Risk of digestive cancers in a cohort of 69 460 five-year survivors of childhood cancer in Europe: the PanCareSurFup study
Bibliographic record
Abstract
BACKGROUND: Survivors of childhood cancer are at risk of subsequent primary neoplasms (SPNs), but the risk of developing specific digestive SPNs beyond age 40 years remains uncertain. We investigated risks of specific digestive SPNs within the largest available cohort worldwide. METHODS: The PanCareSurFup cohort includes 69 460 five-year survivors of childhood cancer from 12 countries in Europe. Risks of digestive SPNs were quantified using standardised incidence ratios (SIRs), absolute excess risks and cumulative incidence. RESULTS: 427 digestive SPNs (214 colorectal, 62 liver, 48 stomach, 44 pancreas, 59 other) were diagnosed in 413 survivors. Wilms tumour (WT) and Hodgkin lymphoma (HL) survivors were at greatest risk (SIR 12.1; 95% CI 9.6 to 15.1; SIR 7.3; 95% CI 5.9 to 9.0, respectively). The cumulative incidence increased the most steeply with increasing age for WT survivors, reaching 7.4% by age 55% and 9.6% by age 60 years (1.0% expected based on general population rates). Regarding colorectal SPNs, WT and HL survivors were at greatest risk; both seven times that expected. By age 55 years, 2.3% of both WT (95% CI 1.4 to 3.9) and HL (95% CI 1.6 to 3.2) survivors had developed a colorectal SPN-comparable to the risk among members of the general population with at least two first-degree relatives affected. CONCLUSIONS: Colonoscopy surveillance before age 55 is recommended in many European countries for individuals with a family history of colorectal cancer, but not for WT and HL survivors despite a comparable risk profile. Clinically, serious consideration should be given to the implementation of colonoscopy surveillance while further evaluation of its benefits, harms and cost-effectiveness in WT and HL survivors is undertaken.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".