Stage at diagnosis and survival by stage for the leading childhood cancers in Rwanda
Bibliographic record
Abstract
BACKGROUND: The lack of accurate population-based information on childhood cancer stage and survival in low-income countries is a barrier to improving childhood cancer outcomes. METHODS: In this study, data from the Rwanda National Cancer Registry (RNCR) were examined for children aged 0-14 diagnosed in 2013-2017 for the eight most commonly occurring childhood cancers: acute lymphoblastic leukaemia, Hodgkin lymphoma (HL), Burkitt lymphoma (BL), non-Hodgkin lymphoma excluding BL, retinoblastoma, Wilms tumour, osteosarcoma and rhabdomyosarcoma. Utilising the Toronto Childhood Cancer Stage Guidelines Tier 1, the study assigned stage at diagnosis to all, except HL, and conducted active follow-ups to calculate 1-, 3- and 5-year observed and relative survival by cancer type and stage at diagnosis. RESULTS: The cohort comprised 412 children, of whom 49% (n = 202) died within 5 years of diagnosis. Five-year survival ranged from 28% (95% confidence interval [CI]: 12.5%-45.6%) for BL to 68% (CI: 55%-78%) for retinoblastoma. For the cancers for which staging was carried out, it was assigned for 83% patients (n = 301 of 362), with over half (58%) having limited or localised stage at diagnosis. Stage was a strong predictor of survival; for example, 3-year survival was 70% (95% CI: 45.1%-85.3%) and 11.8% (2.0%-31.2%) for limited and advanced non-HL, respectively (p < .001). CONCLUSION: This study is only the second to report on stage distribution and stage-specific survival for childhood cancers in sub-Saharan Africa. It demonstrates the feasibility of the Toronto Stage Guidelines in a low-resource setting, and highlights the value of population-based cancer registries in aiding our understanding of the poor outcomes experienced by this population.
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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 | 0.001 |
| 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".