Association between parity and breast cancer among women in north-central Nigeria: An exploratory case-control analysis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".