Traditionally studies of disease are based on incidence and survival using nation and disease specific incidence and outcome data. In the cancer setting, examples include the NORDCAN data set for Scandinavian countries, the National Cancer Registration and Analysis Service for cancer registrations in England, and the Surveillance, Epidemiology and End Results programme for the USA (1-3). Whilst undeniably valuable in guiding disease specific healthcare planning within a registry area, data is limited to those high-income countries (HICs) with registries, providing little insight into cancer diagnoses across nations, for example those with low or middle incomes (LMIC) where there may be little data regarding cancer incidence and outcomes. Furthermore, registrations of incidence and mortality give little insight into associated morbidity and are of limited utility in healthcare planning across different disease states for which registry data may not be available.
Thus, the DALY [disability adjusted life year comprising years of life lost (YLL) and years lived with disability (YLD)] was introduced in the 1990s as a means of measuring the difference between ‘ideal’ and ‘actual’ health status within a population (4). The DALY has been found to be particularly useful in assessing population health, the evaluation of intervention programmes and the setting of healthcare priorities, particularly in LMICs where detailed registry data may be lacking (5).
Childhood cancer is a particular exemplar where deriving DALY data from LMICs is of crucial importance to improving outcomes. Children from HICs with cancer often have an 80% 5-year survival rate (6,7), yet the majority of the world’s childhood population live in LMICs, where advances in modern medicine often do not reach, a situation compounded by a paucity of registry incidence and outcome data.
Given the absence of evidence for lifestyle interventions in decreasing the incidence of childhood cancers or the effectiveness of population screening programmes (other than the relatively uncommon cases where there may be a high risk genetic predisposition-some malignancies such as retinoblastoma, malignant rhabdoid tumour, and childhood adrenocortical carcinoma have a >40% rate of germline predisposing pathogenic variants in RB1, SMARCB1 and TP53 respectively) in decreasing the incidence of childhood cancers, the main factor influencing outcome for childhood cancers is access to early diagnosis when symptomatic, coupled with early intervention. To help enable this through appropriate health resource allocation, accurate estimates of cancer burden are critical.
The Global Burden of Disease Study (GBD), utilises DALYs to quantify morbidity and mortality from major diseases, injuries and risk factors to health at a global, national and regional level with the aim of improving health systems and eliminating disparities (8,9). The past 20 years have seen many publications arising from this data but, until now, data specifically relating to childhood and adolescent cancers have not been studied (10).
The Childhood Cancer Collaborators study is particularly timely following the announcement of the WHO Global Initiative for Childhood Cancer in September 2018 (11). This initiative aims to increase the overall survival for six key childhood cancers, namely ALL, Burkitt’s Lymphoma, Hodgkin Lymphoma, low grade glioma, retinoblastoma and Wilms tumour, which have high long-term survival in HICs. To help identify those high yield opportunities for improving outcomes, knowledge regarding regional and national differences in disease burden is essential.
Utilising the childhood and adolescent cancer data from the GBD 2017 data, the Childhood Cancer Collaborators have investigated the DALYs arising from childhood and adolescent cancer diagnoses in the 0–19 years age group providing the first analysis of the burden of disease arising globally from childhood cancer (12). Being the first study of its kind, this is a critical first step in improving outcomes by accurately estimating where, and for which categories, resources need to be allocated most.
The most stark findings were not only the 11.5 million DALYs globally attributable to childhood cancer, but the 97% being attributed to YLL with only 3% due to YLD. Given that the majority of the DALYs occurred in LMICs with low to low-middle sociodemographic indices (SDI) it is likely that the disproportionate YLL burden arises from lower survival rates in countries with frail health systems where there is a greater proportion of later stage diagnoses and more limited treatment options (13). Furthermore, when considering the global burden of all cancers (adult and children, as expressed by DALYs), childhood cancers were the leading cause of cancer burden in these low and low-middle income countries, further compounded by >99% of the DALYs comprising YLL.
Yet, intriguingly, for some of these LMICs with high age standardised DALY rate for childhood cancers, the reciprocal was true was for adult cancers. Thus, LMICs countries such as Egypt and Sudan, whilst being in the 5th quintile (≥441 DALYs per 100,000 person-years) for childhood cancers, were in the 1st (<222 DALYs per 100,000 person-years) for adult cancers. Whilst the reason for such a discrepancy may not be immediately obvious, and one might expect a low resource healthcare system being applicable to all ages within a nation, one reason for this apparent discrepancy may arise from overall lower life expectancy (both <75 years in 2017) as the majority of adult cancers develop with increasing age, for example >1/3 cancer diagnoses in the UK occur in those ≥75 years (14,15).
