Exploring Differences in Breast Cancer Presentation, Recurrence and Survival by Race/Ethnicity among Young Women in the Prospective PYNK Database
Bibliographic record
Abstract
Abstract Background: While socioeconomic factors contribute to most of the disparities in breast cancer (BC) outcomes between countries, the contribution of biological factors related to race/ethnicity has not been fully explored. Using our prospective database of young BC patients referred from the Greater Toronto Area, we compared clinical/pathological features of the BC, distant recurrence-free survival, and BC-specific survival according to patient race/ethnicity. Methods: A chart review was conducted of the 240 women aged 40 years and younger with a new diagnosis of BC who were seen at the Sunnybrook Odette Cancer Center (an academic tertiary referral cancer center in multiethnic Toronto, Canada) between February 2008 and January 2015 and enrolled in the prospective PYNK database. Associations between patients’ race/ethnicity (classified into five groups) and personal characteristics (age, weight, education, and estimated household income), results of germ-line genetic testing, tumor characteristics, treatment, and clinical outcomes were assessed. Results: Among the 209 women (87%) for whom parental race/ethnicity was known and who were not of “mixed” ancestry, race/ethnicity was as follows: Caucasian 57.4% ( n = 120), Black 8.6% ( n = 18), East Asian 15.8% ( n = 33), South Asian 8.6% ( n = 18), and South-East Asian 9.6% ( n = 20). Median age at the diagnosis of BC was 37. Median tumor size was 2.5 cm, and 58% had lymph node involvement. The majority of patients had hormone receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative BC, 26% had HER2-positive disease, and 13% had triple-negative BC (TNBC). One hundred and seventy-five (83.7%) patients were treated with chemotherapy, 51 (29.1%) of whom received it in the neoadjuvant setting. There were no statistically significant differences in median age, residence type (urban vs. rural), income level, germ-line genetic test results, tumor histology (lobular vs. ductal), BC subtype, stage of disease at presentation, or proportion of patients who received chemotherapy across the various racial/ethnic groups. With a median follow-up of 10.5 years, South Asian women had a nonsignificantly higher risk of distant recurrence and BC-specific death compared with Caucasian women (hazard ratio [HR] = 1.27, 95% confidence interval [CI]: 0.49–3.29, P = 0.627 and HR = 1.42, 95% CI: 0.48–4.16, P = 0.521, respectively), while East Asian ethnicity was associated with lowest risk of distant recurrence (HR = 0.52, 95% CI: 0.18–1.49, P = 0.224) and BC-related death (HR = 0.36, 95% CI: 0.08–1.53, P = 0.167). Conclusion: Our study shows interesting trends of worse BC outcomes among South Asian women and better outcomes among those of East Asian descent. Future validation of our findings in a larger cohort of young women with BC would be of interest.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".