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Record W4248250894 · doi:10.21203/rs.3.rs-312244/v1

Examining the Etiology of Early-Onset Breast Cancer in the Canadian Partnership for Tomorrow’s Health (CanPath)

2021· preprint· en· W4248250894 on OpenAlexafffundabout
Joy Pader, Robert B. Basmadjian, Dylan E. O’Sullivan, Nicole E. Mealey, Yibing Ruan, Christine M. Friedenreich, Rachel A. Murphy, Edwin Wang, May Lynn Quan, Darren R. Brenner

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of CalgaryUniversity of British ColumbiaAlberta Health Services
FundersHealth CanadaAlberta Health ServicesCancer Care OntarioCanadian Institutes of Health ResearchAlberta Cancer FoundationCumming School of Medicine, University of CalgaryUniversity of CalgaryPartenariat Canadien Contre Le Cancer
KeywordsEtiologyGeneral partnershipBreast cancerPolitical scienceMedicineGynecologyCancerInternal medicineLaw

Abstract

fetched live from OpenAlex

Abstract Purpose: Breast cancer incidence among younger women (under age 50) has increased over the past 25 years, yet little is known about the etiology among this age group. The objective of this study was to investigate relationships between modifiable and non-modifiable risk factors and early-onset breast cancer among three prospective Canadian cohorts. Methods: A matched case-control study was conducted using data from Alberta’s Tomorrow Project, BC Generations Project, and the Ontario Health Study. Participants diagnosed with breast cancer before age 50 were identified through provincial registries and matched to three control participants of similar age and follow-up. Conditional logistic regression was used to examine the association between factors and risk of early-onset breast cancer. Results: In total, 609 cases and 1,827 controls were included. A body mass index ≥30kg/m 2 was associated with a lower risk of early-onset breast cancer (OR=0.65; 95% CI: 0.47-0.90), while a waist circumference ≥88 cm was associated with an increased risk (OR=1.40; 95% CI: 1.06-1.84). A reduced risk was found for women with ≥2 pregnancies (OR=0.80; 95% CI: 0.64-1.00) and a first-degree family history of breast cancer was associated with an increased risk (OR=2.06; 95% CI: 1.54-2.75). Conclusions: In this study, measures of adiposity, pregnancy history, and familial history of breast cancer are important risk factors for early-onset breast cancer. Evidence was insufficient to conclude if smoking, alcohol intake, fruit and vegetable consumption, and physical activity are meaningful risk factors. The results of this study could inform targeted primary and secondary prevention for early-onset breast cancer.

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.

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)0.004
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 score0.077
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.258
GPT teacher head0.487
Teacher spread0.229 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

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