This may also explain another apparent discrepancy with HICs such as the UK, USA, Greenland and France being in the 1st or 2nd quintiles for childhood cancers yet the 4th or 5th for adult cancers with adults living longer and being exposed to environmental risk factors over a longer time period. Yet within this there remains unexplained discrepancies with, for example, Colombia, an upper middle-income country with a life expectancy of 76.9 years, being in the 5th centile for childhood cancers and the 1st for adult cancers. The reasons underlying this and other apparent discrepancies may not be immediately clear, but are likely complex and multi-factorial reflecting challenges ranging from data ascertainment to health care delivery.
Interrogating the childhood cancer data further, sub-Saharan Africa has the greatest DALY burden than any other of the GBD super-regions. Here, uncategorised cancers comprise the highest (42%) proportion of cancer types with non-Hodgkin’s lymphoma (NHL) being second, likely accounted for by endemic Burkitt’s lymphoma (included as a NHL in the GBD classification) in equatorial Africa (16).
This high proportion of uncategorised cancers does represent a missed opportunity for estimates of potentially actionable burdens of disease given that an accurate pathology diagnosis is central to subsequent treatments and overall outcomes. GBD data is more biased toward the classification of adult type cancers, namely epithelial carcinomas, and the authors do rightly raise the point that the International Classification of Childhood Cancer should be prioritised in future GBD iterations (17). Also worth highlighting is that the data reported here does not include benign CNS tumours (as these are not differentiated from all benign tumours in the GBD data), and so excludes low grade gliomas which are important contributors to childhood cancer morbidity, if not mortality, and are one of the key cancers for action in the WHO Global Initiative for Childhood Cancer.
In terms of other childhood diseases, globally childhood cancer ranks 9th as measured by DALYs in terms of disease burden. Of note, it was highest in the high-middle and middle SDI ranks reflecting their transitioning from low SDI status where the burden of disease arising from infection and dietary deficiency is higher.
Digging deeper into the data, the authors also found that age standardised incidence was not equivalent across SDI groupings as might be expected given the lack of environmental risk factors for the majority of childhood cancers and that high risk genetic predisposition ought be constant across different populations. Rather, they found a lower incidence in lower SDI regions and surmise this likely reflects limitations in access to healthcare and diagnostic capacity in resource limited settings (18).
Even with these somewhat stark figures, the authors comment that it is likely that overall DALYs are under-represented in this dataset. This is primarily from the under-estimation of YLDs, particularly in LMICs, where there is less data. However, even considering the HICs too, the YLD and YLL data does not accurately reflect the well documented lifelong increase in morbidity and early death in childhood cancer survivors as the disability modelling used is limited to a 10 years post cancer diagnosis window (19-21).
Although absolute numbers are relatively small and childhood cancer is considered rare, the unquestionable message from this data is that childhood cancer does account for a substantial global DALY burden, even when considered in the context of adult cancers and other childhood diseases. Furthermore, it is those countries with least resources that are disproportionately affected as measured by DALYs. Yet, even if one considers the HICs, where an overall 80% five-year survival rate is not unreasonable, such figures do not reveal the intra-country variation on outcomes. Thus a recent study from the USA found a high adjusted Hazard Ratio of death for childhood cancers amenable to medical intervention in both non-Hispanic Black (aHR =1.59, P=0.002) and Hispanic children (aHR =1.62, P<0.01) as compared with white children (22). As for possible reasons, the authors note as well as factors such as clinical trial enrolment and disease biology characteristics, it is likely that socioeconomic status also influences the association between race/ethnicity and cancer survival in this age group. Yet, even within a socialised health care system with free access to all at the point of need it is likely that socio-economic disparities will influence childhood cancer outcomes. The recent Marmot report looking at health inequality in England has shown an increase in child poverty since 2010/2011 with a fall in life expectancy in women in the country’s 10 most deprived areas (23). It remains to be seen whether these trends, if not reversed, are likely to have an impact on childhood cancer survival but sadly the data from GBD and the USA would suggest it will. For a societal group with a whole lifetime ahead of them, from whatever nation or socio-economic background, access to early diagnosis and treatment without the risk of therapy abandonment, unfortunately common in LICs, is critical in reducing the disease burden arising from childhood cancer (24).
