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Abstract PD3-03: Impact of the breast cancer polygenic risk score on preventive endocrine therapy adherence and endocrine therapy usage on quality of life - The Genetic Risk Estimate (GENRE) trial

2020· article· en· W3010231504 on OpenAlexaffabout
Sandhya Pruthi, Julian O. Kim, Daniel J. Schaid, Andrew Cooke, Christina Kim, Benjamin A. Goldenberg, Jason P. Sinnwell, Debjani Grenier, Fergus J. Couch, Celine M. Vachon

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsCancerCare Manitoba
Fundersnot available
KeywordsMedicineBreast cancerOdds ratioInternal medicineRisk assessmentGynecologySingle-nucleotide polymorphismCancerOncologyGenotypeGenetics

Abstract

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Abstract Background: Studies demonstrate breast cancer risk reduction of 50-65% with the use of endocrine therapy (ET) and yet drug uptake and adherence in this setting is suboptimal even among high risk women. A Polygenic Risk Score (PRS) comprised of 77 BC genetic susceptibility loci (Single Nucleotide Polymorphisms (SNP)) can provide a personalized risk assessment and potentially influence ET adherence. We assessed ET adherence at 1 year comparing women whose risk estimate increased due to PRS versus women whose risk estimate decreased due to PRS. The effect of ET use on quality of life (hot flashes, night sweats, vaginal dryness, weight gain, joint pain) was evaluated. Methods: Eligible women required either a 5 year Gail Model risk of ≥3% or 10 year IBIS ( International Breast Intervention Study or Tyrer-Cuzick model) of ≥5%. Women with a history of breast cancer (BC) or hereditary BC syndrome were excluded. High risk women were counseled at baseline using their Gail and IBIS risk scores and ET options were discussed including benefits and risks. Participants completed a self-reported questionnaire at baseline to assess their understanding of breast cancer risk and decision to take preventive ET. Blood samples were obtained and genotyped for 77 SNPs, and the odds ratio from the SNPs were used to modify the IBIS and Gail risk estimates. The BC -PRS risk estimate information was shared with study participants that reflected the IBIS and Gail risk estimates for 5 year, 10 year, & lifetime BC risk with and without the PRS. Follow up questionnaires at year 1 were administered to assess drug adherence and ET usage on quality of life. Results: 151 women were enrolled at Mayo Clinic Rochester and CancerCare Manitoba from 2016 to 2017. The median age was 56.1 (range 36-76.4), 35.6% were premenopausal, 98.7% were Caucasian and 64.7% had>1 family member with BC. Median 5yr, 10yr, & lifetime IBIS- PRS risk estimates were 3.8% (2.0-11.5), 7.9% (5.0-23.1), and 25.3% (5.5 to 92.2). At year 1 (n=112 women) 46 % of those with an increase in risk when considering the BC-PRS score and 16 % with a decrease in risk were taking ET ( p< 0.001). Types of ET taken: tamoxifen-18, raloxifene- 3, exemestane -14 and missing-1. Women taking ET reported weight gain ( 19.4% vs 6.7%, p=0.04) and more joint pain ( 27.8 % vs 12%, p=0.04) when compared to women not taking ET. Conclusion: In high risk women, BC-PRS risk estimates in addition to standard BC risk calculators had a significant impact on preventive ET adherence. ET use was associated with weight gain and joint pain. Citation Format: Sandhya Pruthi, Julian O Kim, Daniel Schaid, Andrew Cooke, Christina Kim, Benjamin Goldenberg, Jason Sinnwell, Debjani Grenier, Fergus Couch, Celine Vachon. Impact of the breast cancer polygenic risk score on preventive endocrine therapy adherence and endocrine therapy usage on quality of life - The Genetic Risk Estimate (GENRE) trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD3-03.

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)0.002
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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.100
GPT teacher head0.446
Teacher spread0.346 · 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 designRandomized trial
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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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