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Abstract A126: Characteristics of menstruation and pregnancy and the risk of lung cancer in women

2008· article· en· W2065583023 on OpenAlexaffabout
Anita Koushik, Marie‐Élise Parent, Jack Siemiatycki

Bibliographic record

VenueCancer Prevention Research · 2008
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversité de MontréalInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
Fundersnot available
KeywordsMedicineLung cancerOdds ratioPopulationObstetricsGynecologyEpidemiologyPregnancyCancerConfidence intervalCancer registryMenopauseBreast cancerDemographyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Abstract A126 Differences between men and women in the descriptive epidemiology of lung cancer suggest that hormonal factors may influence lung carcinogenesis in women. Few epidemiological studies have been conducted on hormone-related variables and lung cancer risk and the findings have not been consistent. We investigated the association between characteristics of menstruation and pregnancy in relation to lung cancer risk in a population-based case-control study carried out in Montreal, Canada. Between January 1996 and December 1997, newly diagnosed lung cancer cases were identified and recruited from 18 Montreal-area hospitals that together diagnose 98% of cases that occur among Montreal residents. Population controls from Montreal were identified from the provincial electoral lists and were randomly selected, stratified to the expected age and sex distribution of cases. The participation rate was 81.7% among cases and 69.4% among controls. Among cases, interviews were conducted an average of 12.1 months after diagnosis. For each variable, odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional logistic regression modeling. Each hormone-related variable was modeled separately. Associations were also examined according to age at diagnosis and level of smoking and by lung cancer histology. All statistical tests were two-sided. Among 422 women with lung cancer and 577 controls, we observed that most characteristics of menstruation and pregnancy were not associated with the risk of lung cancer. However, an increased lung cancer risk was observed for women who had had surgical menopause with bilateral oophorectomy compared to women who had had a natural menopause (OR=1.95, 95% CI: 1.29-3.17). These results did not vary by age at diagnosis or level of smoking, and they were similar for different histological types. Our results suggest that hormonal factors, related to surgical menopause and/or ovary removal, may play a role in the risk of lung cancer. Further studies are needed to confirm these findings, and to assess the possible contribution of hormone replacement therapy. Citation Information: Cancer Prev Res 2008;1(7 Suppl):A126.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.408
Teacher spread0.353 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes2
Has abstractyes

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