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The effect of surgery type on survival and recurrence in very young women with breast cancer.

2013· article· en· W3006536995 on OpenAlexaffabout
May Lynn Quan, Lawrence Paszat, Kimberley Fernandes, Rinku Sutradhar, David R. McCready, Eileen Rakovitch, Ellen Warner, Frances C. Wright, Nicole Hodgson, Muriel Brackstone, Nancy N. Baxter

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsLondon Health Sciences CentreHealth Sciences CentreUniversity of TorontoUniversity Health NetworkJuravinski Cancer CentreSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesPrincess Margaret Cancer CentreFoothills Medical Centre
Fundersnot available
KeywordsMedicineMastectomyBreast cancerProportional hazards modelRadiation therapyCancer registryPopulationBreast-conserving surgerySurgeryCohortCancerRetrospective cohort studyOncologyInternal medicine

Abstract

fetched live from OpenAlex

1002 Background: Young age has been identified as an independent predictor of recurrence and mortality in women with breast cancer. The equivalence of breast conserving surgery (BCS) with mastectomy remains unclear in this population in an era of multimodal therapy. We sought to determine the effect of surgery type on the risk of recurrence and survival in a large, population based cohort of very young women. Methods: All women diagnosed with breast cancer aged ≤35 between 1994 and 2003 in Ontario were identified from the Ontario Cancer Registry, a population based registry of all incident invasive breast cancers in the province. A retrospective chart review was undertaken to identify patient, tumor and treatment variables, as well as locoregional, distant recurrences and death. Univariable and multivariable Cox proportional hazards regression models were fit to determine the effect of primary surgery type on overall survival while controlling for known confounders. To examine time to recurrence in a multivariable analysis, the proportional subdistribution hazards model (Fine and Gray) was used to account for death being a competing risk. Results: A total of 1,381 patients were identified; the median age was 33 (range 18 – 35), median follow up was 11 years. Primary surgical treatment was BCS in 793 (57%) patients of which 89% had adjuvant radiotherapy. Of the 588 (43%) having mastectomy, 53% underwent post mastectomy radiation. Overall, 38% of patients sustained a recurrence of any type and 31% had died. After controlling for tumor size, margin status, node status, grade, LVI, ER/PR, HER2 and treatment (chemotherapy, radiation, hormones) there was no difference in overall survival (HR 0.99, 95% CI 0.79,1.26) or recurrence (HR 0.96, 95% CI 0.73,1.26) among women treated with BCS or mastectomy. Predictors of recurrence were size ≥2 cm, ≥ 1 positive node, neoadjuvant chemotherapy, and lack of radiation. Predictors of death were similar and included high grade and presence of LVI. Conclusions: Very young women selected for BCS had similar outcomes to those selected for mastectomy after controlling for known prognostic factors for recurrence and death.

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)0.000
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 score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.382
Teacher spread0.345 · 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".

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Citations5
Published2013
Admission routes2
Has abstractyes

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