Childhood cancer survival in France, 2000–2008
Bibliographic record
Abstract
This paper reports the latest survival data for French childhood cancer patients at the national level. Data from the two French National Registries of Childhood Cancer (Haematopoietic Malignancies and Solid Tumours) were used to describe survival outcomes for 15,479 children diagnosed with cancer between 2000 and 2008 in mainland France. The overall survival was 91.7% at 1 year, 86.9% at 2 years and 81.6% at 5 years. Relative survival did not differ from overall survival even for infants. Survival was lower among infants for lymphoblastic leukaemia and astrocytoma, but higher for neuroblastoma. For all cancers considered together, 5-year survival increased from 79.5% in the first (2000-2002) diagnostic period to 83.2% in the last (2006-2008) period. The improvement was significant for leukaemia, both myeloid and lymphoid, central nervous system tumours (ependymoma) and neuroblastoma. The results remained valid in the multivariate analysis, and, for all cancers combined, the risk of death decreased by 20% between 2000-2002 and 2006-2008. The figures are consistent with various international estimates and are the result of progress in treatment regimens and collaborative clinical trials. The challenge for the French registries is now to study the long-term follow-up of survivors to estimate the incidence of long-term morbidities and adverse effects of treatments.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".