The cost effectiveness of treating paediatric cancer in low-income and middle-income countries: a case-study approach using acute lymphocytic leukaemia in Brazil and Burkitt lymphoma in Malawi
Bibliographic record
Abstract
Approximately 90% of children with cancer reside in low-income and middle-income countries (LMIC) where healthcare resources are scarce and allocation decisions difficult. The cost effectiveness of treating childhood cancers in these settings is unknown. The objective of the present work was to determine cost-effectiveness thresholds for common paediatric cancers using acute lymphoblastic leukaemia (ALL) in Brazil and Burkitt lymphoma (BL) in Malawi as examples. Disability-adjusted life years (DALYs) prevented by treatment were compared to the gross domestic product (GDP) per capita of each country to define cost-effectiveness thresholds using WHO-CHOICE ('CHOosing Interventions that are Cost-Effective') guidelines. The case examples were selected due to the data available and because ALL and BL both have the potential to yield significant health gains at a low cost per patient treated. The key findings were as follows: the 3:1 cost/DALY prevented to GDP/capita ratio for ALL in Brazil was US $771,225; expenditures below this threshold were cost effective. Costs below US $257,075 (1:1 ratio) were considered very cost effective. Analogous thresholds for BL in Malawi were US $42,729 and US $14,243. Actual costs were far less. In Brazil, US $16,700 was spent to treat each patient while in Malawi total drug costs were less than US $50 per child. In summary, treatment of certain paediatric cancers in LMIC is very cost effective. Future research should evaluate actual treatment and infrastructure expenditures to help guide policymakers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".