Prevalence of factors influencing cancer risk in women with lupus: social habits, reproductive issues, and obesity.
Bibliographic record
Abstract
OBJECTIVE: There is mounting evidence that hematological malignancies are increased in systemic lupus erythematosus (SLE), and the risk of certain solid tumors may also be increased. The pathogenesis may be different for the 2 processes: risk of hematological malignancies in SLE may be due to chronic lymphocyte stimulation, while risk of solid tumors may be influenced by factors such as obesity and reproductive habits. We aimed to determine prevalence in a lupus cohort of selected factors that influence the risk of cancer, and to compare this prevalence to that of the general population. METHODS: Subjects were women followed in the Montreal General Hospital Lupus Clinic. We administered a postal survey of factors known to be associated with lung and aerodigestive cancers (smoking, alcohol use) as well as factors associated with breast and gynecologic cancers (nulliparity, use of oral contraceptives, and hormone replacement therapy). For patients who had died or been lost to followup, data were abstracted from clinic records. Information about nonsteroidal antiinflammatory drug (NSAID) use (a potentially protective factor for colorectal cancer) was also collected. Obesity prevalence was established from the clinic database. Comparison figures were obtained from the 1996-1997 National Population Health Survey data for Quebec women and age adjusted, where possible. RESULTS: Compared to the general population, the lupus population had lower prevalence of current use of oral contraceptives, and greater prevalence of obesity and nulliparity. The average number of pack-years among smokers was also greater in the lupus cohort. CONCLUSION: Solid cancer incidence in SLE may be influenced by established cancer risk factors such as smoking, obesity, and reproductive history.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".