MétaCan
Menu
← Back to cohort

BRCA1/2 mutations and cancer risk in Asian-Americans

2007· article· en· W2261925730 on OpenAlexaff
Allison W. Kurian, Nicolette M. Chun, Meredith Mills, Ashley D. Staton, Brittany Crawford, Yolanda Ridge, Susan S. Donlon, Gail Gong, Dee W. West, James M. Ford

Bibliographic record

VenueJournal of Clinical Oncology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicinePenetranceMutationCancerEpidemiologyGeneticsInternal medicineOncologyBreast cancerDemographyGeneBiologyPhenotype

Abstract

fetched live from OpenAlex

10512 Background: There are significant differences in breast cancer epidemiology between Caucasian and Asian-Americans and even between different Asian groups. These cancer risks and associated BRCA1/2 mutation prevalence have not been well defined in Asians; BRCA1/2 mutation penetrance might differ due to different risk modifiers. We report on a case-control study of BRCA1/2 mutation prevalence and cancer risk in Asian-American women. Methods: Clinical Data Collection: Chart review from cancer genetics services of 4 North American centers with highest Asian volume. BRCA1/2 Mutation Risk Assessment: BRCAPRO and Myriad II models, CancerGene version 4.3 (University of Texas). BRCA1/2 Mutation Testing: Full sequencing and large rearrangement panel (Myriad Genetics Inc.). Endpoints: BRCA1/2 mutation prevalence and predictive model accuracy (observed versus predicted mutations). Results: 43 of 181 Asians (23.8%) had a BRCA1/2 mutation; 36 (19.9%) had a variant of uncertain significance. The observed prevalence of BRCA1/2 mutations was 23.8% of women, which differs significantly from the predicted prevalence of 12.9% using BRCAPRO (p = 5.6 × 10-9), and the predicted prevalence of 12.6% using Myriad II. This 2-fold difference existed for Chinese, Japanese, and Filipina women (the ethnic sub-groups with enough cases available for comparisons), even though the percent with observed and predicted mutations varied for these three groups. Conclusions: One in 4 clinically tested Asian-Americans has a BRCA1/2 mutation. Standard models significantly under-predict mutations in Asians; consequently, Asians are likely under-tested for BRCA1/2 mutations. These results may reflect lower BRCA1/2-associated cancer risk in Asians compared to Caucasians. Comparison to Caucasian controls and to Asians in Hong Kong is underway, to investigate potential genetic and lifestyle modifiers of BRCA1/2-associated cancer risk. [Table: see text] No significant financial relationships to disclose.

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)0.002
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.060
GPT teacher head0.470
Teacher spread0.410 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical Oncology→Same topicBRCA gene mutations in cancer→French-language works237,207→