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Impact of gynecological screening in Lynch syndrome carriers with an <i>MSH2</i> mutation

2012· article· en· W1822066090 on OpenAlexafffund
Susan Stuckless, Julie Green, Lesa Dawson, Brendan J. Barrett, MO Woods, Elizabeth Dicks, Parfrey Ps

Bibliographic record

VenueClinical Genetics · 2012
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsMedicineLynch syndromeOvarian cancerEndometrial cancerGynecologyCancerHysterectomyIncidence (geometry)Prophylactic SurgeryCancer screeningObstetricsInternal medicineColorectal cancerOncologySurgeryDNA mismatch repair

Abstract

fetched live from OpenAlex

Lifetime risk of developing endometrial cancer in Lynch syndrome carriers is very high and females are also at an increased risk of developing ovarian cancer. The aim of the study was to determine the impact of gynecological screening in MSH2 mutation carriers. Gynecological cancer incidence and overall survival was compared in female mutation carriers who received gynecological screening (cases) and in matched controls. Controls were randomly selected from non-screened mutation carriers who were alive and disease-free at the age the case entered the screening program. Median age to diagnosis of gynecological cancer was 54 years in the screened group compared to 56 years in controls (p = 0.50). Stage I or II cancer was diagnosed in 92% of screened patients compared to 71% in the control group (p = 0.17). Two of three deaths in the screened group were the result of ovarian cancer. Mean survival in the screened group was 79 years compared to 69 years in the control group (p = 0.11), likely associated with concomitant colonoscopy screening. Gynecological screening did not result in earlier gynecologic cancer detection and despite screening two young women died from ovarian cancer suggesting that prophylactic hysterectomy with bilateral salpingo-oophorectomy be considered in female mutation carriers who have completed childbearing.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.085
GPT teacher head0.421
Teacher spread0.336 · 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.

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

Citations34
Published2012
Admission routes2
Has abstractyes

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