Racial, ethnic and socioeconomic disparities in diagnosis, treatment, and survival of patients with breast cancer- A Population Analysis in the United States
Bibliographic record
Abstract
Racial disparities in breast cancer are well established. However, there is a paucity of literature assessing the interaction of patient, socioeconomic, and community factors on breast cancer care. The objective of this study was to determine the influence of race/ ethnicity, socioeconomic status (SES), and insurance status on disease presentation, access to care, and survival in breast cancer. A retrospective analysis was conducted of patients of Non-Hispanic White (NHW), Hispanic, and Non-Hispanic Black (NHB) patients with non-metastatic breast cancer in a large American national cancer registry. A total of 382,975 patients were identified. We demonstrated that NHB and Hispanic patients are more likely to present with more advanced stage disease, less likely to undergo surgery, and less likely to undergo breast reconstruction than their NHW counterparts. We also demonstrated worse survival for NHB patients compared to NHW patients. Furthermore, we demonstrated that these disparities were compounded across worsening socioeconomic status and insurance coverage.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".