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Cancer ; 130(7): 1112-1124, 2024 04 01.
Artigo em Inglês | MEDLINE | ID: mdl-38100617

RESUMO

BACKGROUND: National cancer control plans (NCCPs) are complex public health programs that incorporate evidence-based cancer control strategies to improve health outcomes for all individuals in a country. Given the scope of NCCPs, small and vulnerable populations, such as patients with childhood cancer, are often missed. To support planning efforts, a rapid, modifiable tool was developed that estimates a context-specific national budget to fund pediatric cancer programs, provides 5-year scale-up scenarios, and calculates annual cost-effectiveness. METHODS: The tool was codeveloped by teams of policymakers, clinicians, and public health advocates in Zimbabwe, Zambia, and Uganda. The 11 costing categories included real-world data, modeled data, and data from the literature. A base-case and three 5-year scale-up scenarios were created using modifiable inputs. The cost-effectiveness of the disability-adjusted life years averted was calculated. Results were compared with each country's projected gross domestic product per capita for 2022 through 2026. RESULTS: The number of patients/total budget for year 1 was 250/$1,109,366 for Zimbabwe, 280/$1,207,555 for Zambia, and 1000/$2,277,397 for Uganda. In year 5, these values were assumed to increase to 398/$5,545,445, 446/$4,926,150, and 1594/$9,059,331, respectively. Base-case cost per disability-adjusted life year averted/ratio to gross domestic product per capita for year 1, assuming 20% survival, was: $807/0.5 for Zimbabwe, $785/0.7 for Zambia, and $420/0.5 for Uganda. CONCLUSIONS: This costing tool provided a framework to forecast a budget for childhood-specific cancer services. By leveraging minimal primary data collection with existing secondary data, local teams obtained rapid results, ensuring that childhood cancer budgeting is not neglected once in every 5 to 6 years of planning processes.


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Neoplasias , Humanos , Criança , Neoplasias/terapia , Países em Desenvolvimento , Populações Vulneráveis , Análise Custo-Benefício , Custos de Cuidados de Saúde
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