Increased risk of cardiac ischaemia in a pan-European cohort of 36 205 childhood cancer survivors: a PanCareSurFup study
Bibliographic record
Abstract
OBJECTIVE: In this report, we determine the cumulative incidence of symptomatic cardiac ischaemia and its risk factors among European 5-year childhood cancer survivors (CCS) participating in the PanCareSurFup study. METHODS: Eight data providers (France, Hungary, Italy (two cohorts), the Netherlands, Slovenia, Switzerland and the UK) participating in PanCareSurFup ascertained and validated symptomatic cardiac events among their 36 205 eligible CCS. Data on symptomatic cardiac ischaemia were graded according to the Criteria for Adverse Events V.3.0 (grade 3-5). We calculated cumulative incidences, both overall and for different subgroups based on treatment and malignancy, and used multivariable Cox regression to analyse risk factors. RESULTS: Overall, 302 out of the 36 205 CCS developed symptomatic cardiac ischaemia during follow-up (median follow-up time after primary cancer diagnosis: 23.0 years). The cumulative incidence by age 60 was 5.4% (95% CI 4.6% to 6.2%). Men (7.1% (95% CI 5.8 to 8.4)) had higher rates than women (3.4% (95% CI 2.4 to 4.4)) (p<0.0001). Of importance is that a significant number of patients (41/302) were affected as teens or young adults (14-30 years). Treatment with radiotherapy/chemotherapy conferred twofold risk (95% CI 1.5 to 3.0) and cases in these patients appeared earlier than in CCS without treatment/surgery only (15% vs 3% prior to age 30 years, respectively (p=0.04)). CONCLUSIONS: In this very large European childhood cancer cohort, we found that by age 60 years, 1 in 18 CCS will develop a severe, life-threatening or fatal cardiac ischaemia, especially in lymphoma survivors and CCS treated with radiotherapy and chemotherapy increases the risk significantly.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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".