Abstract B006: Reduced survival outcomes in lower income quintile groups for women with breast cancer treated with chemotherapy in Ontario, Canada
Bibliographic record
Abstract
Abstract Background: Despite the comparably comprehensive healthcare system in Canada, health inequities are widespread, and this holds true for breast cancer patients in Ontario. It is thus essential to learn if socio-demographic disparities continue after diagnosis of breast cancer, and if these contribute to higher mortality rates in the lower income quintile groups. Methods: We conducted a real-word population-based study using a provincial health administrative dataset from Ontario, Canada. We included patients diagnosed with HER2-negative breast cancer, treated with surgery and adjuvant chemotherapy, between 2009 to 2017. We used log-rank test and Kaplan Meier curves to compare overall survival (OS) between breast cancer populations among income quintile groups, and Cox regression to evaluate risk factors, using hazard ratio (HR) and 95% confidence intervals (CI). Results: We analysed 10,634 women diagnosed with stage I-III breast cancer. At diagnosis, in the Q1 group, there were 248 (15.8%) women with stage I, 997 (63.7%) with stage II, and 320 (20.45%) with stage III. In the Q5 group, there were 568 (22.15%), with stage I, 1,532 (59.75%) with stage II and 464 (18%) with stage III. Comparison between those in the lowest versus highest income quintile groups, and lymph node (LN) status at diagnosis, showed that in Q1, 534 (34%) women had LN 0 and 897 (57.3%) had LN+. In Q5, there were 954 (37.2%) women with LN 0 and 1,379 (53.8%) with LN+. Similarly, comparing tumor size (TS) at diagnosis, we found that in Q1, there were 463 (32.2%) women with TS≤ 2 cm and 974 (67.8%) with TS > 2 cm. In Q5, 915 (39%) women had TS≤ 2 cm and 1,426 (61%) had TS > 2 cm. In the Q1 group, there were 325 (20.7%) patients who received non- anthracycline and 1,240 (79.3%) treated with anthracycline-taxane chemotherapy. In Q5, there were 673 (26.2%) women treated with non-anthracycline and 1,891 (73.8%) who received anthracycline-taxane chemotherapy. The OS analysis based on the household income group compared to Q5 showed a substantial difference in the Q1 (HR 1.52, 1.2–1.9, p = 0.0002) and Q2 (HR 1.34, 1.1–1.7, p = 0.006) groups. In Cox regression models, Q5 group and endocrine receptor (ER) positive were significantly associated with reduced mortality risk. There was a significant correlation between increased risk of death and the following: receipt of non- anthracycline chemotherapy, TS > 2 cm, LN+ and grade 3 histology. Conclusion: Our study found an uneven distribution of breast cancer patients between the lowest and highest income quintile groups. Women with HER2-negative breast cancer who were part of the lower income quintile groups, thereby likely with a socioeconomic disadvantage, had the lowest OS. At diagnosis, these women were more likely to have more advanced breast cancer staging, including larger tumors, LN+, and receive anthracycline-based chemotherapy as compared to those with higher household income. Further research is warranted to identify the key social determinants that are systematically associated with disparities in equitable access to care. Citation Format: Danilo Giffoni M. M. Mata, Rossanna C. Pezo, Kelvin K.W. Chan, Ines Menjak, Andrea Eisen, Maureen Trudeau. Reduced survival outcomes in lower income quintile groups for women with breast cancer treated with chemotherapy in Ontario, Canada [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B006.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".