed equally to this work. MW and YB were responsible for conceptualisation, data curation, formal analysis, visualisation, and writing of the original draft. YF and XF contributed to methodology development, validation of disease classification, and interpretation of the findings. YJ was responsible for supervision, project administration, funding acquisition, and writing review and editing. MW and YB accessed and verified the underlying data. YJ had final responsibility for the decision to submit the manuscript. All authors reviewed and approved the submitted version.
Data sharing statement
The data sets generated and/or analyzed during the current study are available in the Cancer Incidence in Five Continents project ( https://ci5.iarc.fr/ci5-xii/ ) and Global Cancer Observatory 2022 database ( https://gco.iarc.fr/ ).
Editor note
The Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations.
Declaration of interests
The authors declare no conflict of interest.
References
1 Siegel R.L. Miller K.D. Wagle N.S. Jemal A. Cancer statistics, 2023 CA Cancer J Clin 73 1 2023 17 48 36633525 10.3322/caac.21763
2 World Health Organization WHO global initiative for childhood cancer. Increasing access, advancing quality, saving lives 2021
3 Atun R. Bhakta N. Denburg A. Sustainable care for children with cancer: a lancet oncology commission Lancet Oncol 21 4 2020 e185 e224 32240612 10.1016/S1470-2045(20)30022-X
4 Miller K.D. Fidler-Benaoudia M. Keegan T.H. Hipp H.S. Jemal A. Siegel R.L. Cancer statistics for adolescents and young adults, 2020 CA Cancer J Clin 70 6 2020 443 459 32940362 10.3322/caac.21637
5 World Health Organization CureAll framework: WHO global initiative for childhood cancer: increasing access, advancing quality, saving lives 2021
6 World Health Organization Technical report: pricing of cancer medicines and its impacts: a comprehensive technical report for the World Health Assembly Resolution 70.12: operative paragraph 2.9 on pricing approaches and their impacts on availability and affordability of medicines for the prevention and treatment of cancer 2018
7 Bhakta N. Force L.M. Allemani C. Childhood cancer burden: a review of global estimates Lancet Oncol 20 1 2019 e42 e53 30614477 10.1016/S1470-2045(18)30761-7
8 Erdmann F. Frederiksen L.E. Bonaventure A. Childhood cancer: survival, treatment modalities, late effects and improvements over time Cancer Epidemiol 71 2021 101733 10.1016/j.canep.2020.101733 32461035
9 The L. Cancer registries: the bedrock of global cancer care Lancet 405 10476 2025 353 39892893 10.1016/S0140-6736(25)00189-8
10 Stevens G.A. Alkema L. Black R.E. Guidelines for accurate and transparent health estimates reporting: the GATHER statement Lancet 388 10062 2016 e19 e23 27371184 10.1016/S0140-6736(16)30388-9
11 Bray F.C.M. Aitken J.F. Bardot A. Cancer incidence in five continents, Vol. XII (IARC CancerBase No. 19) 2023 International Agency for Research on Cancer Lyon
12 World Health Organization International classification of diseases for oncology (ICD-O) 2013 World Health Organization
13 Bray F. Laversanne M. Sung H. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries CA Cancer J Clin 74 3 2024 229 263 38572751 10.3322/caac.21834
14 Bongaarts J. United nations department of economic and social affairs, population division world family planning 2020: highlights, united nations publications, 2020 2020 Wiley Online Library 46
15 Bray F. Age-standardization Cancer Incidence Five Continent 8 2002 87 89
16 Dee E.C. Wu J.F. Feliciano E.J.G. National cancer system characteristics and global pan-cancer outcomes JAMA Oncol 11 6 2025 650 654 40208599 10.1001/jamaoncol.2025.0473 PMC11986824
17 Division for Human Health What is Directory of Radiotherapy Centres (DIRAC) https://dirac.iaea.org/ 2024
