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Record W1972606816 · doi:10.1002/ijc.21273

Effect of pregnancy as a risk factor for breast cancer in <i>BRCA1</i>/<i>BRCA2</i> mutation carriers

2005· article· en· W1972606816 on OpenAlexaff
Carey A. Cullinane, Jan Lubiński, Susan L. Neuhausen, Parviz Ghadirian, Henry T. Lynch, Claudine Isaacs, Barbara Weber, Pål Møller, Kenneth Offit, Charmaine Kim‐Sing, Eitan Friedman, Susan Randall, Barbara Pasini, Peter Ainsworth, Ruth Gershoni‐Baruch, William D. Foulkes, Jan G.M. Klijn, Nadine Tung, Gad Rennert, Olufunmilayo I. Olopade, Fergus J. Couch, Teresa Wagner, Håkan Olsson, Ping Sun, Jeffrey N. Weitzel, Steven A. Narod

Bibliographic record

VenueInternational Journal of Cancer · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsLondon Health Sciences CentreWestern UniversityUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer CentreBC Cancer AgencyUniversité de MontréalHôtel-Dieu de MontréalUniversity of British ColumbiaCoalition for Research in Women's HealthMcGill UniversityCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineBreast cancerOdds ratioBRCA mutationGynecologyObstetricsRisk factorCase-control studyPopulationConfidence intervalCancerPregnancyParity (physics)OncologyInternal medicineGeneticsBiology

Abstract

fetched live from OpenAlex

Early age at first birth and multiparity have been associated with a decrease in the risk of breast cancer in women in the general population. We examined whether this relationship is also present in women at high risk of breast cancer due to the presence of a mutation in either of the 2 breast cancer susceptibility genes, BRCA1 or BRCA2. We performed a matched case-control study of 1,260 pairs of women with known BRCA1 or BRCA2 mutations, recruited from North America, Europe and Israel. Women who had been diagnosed with breast cancer were matched with unaffected control subjects for year of birth, country of residence, and mutation (BRCA1 or BRCA2). Study subjects completed a questionnaire detailing their reproductive histories. Odds ratios (ORs) and 95% confidence intervals (CIs) were derived by conditional logistic regression. Among BRCA1 carriers, parity per se was not associated with the risk of breast cancer (OR for parous vs. nulliparous = 0.94; 95% CI = 0.75-1.19; p = 0.62). However, women with a BRCA1 mutation and 4 or more children had a 38% decrease in breast cancer risk compared to nulliparous women (OR = 0.62; 95% CI = 0.41-0.94). In contrast, among BRCA2 carriers, increasing parity was associated with an increased risk of breast cancer; women with 2 or more children were at approximately 1.5 times the risk of breast cancer as nulliparous women (OR = 1.53; 95% CI = 1.01-2.32; p = 0.05). Among women with BRCA2 mutations and who were younger than age 50, the (adjusted) risk of breast cancer increased by 17% with each additional birth (OR = 1.17; 95% CI = 1.01-1.36; p = 0.03). There was no significant increase in the risk of breast cancer among BRCA2 carriers older than 50 (OR for each additional birth = 0.97; 95% CI = 0.58-1.53; p = 0.92). In the 2-year period following a birth, the risk of breast cancer in a BRCA2 carrier was increased by 70% compared to nulliparous controls (OR = 1.70; 95% CI = 0.97-3.0). There was a much smaller increase in breast cancer risk among BRCA2 carriers whose last birth was 5 or more years in the past (OR = 1.24; 95% CI = 0.79-1.95). A modest reduction in risk of breast cancer was observed among BRCA1 carriers with 4 or more births. Among BRCA2 carriers, increasing parity was associated with a significant increase in the risk of breast cancer before age 50 and this increase was greatest in the 2-year period following a pregnancy.

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)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.320
Teacher spread0.315 · 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".

Quick stats

Citations177
Published2005
Admission routes1
Has abstractyes

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