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Abstract B014: Early-onset breast cancer and reproductive timing: results from the Mexican Teachers’ Cohort

2025· article· en· W7113895490 on OpenAlexaffabout

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsBreast cancerHazard ratioProportional hazards modelMenarcheIncidence (geometry)Prospective cohort studyCohortConfidence intervalCancer

Abstract

fetched live from OpenAlex

Abstract Background: The incidence of early-onset breast cancer (EOBC; diagnosed under the age of 50) is rising globally, with incidence and mortality rates in Latin America being twice as high as those in high-income countries. The Mexican Teachers’ Cohort, the largest prospective cancer study in the region, is uniquely positioned to provide valuable insights into EOBC in Latin America. Methods: We followed 95,828 Mexican women younger than 50 (2006–2023; 824,053 person-years). Incident breast cancers were validated through population-based cancer and mortality registries, health utilization datasets (Positive predictive value, PPV, 97%), and self-reports. EOBC was defined as a diagnosis <50 years. For each reproductive factor (age at menarche, parity/number of births, age at first full-term pregnancy (FFTP), breastfeeding, and hormonal contraceptive (HC) use), we used multivariate Cox proportional hazards models with follow-up time as the time scale to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). Adjustment sets were selected a priori using directed acyclic graphs (DAGs). Results: Among 2,214 incident breast cancers, 618 were EOBC, <50 years old (28%): 47 occurred before 40, 160 between 40–44, and 411 between 45–49 years. In EOBC-focused models, later menarche was inversely associated with EOBC incidence (per-year HR, 0.93; 95% CI, 0.88–0.98; ≥15 vs. ≤11 years, HR, 0.72; 95% CI, 0.53–0.98). Having had a full-term birth showed no clear protective effect (HR, 0.97; 95% CI, 0.77–1.22). Among women who have given birth, higher parity was protective (3 vs. 1 birth: HR 0.67, 0.51–0.88; 4 or more vs. 1: HR 0.85, 0.62–1.18; per additional birth: HR 0.92, 0.84–1.01). Older age at first FFTP was linked to higher EOBC incidence compared to age 19 or younger (20–24 HR 1.24, 0.85–1.79; 25–29 HR 1.21, 0.83–1.76; 30–34 HR 1.53, 1.01–2.31; 35 or older HR 1.58, 0.89–2.82; per year HR 1.02, 1.00–1.04). Breastfeeding showed no strong protective effect, with some modest inverse estimates without a clear dose–response relationship (≥18 vs 0 months: HR 0.82, 0.59–1.14; per additional month: HR 0.99, 0.98–1.00). HC use was positively associated with EOBC (ever vs never, HR 1.22, 1.04–1.45); use of ≥5 years showed a similar trend (HR 1.25, 0.99–1.57). Oral HC users had a higher incidence of EOBC compared to non-users (HR 1.27, 1.04–1.55). Conclusions: In this cohort, one-third of breast cancer diagnoses occur before the age of 50. The timing of reproductive events—specifically, later onset of menarche (which appears to be protective), older age at FFTP, and higher parity (also protective)—was noted. At the same time, there is limited evidence supporting the protective role of breastfeeding and only modest positive associations identified with certain patterns of hormonal contraceptive use. These findings, derived from an underrepresented population, underscore the importance of incorporating reproductive timing into risk stratification and prevention strategies for EOBC in Mexico and throughout Latin America. Citation Format: Liliana Gomez-Flores-Ramos, Leticia Palma, Dalia Stern, Marion Brochier, Jocelyn Jaen, Adrian Cortes, Alberto Castellanos, Martin Lajous. Early-onset breast cancer and reproductive timing: results from the Mexican Teachers’ Cohort [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr B014.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.225
GPT teacher head0.532
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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