MétaCan
Menu
Back to cohort
Record W3197352694 · doi:10.3390/biomedicines9091174

Is Gestational Diabetes Mellitus a Risk Factor of Maternal Breast Cancer? A Systematic Review of the Literature

2021· review· en· W3197352694 on OpenAlexaboutno aff
Julien Simon, Karine Goueslard, Sonia Bechraoui‐Quantin, Patrick Arveux, Catherine Quantin

Bibliographic record

VenueBiomedicines · 2021
Typereview
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
Fundersnot available
KeywordsGestational diabetesMedicineSystematic reviewBreast cancerHyperinsulinemiaMEDLINEDiabetes mellitusCochrane LibraryPregnancyMeta-analysisObstetricsInternal medicineCancerInsulin resistanceGestationEndocrinologyBiology

Abstract

fetched live from OpenAlex

The association between gestational diabetes mellitus (GDM) and breast cancer (BC) risk is complex. We aimed to examine this association in a systematic review of the literature. This review was done using the PubMed/Medline and Web of Science databases, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Newcastle-Ottawa Scale was used for the assessment of bias and quality of studies. Only English-language articles published before 1 June 2021, were included. Fourteen studies were included in this systematic review. Among them, eight did not find statistically significant results. Three studies showed a statistically significant increased risk of BC after GDM, and they explained this potential increased risk by hyperinsulinemia, hyperglycemia, and low-grade inflammation. However, three studies showed a statistically significant decreased risk of BC after GDM, suggesting a possible protective effect of hormonal changes induced by GDM during pregnancy. These controversial results should be interpreted with caution due to both quantitative and qualitative methodological shortcomings. Further investigations are thus needed in order to gain a better understanding of the associations between GDM and BC, and their underlying mechanisms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.066
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
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 head0.024
GPT teacher head0.337
Teacher spread0.313 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBiomedicinesSame topicCancer Risks and FactorsFrench-language works237,207