Late mortality among 5‐year survivors of childhood cancer: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Childhood cancer survivors are at increased risk of late mortality (death ≥5 years after diagnosis) from cancer recurrence and treatment-related late effects. The authors conducted a systematic review and meta-analysis to provide comprehensive estimates of late mortality risk among survivors internationally and to investigate differences in risk across world regions. METHODS: Health sciences databases were searched for cohort studies comprised of 5-year childhood cancer survivors in which the risk of mortality was evaluated across multiple cancer types. Eligible studies assessed all-cause mortality risk in survivors relative to the general population using the standardized mortality ratio (SMR). The absolute excess risk (AER) was assessed as a secondary measure to examine excess deaths. Cause-specific mortality risk was also assessed, if reported. SMRs from nonoverlapping cohorts were combined in subgroup meta-analysis, and the effect of world region was tested in univariate meta-regression. RESULTS: Nineteen studies were included, and cohort sizes ranged from 314 to 77,423 survivors. Throughout survivorship, SMRs for all-cause mortality generally declined, whereas AERs increased after 15-20 years from diagnosis in several cohorts. All-cause SMRs were significantly lower overall in North American studies than in European studies (relative SMR, 0.63; 95% confidence interval, 0.49-0.80). SMRs for subsequent malignant neoplasms and for cardiovascular, respiratory, and external causes did not vary significantly between world regions. CONCLUSIONS: The current findings suggest that late mortality risk may differ significantly between world regions, but these conclusions are based on a limited number of studies with considerable heterogeneity. Reasons for regional differences remain unclear but may be better elucidated through future analyses of individual-level data.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.038 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".