Pediatric cancer care in Africa: SIOP Global Mapping Program report on economic and population indicators
Bibliographic record
Abstract
INTRODUCTION: Inalignment with the World Health Organization (WHO) Global Initiative for Childhood Cancer (GICC), the International Society of Pediatric Oncology initiated a program to map global pediatric oncology services. As survival rates in Africa are low and data are scant, this continent was mapped first to identify areas with greatest need. METHODS: Beginning November 2018, an electronic survey was sent to all known stakeholders, followed by email communications and internet searches to verify data. Availability of pediatric oncologists, chemotherapy, surgical expertise, and radiotherapy was correlated with geographic region, World Bank income status, Universal Health Coverage, population < 15 and < 24 years, percentage of gross domestic product spent on healthcare, and Human Development Index (HDI). RESULTS: Responses were received from 48/54 African countries. All three treatment modalities were reportedly available in 9/48 countries, whereas seven countries reported no pediatric oncology services. Negative correlations were detected between provision of all three services and geographic region (P = 0.01), younger median population age (P = 0.002), low-income country status (P = 0.045), and lower HDI (P < 0.001). CONCLUSION: This study provides a comprehensive overview of pediatric oncology care in Africa, emphasizing marked disparities between countries: some have highly specialized services, whereas others have no services. A long-term strategy to eliminate disparities in African pediatric cancer care should be aligned with the WHO GICC aims and facilitated by SIOP Africa. MEETING ABSTRACTS: SIOP maps pediatric oncology services in Africa to address inequalities in childhood cancer services. Geel J, Ranasinghe N, Davidson A, Challinor J, Howard S, Wollaert S, Myezo K, Renner L, Hessissen L, Bouffet E. 51st Annual Congress of the International Society of Paediatric Oncology (SIOP), Lyon, France, October 2019. Pediatric Blood and Cancer Vol 66 S219-S219. Pediatric cancer care in Africa: SIOP Global Mapping Program report on economic and population indicators.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".