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Record W2606565056 · doi:10.1093/jnci/djx051

Association of Common Genetic Variants With Contralateral Breast Cancer Risk in the WECARE Study

2017· article· en· W2606565056 on OpenAlexaff
Mark E. Robson, Anne S. Reiner, Jennifer D. Brooks, Patrick Concannon, Esther M. John, Lene Mellemkjær, Leslie Bernstein, Kathleen E. Malone, Julia A. Knight, Charles F. Lynch, Meghan Woods, Xiaolin Liang, Robert W. Haile, David Duggan, Roy E. Shore, Susan A. Smith, Duncan C. Thomas, Daniel O. Stram, Jonine L. Bernstein

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsSinai Health SystemLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersNational Cancer Institute
KeywordsBreast cancerAssociation (psychology)MedicineOncologyGenetic associationGenome-wide association studyGeneticsInternal medicineCancerBiologyBioinformaticsSingle-nucleotide polymorphismGenotypeGenePsychology

Abstract

fetched live from OpenAlex

Background: Women with unilateral breast cancer (UBC) are at risk of developing a subsequent contralateral breast cancer (CBC). Common variants are associated with breast cancer risk. Whether these influence CBC risk is unknown. Methods: Participants were breast cancer cases from the population-based Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study. Sixty-seven established breast cancer risk loci were genotyped directly or by imputation in 1459 case subjects with CBC and 2126 UBC control subjects. An unweighted polygenic risk score (PRS) was created by summing the number of risk alleles for each directly genotyped single nucleotide polymorphism (SNP), or for imputed loci, the imputed dosage. A weighted PRS was calculated similarly, but where each SNP's contribution was weighted by the published per-allele log odds ratio. Unweighted and weighted polygenic risk scores and CBC risk were modeled using conditional logistic regression. Cumulative CBC risk was estimated and benchmarked using Surveillance, Epidemiology, and End Results population incidence rates. Results: Both unweighted and weighted PRS were statistically significantly associated with CBC risk. The adjusted risk ratio of CBC in women in the upper quartile of unweighted PRS compared with the lowest quartile was 1.63 (95% confidence interval [CI] = 1.33 to 2.00). The estimated 10-year cumulative risk for women in the upper quartile of the unweighted PRS was 7.4% (95% CI = 6.0% to 9.1%). For women in the upper quartile of the weighted PRS, the risk ratio for CBC was 1.75 (95% CI = 1.41 to 2.18) compared with women in the lowest quartile. There was no statistically significant heterogeneity by age, treatment (radiation therapy dose, tamoxifen, chemotherapy), estrogen receptor status of the first primary, histology of the first primary, length of at-risk period for CBC, or breast cancer family history. Conclusions: Common genomic variants associated with the development of first primary breast cancer are also associated with the development of CBC; the risk is strongest among those who carry more risk alleles.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.323
Teacher spread0.304 · 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 designObservational
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

Citations37
Published2017
Admission routes1
Has abstractyes

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