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Age‐specific incidence rates for breast cancer in carriers of BRCA1 mutations from Norway

2012· article· en· W2049501769 on OpenAlexaff
Pål Møller, Lovise Mæhle, Anita Vabø, Neal Clark, Peng Sun, SA Narod

Bibliographic record

VenueClinical Genetics · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsBreast cancerMedicineIncidence (geometry)PenetranceCohortDemographyCancerGynecologyInternal medicineObstetricsOncologyGeneticsBiology

Abstract

fetched live from OpenAlex

Incidence rates of breast cancer among women with a BRCA1 mutation vary according to their reproductive histories and country of residence. To measure cancer incidence, it is best to follow-up cohort of healthy women prospectively. We followed up a cohort of 675 women with a BRCA1 mutation who did not have breast or ovarian cancer before inclusion and who had a normal clinical examination and mammography at first visit. After a mean of 7.1 years, 98 incident cases of breast cancer were recorded in the cohort. Annual cancer incidence rates were calculated, and based on these, a penetrance curve was constructed. The average annual cancer risk for the Norwegian women from age 25 to 70 was 2.0%. Founder mutations had lower incidence rate (1.7%) than less frequent mutations (2.5%) (p = 0.03). The peak incidence (3.1% annual risk) was observed in women from age 50 to 59. The age-specific annual incidence rates and penetrance estimate were compared with published figures for women from North America and from Poland. The risk of breast cancer to age 70 was estimated to be 61% for women from Norway, compared with 55% for women from Poland and 69% for women from North America.

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)0.000
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 score0.131
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.047
GPT teacher head0.396
Teacher spread0.350 · 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

Citations16
Published2012
Admission routes1
Has abstractyes

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