Burden of Cancer Mortality in the Canadian Armed Forces, 1976–2012: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Military personnel may have potential exposures to carcinogens during their military careers. However, the generalizability of causal evidence between occupational exposures and cancer outcomes in military personnel is limited. This study aims to describe the epidemiology cause-specific cancer mortality in still serving and released Canadian Armed Forces (CAF) personnel recruited between 1976 and 2012. METHODS: Data came from the Canadian Forces Cancer and Mortality Study II (CF CAMS II), a record-linkage study of approximately 228,685 CAF Regular Force personnel and Reservists. Sex-stratified standardized mortality ratios (SMR) were calculated for each neoplasm subcategory, with the Canadian general population (CGP) as the reference. RESULTS: Approximately 1,450 deaths were attributable to neoplasms. Cancer mortality was lower in both men and women with military service (SMR = 0.77 and 0.78, respectively) versus CGP. Females had a significantly lower risk of breast cancer. Males in the cohort had a significantly lower risk of lip, oral cavity and pharynx, digestive organs, respiratory and intrathoracic organs, bone and articular cartilage, and mesothelial and soft-tissue cancers. However, males also had a significantly increased risk for neoplasms of the central nervous system and lymphoid cells, as well as for certain specific cancer diagnoses. CONCLUSIONS: Current and former CAF personnel were at comparable, or lower risk than, the CGP for cancer-related deaths. However, there was an increased risk for certain neoplasm subcategories and specific cancers. IMPACT: These findings contribute to the limited body of evidence investigating the link between military service and cancer mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".