Risk of a second malignant neoplasm among 5‐year survivors of cancer in childhood and adolescence in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: We examined second malignancies, a recognized late effect of therapy among survivors of childhood and adolescent cancer, among a recent, population-based cohort of 2,322 5-year survivors diagnosed before 20 years of age in British Columbia (BC), Canada between 1970 and 1995. PROCEDURE: Survivors and second malignancies were identified from the BC Cancer Registry. Risk of second malignancy was evaluated using standardized incidence ratios (SIRs), absolute excess risk (AER), and cumulative risk. The effect of demographic, temporal, and disease-related characteristics on risk was assessed. RESULTS: Fifty-five second malignancies were observed after 26,071 person-years of follow-up. Relative rate of developing a second malignancy among survivors was 5 times higher than expected (SIR = 5.0, 95% CI, 3.8-6.5), and absolute excess risk was 1.7 deaths per 1,000 person-years. Cumulative incidence of a second malignancy was 5.1% at 25 years after diagnosis of the first cancer. SIRs and absolute excess risk of subsequent cancer was higher among females (SIR = 5.9, 95% CI, 4.5-8.3 and AER = 2.66). While relative risk of second cancer was higher for those diagnosed before 10 years of age (SIR = 10.6, 95% CI, 7.1-16.0), absolute excess risk was slightly higher for those diagnosed after 10 years of age. SIRs were significantly elevated for all follow-up periods, but absolute excess risk of a second cancer was highest among patients surviving more than 15 years. CONCLUSIONS: Increased risk of a subsequent neoplasm is evident among childhood cancer survivors diagnosed in more recent periods than has been previously reported, continues years after diagnosis, and varies according to several risk factors. Continued surveillance is essential to quantify and characterize long-term and changing risks for appropriate follow-up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".