We thank Kidscan (Charity #1094946) for research support.
Funding: DGE and ERW are supported by the all Manchester NIHR Biomedical Research Centre (IS-BRC-1215-20007).
Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/cco.2020.04.03). ERW has nothing to disclose; DGE reports personal fees from Astrazeneca, outside the submitted work.
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.
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/.
- Cancer statistics for the Nordic countries. Available online: http://www-dep.iarc.fr/NORDCAN/english/frame.asp
- National Cancer Registration and Analysis Service (NCRAS). Available online: https://www.gov.uk/guidance/national-cancer-registration-and-analysis-service-ncras.
- National Cancer Institute. Surveillance, Epidemiology and End Results Program. Available online: https://seer.cancer.gov/statistics/
- Homedes N. The disability-adjusted life year (DALY) definition, measurement and potential use. World Bank; 1996.
- Chen A, Jacobsen KH, Deshmukh AA, et al. The evolution of the disability-adjusted life year (DALY). Socio Econ Plan Sci 2015;49:10-5. [Crossref]
- Gatta G, Botta L, Rossi S, et al. Childhood cancer survival in Europe 1999–2007: results of EUROCARE-5—a population-based study. Lancet Oncol 2014;15:35-47. [Crossref] [PubMed]
- Noone AM, Howlader N, Krapcho M, et al. SEER Cancer Statistics Review, 1975–2015, National Cancer Institute. April, 2018. Available online: https://seer.cancer.gov/csr/1975_2015/
- The Global Burden of Disease. Available online: http://www.healthdata.org/gbd/about.
- The Lancet. Global Burden of Disease. Available online: https://www.thelancet.com/gbd
- Global Burden of Disease publications. Available online: http://www.healthdata.org/gbd/publications.
- World Health Organisation Cancer in Children. Available online: https://www.who.int/news-room/fact-sheets/detail/cancer-in-children.
- GBD 2017 Childhood Cancer Collaborators. The global burden of childhood and adolescent cancer in 2017: an analysis of the Global Burden of Disease Study 2017. Lancet Oncol 2019;20:1211-25. [PubMed]
- Rodriguez-Galindo C, Friedrich P, Alcasabas P, et al. Toward the cure of all children with cancer through collaborative efforts: pediatric oncology as a global challenge. J Clin Oncol 2015;33:3065. [Crossref] [PubMed]
- The World Bank. Countries and Economies. Available online: https://data.worldbank.org/country/
- Cancer Research UK. Cancer Incidence by Age. Available online: https://www.cancerresearchuk.org/health-professional/cancer-statistics/incidence/age#heading-Zero
- Hämmerl L, Colombet M, Rochford R, et al. The burden of Burkitt lymphoma in Africa. Infect Agent Cancer 2019;14:17. [Crossref] [PubMed]
- Steliarova-Foucher E, Stiller C, Lacour B, et al. International classification of childhood cancer. Cancer 2005;103:1457-67. [Crossref] [PubMed]
- Ward ZJ, Yeh JM, Bhakta N, et al. Estimating the total incidence of global childhood cancer: a simulation-based analysis. Lancet Oncol 2019;20:483-93. [Crossref] [PubMed]
- Robison LL, Hudson MM. Survivors of childhood and adolescent cancer: life-long risks and responsibilities. Nat Rev Cancer 2014;14:61-70. [Crossref] [PubMed]
- Bhakta N, Force LM, Allemani C, et al. Childhood cancer burden: a review of global estimates. Lancet Oncol 2019;20:e42-53. [Crossref] [PubMed]
- Armstrong GT, Chen Y, Yasui Y, et al. Reduction in late mortality among 5-year survivors of childhood cancer. New Engl J Med 2016;374:833-42. [Crossref] [PubMed]
- Delavar A, Barnes JM, Wang X, et al. Associations Between Race/Ethnicity and US Childhood and Adolescent Cancer Survival by Treatment Amenability. JAMA Pediatr 2020. [Epub ahead of print]. [Crossref] [PubMed]
- Institute of Health Equity. Marmot Review 10 Years On. Available online: http://www.instituteofhealthequity.org/resources-reports/marmot-review-10-years-on/
- Friedrich P, Lam CG, Itriago E, et al. Magnitude of treatment abandonment in childhood cancer. PloS One 2015;10:e0135230. [Crossref] [PubMed]