18 Malard F. Mohty M. Acute lymphoblastic leukaemia Lancet 395 10230 2020 1146 1162 32247396 10.1016/S0140-6736(19)33018-1
19 Pagliaro L. Chen S.-J. Herranz D. Acute lymphoblastic leukaemia Nat Rev Dis Primers 10 1 2024 41 38871740 10.1038/s41572-024-00525-x
20 O'Connor D. Enshaei A. Bartram J. Genotype-specific minimal residual disease interpretation improves stratification in pediatric acute lymphoblastic leukemia J Clin Oncol 36 1 2018 34 43 29131699 10.1200/JCO.2017.74.0449 PMC5756322
21 Ostrom Q.T. Cioffi G. Gittleman H. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2012-2016 Neuro Oncol 21 Suppl 5 2019 v1 v100 31675094 10.1093/neuonc/noz150 PMC6823730
22 Tian M. Ma W. Chen Y. Impact of gender on the survival of patients with glioblastoma Biosci Rep 38 6 2018 BSR20180752 10.1042/BSR20180752 PMC6239255 30305382
23 Ostrom Q.T. Rubin J.B. Lathia J.D. Berens M.E. Barnholtz-Sloan J.S. Females have the survival advantage in glioblastoma Neuro Oncol 20 4 2018 576 577 29474647 10.1093/neuonc/noy002 PMC5909625
24 Ostrom Q.T. Francis S.S. Barnholtz-Sloan J.S. Epidemiology of brain and other CNS tumors Curr Neurol Neurosci Rep 21 12 2021 68 34817716 10.1007/s11910-021-01152-9 PMC8613072
25 Sun T. Warrington N.M. Luo J. Sexually dimorphic RB inactivation underlies mesenchymal glioblastoma prevalence in males J Clin Invest 124 9 2014 4123 4133 25083989 10.1172/JCI71048 PMC4151215
26 Bayik D. Zhou Y. Park C. Myeloid-derived suppressor cell subsets drive glioblastoma growth in a sex-specific manner Cancer Discov 10 8 2020 1210 1225 32300059 10.1158/2159-8290.CD-19-1355 PMC7415660
27 Epstein M.A. Achong B.G. Barr Y.M. Virus particles in cultured lymphoblasts from Burkitt's lymphoma Lancet 1 7335 1964 702 703 14107961 10.1016/s0140-6736(64)91524-7
28 Zech L. Haglund U. Nilsson K. Klein G. Characteristic chromosomal abnormalities in biopsies and lymphoid-cell lines from patients with Burkitt and non-Burkitt lymphomas Int J Cancer 17 1 1976 47 56 946170 10.1002/ijc.2910170108
29 Schulz T.F. Boshoff C.H. Weiss R.A. HIV infection and neoplasia Lancet 348 9027 1996 587 591 8774574 10.1016/S0140-6736(95)11033-X
30 Parkin D.M.F.J. Hamdi-Chérif M. Sitas F. Thomas J.O. Wabinga H. Whelan S.L. Cancer in Africa: epidemiology and prevention 2003 IARC Scientific Publications Lyon, France
31 Molyneux E.M. Rochford R. Griffin B. Burkitt's lymphoma Lancet 379 9822 2012 1234 1244 22333947 10.1016/S0140-6736(11)61177-X
32 Zoufaly A. Stellbrink H.J. Heiden M.A. Cumulative HIV viremia during highly active antiretroviral therapy is a strong predictor of AIDS-related lymphoma J Infect Dis 200 1 2009 79 87 19476437 10.1086/599313
33 Arora R.S. Eden T. Pizer B. The problem of treatment abandonment in children from developing countries with cancer Pediatr Blood Cancer 49 7 2007 941 946 17252565 10.1002/pbc.21127
34 World Health Organization Childhood cancer inequalities in the WHO European region 2022
35 Magrath I. Steliarova-Foucher E. Epelman S. Paediatric cancer in low-income and middle-income countries Lancet Oncol 14 3 2013 e104 e116 23434340 10.1016/S1470-2045(13)70008-1
Supplementary data
Supplementary materials
Acknowledgements
This study was funded by 10.13039/501100001809 National Natural Science Foundation of China (No. 72274005 and No. 72304013 ) and Beijing Natural Science Foundation ( 9232009 ).
We acknowledged Cancer Incidence in Five Continents (CI5) programme and Global Cancer Observatory coordinated by the 10.13039/100008700 International Agency for Research on Cancer (IARC). We extend our gratitude to all 670 population-based cancer registries contributing to CI5 and GLOBOCAN for their rigorous data collection efforts.
Supplementary data related to this article can be found at https://doi.org/10.1016/j.eclinm.2025.103571 .