Risk of Second Primary Cancer among Esophageal Cancer Patients: a Pooled Analysis of 13 Cancer Registries
Bibliographic record
Abstract
BACKGROUND: The objective of this study is to assess the risk of second primary cancers following a first primary esophageal cancer as well as the risk of esophageal cancer as a second primary, following first primary cancers of other sites. METHODS: The present investigation is a multicenter study of 13 population-based cancer registries in Europe, Australia, Canada, and Singapore. To assess excess occurrence of second cancers after esophageal cancers, we calculated standardized incidence ratios (SIR) by dividing the observed numbers of second cancers by the expected number of cancers calculated from the accumulated person-years and the age-, sex-, calendar period-, and registry-specific first primary cancer incidence rates. RESULTS: During the study period, 959 cases of second primary cancers occurred after an initial esophageal cancer, resulting in a SIR of 1.15 (95% confidence interval, 1.08-1.22). Second primary stomach cancers were associated with first primary esophageal adenocarcinomas (SIR, 2.13; 95% confidence interval, 1.26-3.37) and second primary cancers of the oral cavity and pharynx (6.68; 5.33-8.26), stomach (1.53; 1.14-2.01), larynx (3.24; 1.88-5.18), lung (1.55; 1.28-1.87), kidney (1.88; 1.18-2.85), and thyroid (2.92; 1.18-6.02) were associated with first primary squamous cell carcinomas of the esophagus. An excess of esophageal cancer as a second primary were observed following first primary cancers of the aerodigestive tract, female breast, cervix, testis, bladder, Hodgkin's lymphoma, and non-Hodgkin lymphoma. CONCLUSION: We observed associations of esophageal cancer with second primary head and neck cancers and lung cancer regardless of years of follow-up, which may suggest that common risk factors play a role in multiple tumor development.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".