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Record W3107714852 · doi:10.1038/s41436-020-01029-1

Risk-reducing hysterectomy and bilateral salpingo-oophorectomy in female heterozygotes of pathogenic mismatch repair variants: a Prospective Lynch Syndrome Database report

2020· article· en· W3107714852 on OpenAlexaff
Mev Dominguez–Valentin, Emma J. Crosbie, Christoph Engel, Stefan Aretz, Finlay Macrae, Ingrid Winship, Gabriel Capellá, Huw Thomas, Sigve Nakken, Eivind Hovig, Maartje Nielsen, Rolf H. Sijmons, Lucio Bertario, Bernardo Bonanni, Maria Grazia Tibiletti, Giulia Martina Cavestro, Miriam Mints, Nathan Gluck, Lior H. Katz, Karl Heinimann, Carlos Vaccaro, Kate Green, Fiona Lalloo, James Hill, Wolff Schmiegel, Deepak Vangala, Claudia Perne, Hans-Georg Strauß, Johanna Tecklenburg, Elke Holinski‐Feder, Verena Steinke‐Lange, Jukka‐Pekka Mecklin, John‐Paul Plazzer, Marta Pineda, Matilde Navarro, Revital Kariv, Guy Rosner, Tamara Alejandra Piñero, María Laura González, Pablo Kalfayan, Neil Ryan, Sanne W. ten Broeke, Mark A. Jenkins, Lone Sunde, Inge Bernstein, John Burn, Marc S. Greenblatt, Wouter H. de Vos tot Nederveen Cappel, Adriana Della Valle, Francisco Lopez-Koestner, Karin Álvarez, Reinhard Büttner, Heike Görgens, Monika Morak, Stefanie Holzapfel, Robert Hüneburg, Magnus von Knebel Doeberitz, Markus Loeffler, Nils Rahner, Jürgen Weitz, Kirsi Pylvänäinen, Laura Renkonen‐Sinisalo, Anna Lepistö, Annika Auranen, John L. Hopper, Aung Ko Win, Robert W. Haile, Noralane M. Lindor, Steven Gallinger, Loı̈c Le Marchand, Polly A. Newcomb, Jane C. Figueiredo, Stephen N. Thibodeau, Christina Therkildsen, Henrik Okkels, Zohreh Ketabi, Oliver G. Denton, Einar Andreas Rødland, Hans F. A. Vasen, Florencia Neffa, Patricia Esperón, Douglas Tjandra, Gabriela Möslein, Julian R. Sampson, D. Gareth Evans, Toni T. Seppälä, Pål Møller

Bibliographic record

VenueGenetics in Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersEuropean Regional Development FundMedical Research CouncilNational Institutes of HealthCentro de Investigación Biomédica en Red de CáncerMinisterio de Economía y CompetitividadDeutsche KrebshilfeEmil Aaltosen SäätiöJane ja Aatos Erkon SäätiöInstrumentariumin TiedesäätiöNational Institute for Health and Care ResearchGeneralitat de CatalunyaParc Geneteg CymruHealth and Care Research WalesNational Cancer InstituteKWF KankerbestrijdingSuomen Lääketieteen SäätiöKreftforeningen
KeywordsEndometrial cancerMedicineMSH6Lynch syndromeHysterectomyProspective cohort studyPMS2GynecologyUterine cancerOophorectomyInternal medicineCancerSurgeryDNA mismatch repairColorectal cancer

Abstract

fetched live from OpenAlex

PURPOSE: To determine impact of risk-reducing hysterectomy and bilateral salpingo-oophorectomy (BSO) on gynecological cancer incidence and death in heterozygotes of pathogenic MMR (path_MMR) variants. METHODS: The Prospective Lynch Syndrome Database was used to investigate the effects of gynecological risk-reducing surgery (RRS) at different ages. RESULTS: Risk-reducing hysterectomy at 25 years of age prevents endometrial cancer before 50 years in 15%, 18%, 13%, and 0% of path_MLH1, path_MSH2, path_MSH6, and path_PMS2 heterozygotes and death in 2%, 2%, 1%, and 0%, respectively. Risk-reducing BSO at 25 years of age prevents ovarian cancer before 50 years in 6%, 11%, 2%, and 0% and death in 1%, 2%, 0%, and 0%, respectively. Risk-reducing hysterectomy at 40 years prevents endometrial cancer by 50 years in 13%, 16%, 11%, and 0% and death in 1%, 2%, 1%, and 0%, respectively. BSO at 40 years prevents ovarian cancer before 50 years in 4%, 8%, 0%, and 0%, and death in 1%, 1%, 0%, and 0%, respectively. CONCLUSION: Little benefit is gained by performing RRS before 40 years of age and premenopausal BSO in path_MSH6 and path_PMS2 heterozygotes has no measurable benefit for mortality. These findings may aid decision making for women with LS who are considering RRS.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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.

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

Citations42
Published2020
Admission routes1
Has abstractyes

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