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Record W2806095229 · doi:10.1007/s10897-018-0264-2

Uptake of Preimplantation Genetic Diagnosis in Female BRCA1 and BRCA2 Mutation Carriers

2018· article· en· W2806095229 on OpenAlexaff
Pnina Mor, Sarah Brennenstuhl, Kelly Metcalfe

Bibliographic record

VenueJournal of Genetic Counseling · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of Toronto
FundersNational Comprehensive Cancer Network
KeywordsPreimplantation genetic diagnosisBRCA mutationMedicineGynecologyGenetic counselingBreast cancerOvarian cancerInfertilityGenetic testingRegretObstetricsGermline mutationOncologyCancerMutationInternal medicinePregnancyGeneticsBiologyGene

Abstract

fetched live from OpenAlex

Women with a germline pathogenic variant in the BReast CAncer susceptibility genes (BRCA1 or BRCA2) have an increased risk of early-onset breast and ovarian cancer. In addition to weighing cancer screening and risk-reduction options, healthy BRCA mutation carriers of childbearing age may choose to preclude passing the mutation to the next generation. In the current study, we report on preimplantation genetic diagnosis (PGD) practices in BRCA-positive Israeli women who were offered PGD at no cost. Methods: we measured PGD uptake, decision satisfaction or regret, and predictors of uptake. Of the 70 participant female carriers, only 25.7% chose to use PGD to prevent transmission of the mutation, and were not predicted by age or religious affiliation. For those who chose IVF/PGD, satisfaction with the decision regarding IVF and PGD was significantly higher than those who did not have IVF and PGD (p < 0.04). Experiencing previous infertility was the only significant predictor of uptake of IVF/PGD (p < 0.001), which may suggest that BRCA status is secondary to infertility in the decision-making process for PGD in women with a BRCA mutation.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.453

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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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 designBench or experimental
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

Citations27
Published2018
Admission routes1
Has abstractyes

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