Health-Related and Behavioral Factors Associated With Lung Cancer Stage at Diagnosis: Observations From Alberta’s Tomorrow Project
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it