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Record W7064293772

Association between parity and breast cancer among women in north-central Nigeria: An exploratory case-control analysis

2015· article· en· W7064293772 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Repository of the University of Porto (University of Porto) · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsParity (physics)Breast cancerFertilityPopulationCervical cancerPregnancyHomogeneousQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Many studies conducted over the years have recognized the substantial epidemiologic evidence on the contribution of reproductive factors for the occurrence of breast carcinoma, including parity. However, most studies evaluated relatively homogeneous populations, with a small number of women with high fertility, and the association of very high parity with breast cancer remains poorly understood. Therefore, we addressed this topic in an African population characterized by high fertility rates. METHODS: We conducted a case-control analysis among women that were attending the Taimako breast and cervical cancer-screening centre, which is located in Nasarawa state of North-Central Nigeria. RESULTS: Among cases, 34.5% of the women were 39 years or less. About a quarter had ever used oral contraceptives, nearly half had attained menopause, and nearly two thirds had parity higher than 4 (parity 5-6, 32.1%; parity 7-8, 25.0%, parity ≥9, 7.1%). Compared to women with parity 1-4 the risk of breast cancer tended to be higher among nulliparous women (OR=3.44, 95%CI: 0.68-17.54), though it was lower among those aged ≤45 years (OR=1.43, 95%CI: 0.11-18.22) and higher in participants aged >45 years (OR=12.07, 95%CI: 0.62-233.00). For women with higher parity, the OR estimates were similar for those with parity 5-6 (OR=2.54, 95%CI: 0.80-8.01) and 7-8 (OR=2.65, 95%CI: 0.74-9.48). CONCLUSION: Our results suggest that future increase in incident breast cancer cases in this setting may result from an improvement of screening and diagnostic services, rather than from a dramatic but unlikely reduction in parity. © 2015, ArquiMed. All rights reserved.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.209
Teacher spread0.198 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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