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Record W2109391495 · doi:10.1007/s10897-009-9228-x

The Effectiveness of Family History Questionnaires in Cancer Genetic Counseling

2009· article· en· W2109391495 on OpenAlexaffabout
Susan Randall Armel, Jeanna McCuaig, Amy Finch, Rochelle Demsky, Tony Panzarella, Joan Murphy, Barry P. Rosen

Bibliographic record

VenueJournal of Genetic Counseling · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsGenetic counselingFamily historyPedigree chartMedicineGenetic testingFamily medicineClinical psychologyGeneticsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

The number of individuals receiving genetic counseling for hereditary breast and ovarian cancer syndrome has steadily risen. To triage patients for genetic counseling and to help reduce the amount of time needed by a genetic counselor in direct patient contact, many clinics have implemented the use of family history questionnaires. Although such questionnaires are widely used, scant literature exists evaluating their effectiveness. This article explores the extent to which family history questionnaires are being used in Ontario and addresses the utility of such questionnaires in one familial cancer clinic. By comparing the pedigrees created from questionnaires to those updated during genetic counseling, the accuracy and effectiveness of the questionnaires was explored. Of 121 families recruited into the study, 12% acquired changes to their pedigree that led to a revised probability estimate for having a BRCA1 or BRCA2 mutation and 5% acquired changes that altered their eligibility for genetic testing. No statistically significant difference existed between the eligibility for genetic testing prior to and post counseling. This suggests that family history questionnaires can be effective at obtaining a family history and accurately assessing eligibility for genetic testing. Based on the variables that were significantly associated with a change in probability estimate, we further present recommendations for improving the clarity of such questionnaires and therefore the ease of use by patients.

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)0.001
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 score0.741
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.280
Teacher spread0.268 · 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

Citations25
Published2009
Admission routes2
Has abstractyes

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