Health-Related and Behavioral Factors Associated With Lung Cancer Stage at Diagnosis: Observations From Alberta’s Tomorrow Project
Bibliographic record
Abstract
BACKGROUND: Lung cancer is the leading cause of cancer death in Canada, with stage at diagnosis among the top predictors of lung cancer survival. Identifying factors associated with stage at diagnosis can help reduce lung cancer morbidity and mortality. This study used data from a prospective cohort study of adults living in Alberta, Canada to examine factors associated with lung cancer stage at diagnosis. METHODS: This cohort study used data from adults aged 35-69 years enrolled in Alberta's Tomorrow Project. Partial Proportional Odds models were used to examine associations between sociodemographic characteristics and health-related factors and subsequent lung cancer stage at diagnosis. RESULTS: A total of 221 participants (88 males and 133 females) developed lung cancer over the study period. Nearly half (48.0%) of lung cancers were diagnosed at a late stage (stage IV), whereas 30.8 % and 21.3% were diagnosed at stage I/II and III, respectively. History of sunburn in the past year was protective against late-stage lung cancer diagnosis (odds ratio (OR) .40, P=.005). In males, a higher number of lifetime prostate specific antigen tests was associated with reduced odds of late-stage lung cancer diagnosis (odds ratio .66, P=.02). Total recreational physical activity was associated with increased odds of late-stage lung cancer diagnosis (OR 1.08, P=.01). DISCUSSION: Lung cancer stage at diagnosis remains a crucial determinant of prognosis. This study identified important factors associated with lung cancer stage at diagnosis. Study findings can inform targeted cancer prevention initiatives towards improving early detection of lung cancer and lung cancer survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".