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Childhood cancer: Estimating regional and global incidence
W T Johnston1, Friederike Erdmann2, Robert Newton3
1Epidemiology and Cancer Statistics Group, Department of Health Sciences, University of York, York, United Kingdom.
Insights
Estimating childhood cancer incidence globally is challenging due to limited data. A new Baseline Model (BM) provides updated childhood cancer burden estimates, particularly in regions with weak health systems.
Area of Science:
- Global Health
- Epidemiology
- Pediatric Oncology
Background:
- Limited cancer surveillance and vital registration systems worldwide hinder accurate global cancer burden estimation.
- Childhood cancer quantification is particularly challenging due to rarity and non-specific symptoms mimicking common childhood illnesses.
- Accurate global childhood cancer incidence data is crucial for resource allocation and targeted interventions.
Purpose of the Study:
- To develop and apply a Baseline Model (BM) for estimating global and regional childhood cancer incidence in 2015.
- To compare BM estimates with existing global cancer burden models like GLOBOCAN, IICC-3, and GCC.
- To identify factors influencing discrepancies in childhood cancer estimates across different regions and Human Development Index (HDI) levels.
Main Methods:
- Constructed a Baseline Model (BM) using US SEER data for sex- and age-specific cancer rates (ICCC-3 diagnostic groups).
- Applied BM rates to global 2015 population data, incorporating risk factors for Burkitt lymphoma and Kaposi sarcoma.
- Compared BM results with GLOBOCAN 2018, IICC-3 extrapolations, and the GCC model.
Main Results:
- The BM estimated 360,114 childhood cancers globally in 2015, with 54% in Asia and 28% in Africa.
- Estimated standardized rates varied by region, with higher rates in Africa compared to Europe and North America.
- Discrepancies between models were noted, particularly in countries with lower Human Development Index (HDI) and limited registration coverage.
Conclusions:
- Disagreements in childhood cancer estimates highlight challenges in regions with inadequate health systems for diagnosis and care.
- The BM's ability to incorporate etiological evidence allows for better estimation of specific cancer burdens, like Burkitt lymphoma and Kaposi sarcoma.
- Further refinement of the BM with additional etiological data can improve global childhood cancer burden assessments.
Background:
Most of the world's population is not covered by cancer surveillance systems or vital registration, and worldwide/UN-regional cancer incidence is estimated using a variety of methods. Quantifying the cancer burden in children (<15 years) is more challenging than in adults; childhood cancer is rare and often presents with non-specific symptoms that mimic those of more prevalent infectious and nutritional conditions.
Methods:
A Baseline Model (BM) was constructed comprising a set of quality assured sex- and age-specific cancer rates derived from the US Surveillance, Epidemiology and End Results (SEER) program, for diagnostic groups of the International Classification of Childhood Cancers (ICCC-3) 3rd edition, and information on a known risk factor for endemic Burkitt lymphoma and Kaposi's sarcoma. These rates were applied to global country-level population data for 2015 to estimate the global and regional incidence of childhood cancer. Results were compared to GLOBOCAN 2018, extrapolations from the International Incidence of Childhood Cancer (IICC-3) and estimates from the Global Childhood Cancer (GCC) model (based on IICC-3 data combined with information on health care systems and other parameters).
Results:
The BM estimated 360,114 total childhood cancers occurring worldwide in 2015; 54% in Asia and 28% in Africa. BM estimated standardised rates ranged from ∼178 cases per million in Europe and North America, through to ∼218 cases per million in West and Middle Africa. Totals from GLOBOCAN and extrapolations from the IICC-3 study were lower (44.6% and 34.7% respectively), but the estimate from the GCC model was 10.2% higher. In all models, agreement was good in countries with very high human development index (HDI), but more variable in countries with medium and low HDIs; the discrepancies correlating with registration coverage across these settings.
Conclusion:
Disagreements between the BM estimates and other sources occur in areas where health systems are insufficiently equipped to provide adequate access to diagnosis, treatment, and supportive care. Incorporating aetiological evidence into the BM enabled the estimation of the additional burden of Burkitt lymphoma and Kaposi sarcoma; similar adjustments could be applied to other cancers, as and when information becomes available.
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