The cost effectiveness of treating Burkitt lymphoma in Uganda
Bibliographic record
Abstract
BACKGROUND: Perceptions of high cost and resource intensity remain political barriers to the prioritization of childhood cancer treatment programs in many low- and middle-income countries (LMICs). Little knowledge exists of the actual cost and cost-effectiveness of such programs. To improve outcomes for children with Burkitt lymphoma (BL), the most common childhood cancer in Africa, the Uganda Cancer Institute implemented a comprehensive BL treatment program in 2012. We undertook an economic evaluation of the program to ascertain the cost-effectiveness of BL therapy in a specific LIC setting. METHODS: We compared the treatment of BL to usual care in a cohort of 122 patients treated between 2012 and 2014. Costs included variable, fixed, and family costs. Our primary measure of effectiveness was overall survival (OS). Patient outcomes were determined through prospective capture and retrospective chart abstraction. The cost per disability-adjusted life-year (DALY) averted was calculated using the World Health Organization's Choosing Interventions That Are Cost-Effective (WHO-CHOICE) methodology. RESULTS: The 2-year OS with treatment was 55% (95% CI, 45% to 64%). The cost per DALY averted in the treatment group was US$97 (Int$301). Cumulative estimate of national DALYs averted through treatment was 8607 years, and the total national annual cost of treatment was US$834,879 (Int$2,590,845). The cost of BL treatment fell well within WHO-CHOICE cost-effectiveness thresholds. The ratio of cost per DALY averted to per capita gross domestic product was 0.14, reflecting a very cost-effective intervention. CONCLUSION: This study demonstrates that treating BL with locally tailored protocols is very cost-effective by international standards. Studies of this kind will furnish crucial evidence to help policymakers prioritize the allocation of LMIC health system resources among noncommunicable diseases, including childhood cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".