Impact of a breast cancer (BC) polygenic risk score (PRS) on the decision to take preventive endocrine therapy (ET): The Genetic Risk Estimate (GENRE) trial.
Bibliographic record
Abstract
1501 Background: Despite BC risk reduction of 50-65% by preventive endocrine therapy (ET), very few at-risk women choose to take them. A woman’s perceived BC risk correlates with uptake of ET. A PRS comprised of 77 BC genetic susceptibility loci (Single Nucleotide Polymorphisms (SNP) improves the accuracy of risk prediction for BC. We examined the impact of the addition of individualized PRS BC risk prediction to standard risk calculator estimates on intent to take BC prevention medication. Methods: Eligible women had ≥5% 10 yr BC Tyrer-Cuzick risk (IBIS) or 5 year Gail score ≥3%, with no history of BC or hereditary BC syndrome. Standard BC risk estimates (IBIS or Gail) were incorporated into the counselling on BC preventive ET. A self-reported questionnaire at baseline quantified intention to take ET and explored factors associated with this decision. Blood samples were obtained and genotyped for 77 SNPs, individualized PRS were calculated then incorporated into IBIS and Gail predictions for 5 yr, 10 yr, & lifetime BC risk. At a second visit, PRS risk & prevention recommendations were revisited. Post visit questionnaires assessed change in intent to take ET. Multivariable linear regression was performed to assess impact of baseline variables on change in intent to take medication. Results: From 2016 to 2017, 151 women in Canada & USA were enrolled, median age: 56.1 (range 36-76.4), 35.6% were premenopausal, 98.7% were Caucasian. Median 5yr, 10yr, & lifetime IBIS risk estimates were 3.8% (2.0-11.5), 7.9% (5.0-23.1), and 25.3% (5.5 to 92.2). PRS increased BC risk estimates in 84 (55.6%) and reduced BC risk estimates in 67 (44%) women. After PRS risk counselling, intention to take ET significantly changed (p<0.001): 41.9% of those with increased PRS were more inclined, and 46.7% of women with decreased PRS were less inclined to take ET. On multivariable regression, increase in PRS (p<0.0001) and less concern about ET side effects (p<0.0001) were associated with greater intent to take ET. Conclusions: In high risk women, PRS significantly changed BC risk estimates & intent to take preventive ET. Further assessments of the impact of PRS scores on compliance with ET are warranted. Clinical trial information: NCT02517593.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".