The influence of cosmetic breast augmentation on the stage distribution and prognosis of women subsequently diagnosed with breast cancer
Bibliographic record
Abstract
This study aimed to determine whether cosmetic breast implants impair the early detection of breast cancer, and adversely influence survival. This analysis derives from a cohort of 24,558 women who received bilateral cosmetic breast implants, and 15,893 women who underwent other plastic surgery procedures at the same practices in Ontario and Quebec, Canada, between 1974 and 1989. Incident cancers and vital status through 1997 were determined by record linkage to the Canadian Cancer Registry and Canadian Mortality Database. Analyses are based on a total of 182 and 202 incident cases of breast cancer identified among the implant and control groups, respectively. Contingency table analyses were performed to test for differences in the stage distribution of breast cancers between the 2 groups. Potential differences in survival were evaluated using the Kaplan-Meier estimates and Cox proportional hazards models. Women who received breast implants were more likely to have advanced stage breast carcinoma relative to the other plastic surgery patients (crude and adjusted ps </= 0.01). No statistically significant differences in distributions between the implant and control patients were found for age at diagnosis, tumor size, histological type, period of diagnosis or length of follow-up. The delayed diagnosis in augmented women did not appear to influence the overall prognosis. Breast cancer-specific survival was similar in both groups (hazard ratio = 1.06; 95% confidence interval = 0.65-1.74). In conclusion, this study suggests that breast implants delay the detection of breast cancer, but there was no statistically significant difference in survival between the breast implant and other plastic surgery groups.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".