Risk of subsequent primary cancers among adult cancer survivors in Alberta
Bibliographic record
Abstract
Abstract Background Improvements in cancer control have led to a drastic increase in cancer survivors who may be at an elevated risk of developing a subsequent primary cancer (SPC). In this study, we assessed the risk and patterns of SPC development among 134,693 adult cancer survivors in Alberta, Canada. Methods We used data from the Alberta Cancer Registry to identify all first primary cancers (FPC) occurring between 2004 and 2015. A SPC was considered as the next primary cancer occurring in a different site. We estimated standardized incidence ratios (SIR) for SPC development as the observed number of SPC (O) divided by the expected number of SPC (E), where E is a weighted-sum of the population-based year-age-sex-specific incidence rates and the corresponding person-years of follow-up. Results The risk of developing a SPC up to fifteen years after an initial cancer was 16.1% for males and 12.3% for females, though these estimates vary considerably by cancer site. Survivors of initial head and neck cancers had a 21.3% fifteen-year cumulative incidence and a 2.5-fold relative risk of SPC development. Overall, both males (SIR=1.50) and females (SIR=1.64) had an increased risk of a SPC. There were significant increases in SPC risk for nearly all age groups, with a greater than 5-fold increase for survivors of cancers diagnosed between ages 18-39. Conclusions Cancer survivors of nearly every FPC site had substantially increased risk of a SPC, compared to the cancer risk in the general population. Screen-detectable cancers (breast, cervical, colorectal, lung) were common SPC sites and highlights the need to investigate optimal strategies for screening the growing population of cancer survivors.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".