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Record W2890802023 · doi:10.1159/000493128

Breast Cancer in Pregnancy: A Retrospective Cohort Study

2018· article· en· W2890802023 on OpenAlexaff
Cynthia Maxwell, Hanan Al-Sehli, Jacqueline Parrish, Rohan D’Souza

Bibliographic record

VenueGynecologic and Obstetric Investigation · 2018
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMedicinePregnancyRetrospective cohort studyObstetricsBreast cancerGynecologyMalignancyCancerCohortGestationCohort studySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Gestational breast cancer (GBC) is the second most commonly occurring malignancy affecting pregnant women. Management is complex due to potential foetal risks in the setting of maternal treatment. We report on the maternal, foetal, short-term neonatal and placental histopathologic findings of a retrospective cohort of pregnant women with either pre-gestational (group 1) or GBC (group 2) from a tertiary-level maternity care centre. Of the 69 women identified over 12 years, there were 47 in group 1 and 22 in group 2. Demographics, stage of breast cancer at diagnosis were similar in the 2 groups. Women with GBC (group 2) were more likely to receive surgery and chemotherapy or surgery alone as compared to those in group 1. No women with GBC received radiation during pregnancy, but 2 received this treatment postpartum. With regard to pregnancy outcomes, induction of labour was more common in women with GBC, as was preterm birth. Most preterm birth in women with GBC was late preterm, iatrogenic in nature to facilitate postpartum treatment. We conclude comparable pregnancy outcomes for women with GBC as compared to those with pregestational breast cancer.

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)0.003
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.277
Teacher spread0.258 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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