Reduction in late mortality among 5-year survivors of childhood cancer: A report from the Childhood Cancer Survivor Study (CCSS).
Bibliographic record
Abstract
LBA2 Background: Over the past four decades, treatment of many childhood cancers has been modified with the aim of achieving high survival rates while reducing the risk of life-threatening late-effects, and promoting risk-based follow-up care of survivors. Methods: Late mortality was evaluated in 34,033 5-year survivors (diagnosed < 21 years of age from 1970-1999, median follow-up 21 years, range 5-38) using cumulative incidence and Poisson regression models adjusted for demographic and disease factors to calculate relative risk (RR) and 95% confidence intervals (CI). Mortality due to non-recurrence/non-external (NR/NE) causes, which includes deaths that reflect late-effects of cancer therapy, was evaluated. Results: 1,622 (41%) of the 3,958 deaths were attributable to NR/NE causes, including 751 subsequent neoplasm (SN), 243 cardiac, and 136 pulmonary deaths. Changes in therapy by decade included reduced rates of: cranial radiotherapy (RT) for acute lymphoblastic leukemia (ALL, 86%, 54%, 22%), RT for Wilms tumor (WT, 77%, 54%, 49%) and RT for Hodgkin lymphoma (HL, 96%, 88%, 77%). Reductions in 15 year cumulative NR/NE mortality were observed across treatment eras for ALL (p < .001), HL (p = .005), and WT (p = .005). Cardiac deaths decreased in ALL (p = .002), HL (p = .06), and WT (p = .04), and SN deaths decreased in WT (p < .001). Year of diagnosis (adjusted for age, sex, diagnosis, follow-up time) was significantly associated with a reduced risk of all-cause mortality (RR = 0.85, CI 0.83-0.87), NR/NE death (RR = 0.87, CI 0.84-0.91), death from SN (RR = 0.84, CI 0.80-0.89), cardiac death (RR = 0.78, CI 0.69-0.87) and pulmonary death (RR = 0.79, CI 0.68-0.91). Conclusions: The CCSS cohort provides evidence that the strategy of modifying therapy to reduce the occurrence of late-effects, and promotion of early detection, is successfully translating into a significant reduction in observed late mortality. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".