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Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk
Iris Kramer, Maartje J. Hooning, Nasim Mavaddat, Michael Hauptmann, Renske Keeman, Ewout W. Steyerberg, Daniele Giardiello, Antonis C. Antoniou, Paul D.P. Pharoah, Sander Canisius, Zumuruda Abu-Ful, Irene L. Andrulis, Hoda Anton‐Culver, Kristan J. Aronson, Annelie Augustinsson, Heiko Becher, Matthias W. Beckmann, Sabine Behrens, Javier Benı́tez, Marina Bermisheva, Natalia Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Bernardo Bonanni, Hiltrud Brauch, Michael Bremer, Sara Y. Brucker, Barbara Burwinkel, Jose E. Castelao, Tsun Leung Chan, Jenny Chang‐Claude, Stephen J. Chanock, Georgia Chenevix‐Trench, Ji‐Yeob Choi, Christine L. Clarke, Anne‐Lise Børresen‐Dale, Kristine Kleivi Sahlberg, Lars Ottestad, Rolf Kåresen, Ellen Schlichting, Marit Muri Holmen, Toril Sauer, Vilde Drageset Haakensen, Olav Engebråten, Bjørn Naume, Alexander Fosså, Cecile E. Kiserud, Kristin V. Reinertsen, Åslaug Helland, Margit Riis, Jürgen Geisler, Grethe Grenaker Alnæs, Margriet Collée, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Peter Devilee, Thilo Dörk, Isabel dos‐Santos‐Silva, Alison M. Dunning, Miriam Dwek, D. Gareth Evans, Peter A. Fasching, Henrik Flyger, Manuela Gago-Domínguez, Montserrat García‐Closas, José Á. García-Sáenz, Graham G. Giles, Anna González‐Neira, Christopher A. Haiman, Niclas Håkansson, Ute Hamann, Mikael Hartman, Bernadette A. M. Heemskerk‐Gerritsen, Antoinette Hollestelle, John L. Hopper, Ming‐Feng Hou, Anthony Howell, Deborah J. Marsh, Rodney J. Scott, Robert Baxter, Desmond Yip, Jane Carpenter, Alison Davis, Nirmala Pathmanathan, Peter T. Simpson, J. Dinny Graham, Mythily Sachchithananthan, David J. Amor, Lesley Andrews, Yoland Antill, Rosemary L. Balleine, Jonathan Beesley, Ian Bennett, Michael Bogwitz, Leon Botes, Meagan Brennan, Melissa A. Brown, Michael F. Buckley, Jo Burke, Phyllis Butow, Liz Caldon, Ian Campbell, Deepa Chauhan, Manisha Chauhan, Alice Christian, Paul A. Cohen, Alison Colley, Ashley Crook, James Cui, Margaret C. Cummings, Sarah‐Jane Dawson, Anna DeFazio, Martin Delatycki, Rebecca Dickson, Joanne Dixon, Ted Edkins, Stacey L. Edwards, Gelareh Farshid, Andrew Fellows, Georgina Fenton, Michael Field, James M. Flanagan, Peter C.C. Fong, Laura Forrest, Stephen B. Fox, Juliet D. French, Michael Friedländer, Clara Gaff, Mike Gattas, Peter George, Sian Greening, Marion Harris, Stewart Hart, Cass Hoskins, Clare Hunt, Paul A. James, Mark A. Jenkins, Alexa Kidd, Judy Kirk, Jessica Koehler, James Kollias, Sunil R. Lakhani, Mitchell G. Lawrence, Geoffrey J. Lindeman, Lara Lipton, Liz Lobb, Graham J. Mann, Sue Anne McLachlan, Bettina Meiser, Roger L. Milne, Sophie Nightingale, Shona O’Connell, Sarah O’Sullivan, David Gallego‐Ortega, Nick Pachter, Briony Patterson, Amy Pearn, Ellen Pieper, Edwina Rickard, Bridget A. Robinson, Mona Saleh, Elizabeth Salisbury, Christobel Saunders, Jodi M. Saunus, Clare L. Scott, Adrienne Sexton, Andrew N. Shelling, Melissa C. Southey, Amanda B. Spurdle, Jessica Taylor, Renea A. Taylor, Heather Thorne, Alison H. Trainer, Kathy Tucker, Jane E. Visvader, Logan C. Walker, Rachael Williams, Ingrid Winship, Mary Ann Young, Hidemi Ito, Milena Jakimovska, Anna Jakubowska, Wolfgang Janni, Esther M. John, Audrey Jung, Daehee Kang, C. Marleen Kets, Э. К. Хуснутдинова, Yon‐Dschun Ko, Vessela N. Kristensen, Allison W. Kurian, Ava Kwong, Diether Lambrechts, Loı̈c Le Marchand, Jingmei Li, Annika Lindblom, Jan Lubiński, Mehdi Manoochehri, Sara Margolin, Keitaro Matsuo, Dimitrios Mavroudis, Anna Marie Mulligan, Taru Muranen, Susan L. Neuhausen, Heli Nevanlinna, William G. Newman, Andrew F. Olshan, Janet E. Olson, Håkan Olsson, Tjoung‐Won Park‐Simon, Julian Peto, Christos Petridis, Dijana Plaseska‐Karanfilska, Nadège Presneau, Katri Pylkäs, Paolo Radice, Gad Rennert, Atocha Romero, Rebecca Roylance, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Lukas Schwentner, Mee‐Hoong See, Mitul Shah, Chen‐Yang Shen, Xiao‐Ou Shu, Sabine Siesling, Susan Slager, Christof Sohn, John J. Spinelli, Jennifer Stone, William Tapper, Maria Tengström, Soo‐Hwang Teo, Mary Beth Terry, Rob A.�E.�M. Tollenaar, Ian Tomlinson, Melissa A. Troester, Celine M. Vachon, Chantal Van Ongeval, Elke M. van Veen, Robert Winqvist, Alicja Wolk, Wei Zheng, Argyrios Ziogas, Douglas F. Easton, Per Hall, Marjanka K. Schmidt
Bibliographic record
VenueThe American Journal of Human Genetics · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoUniversity Health NetworkQueen's UniversityLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersNational Institute of Environmental Health SciencesLeids Universitair Medisch CentrumMedical Research CouncilCancer Institute NSWCanadian Institutes of Health ResearchImperial Experimental Cancer Medicine CentreNational Cancer InstituteWellcome TrustCancer Research UKKWF KankerbestrijdingNational Breast Cancer FoundationNational Health and Medical Research CouncilGovernment of CanadaEuropean CommissionBreast Cancer Research FoundationInstituto de Salud Carlos IIIAmgenOvarian Cancer Research FundCancer Council Western AustraliaPfizerNational Institute for Health and Care ResearchGenome CanadaFondation du cancer du sein du QuébecNational Institutes of Health
KeywordsBreast cancerPolygenic risk scoreMedicineOncologyCancerRisk assessmentInternal medicineBiologySingle-nucleotide polymorphismGeneticsGeneGenotypeComputer science
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
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 score0.008
Threshold uncertainty score0.025
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 head0.273
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation status
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.
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
Citations69
Published2020
Admission routes2
Has abstractno