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Record W1871681524 · doi:10.1111/cge.12233

Health care provider recommendations for reducing cancer risks among women with a <i> BRCA1</i> or <i>BRCA2</i> mutation

2013· article· en· W1871681524 on OpenAlexafffundabout
Kelly Metcalfe, Charmaine Kim‐Sing, P Ghadirian, Peng Sun, SA Narod

Bibliographic record

VenueClinical Genetics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversité de MontréalBC Cancer AgencyWomen's College HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsMedicineTamoxifenProphylactic MastectomyBreast cancerOophorectomyGuidelineGenetic counselingCancerProphylactic SurgeryMastectomyGynecologyFamily medicineGenetic testingHealth careOncologyInternal medicineHysterectomySurgeryGeneticsPathology

Abstract

fetched live from OpenAlex

There is a significant variation in the uptake of cancer risk reducing options by women with a BRCA1 or BRCA2 mutation. It is currently unclear why these differences exist and it is possible that recommendations vary between providers and these influence patient decisions. Eligible health care providers who provide genetic counseling for hereditary breast and ovarian cancer families in Canada were identified. Each provider was asked to complete a study specific questionnaire that included their opinion of various cancer risk reduction options and their recommendations for specific cases. Respondents recommended prophylactic oophorectomy more often than prophylactic mastectomy or tamoxifen for women with a BRCA1 or BRCA2 mutation (p < 0.0001). Fewer than half of the respondents agreed with the recommendation for prophylactic mastectomy, and a minority of the respondents supported the recommendation for tamoxifen for chemoprevention. The majority of Canadian genetics health care providers adhere to the National Comprehensive Cancer Network (NCCN) Guideline of recommending prophylactic oophorectomy to mutation carriers, however, the minority of genetics health care providers recommend either prophylactic mastectomy or tamoxifen.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.735

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 head0.065
GPT teacher head0.412
Teacher spread0.347 · 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 designNot applicable
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

Citations20
Published2013
Admission routes3
Has abstractyes

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