Abstract P6-06-04: Breast cancer in young women: Have the prognostic and predictive implications of breast cancer subtypes changed over time?
Bibliographic record
Abstract
Abstract Background: Breast cancer (BC) occurring in very young women has a worse prognosis compared to older women, and is the leading cause of cancer death in women aged < 40 years. Over the last decade BC management has evolved to incorporate increased understanding of BC subtypes and new therapeutic agents such as taxanes and trastuzumab. Whether the previously observed poor prognosis associated with BC in young women persists in the context of modern adjuvant therapies and relative to the BC subtypes has not been widely investigated. Methods: We analyzed BC outcomes of young (40-49 years) and very young (<40 years) patients (pts) according to subtype defined by immune histochemistry (IHC) and evaluated for any changes over time by comparing 2 cohorts representative of different time periods. Data from 1,101 women aged < 50 diagnosed with invasive BC between 1986-1992, and 1,945 women diagnosed between 2004-2007 were abstracted from the British Columbia Cancer Agency's Breast Cancer Outcomes Database and analyzed according to two age categories (40 years and 40-49 years) and subtype (IHC was available on the earlier cohort from an established tumor repository for those years). Subtypes were defined as follows: Luminal: estrogen receptor (ER) and/or progesterone receptor (PR) positive, and HER2 negative, HER2: HER2 positive and any ER/PR, and Triple Negative (TN) (ie for ER,PR and HER2 negative). Survival analysis was performed using the Kaplan Meier method. Results: Median follow-up was 13.2 years and 6.2 years for the 1986-1992 and 2004-2007 cohorts respectively. Within both time cohorts, luminal subtype pts <40 demonstrated worse survival compared with those 40-49. This difference remained after accounting for grade in the contemporary cohort alone (Hazard ratio 0.50 p = 0.0001). Inferior survival was observed for pts <40 with HER2 BC in the 1986-1992 cohort, no impact of age was demonstrated in the HER2 2004-2007 cohort. No survival difference was seen between the age groups for TN BC in either time cohort. Across the HER2 and TN subtypes, and for luminal pts 40-49 a significant improvement was seen in 5-year RFS and OS between the 2 time cohorts. 5-year RFS but not OS improved over time for the luminal pts <40. 5 year overall survival 1986-1992 2004-2007 5-yr OS (%) 5-yr OS (%) p value (95% CI) (95% CI) Luminalage < 4082 (76-89) 88 (84-93) 0.138 age 40-4990 (87-92) 95 (94-97) 0.001 p value0.055 <0.001 HER2age < 4049 (35-63) 89 (83-95) <0.001 age 40-4966 (57-75) 89 (83-94) <0.001 p value0.017 0.879 TNage < 40 (101)67 (58-77) 82 (73-90) 0.011 age 40-49 (182)74 (67-80) 84 (79-89) <0.001 p value0.909 0.759 Conclusions: We observed a significant improvement in survival over time for both HER2 and TN BC which may reflect improvements in adjuvant strategies based on subtype presentation. Inferior survival for pts <40 with luminal BC persists in the modern era and this group should be targeted for research. 5 year relapse free survival 1986-1992 2004-2007 5-yr RFS (%) 5-yr RFS (%) p value (95% CI) (95% CI) Luminalage<4065(57-74) 79 (74-85) <0.001 age 40-4977 (72-80) 92 (91-94) <0.001 p value0.009 <0.001 HER2age<4039 (25-52) 81 (70-92) <0.001 age 40-4958 (48-67) 84 (80-88) <0.001 p value0.039 0.879 TNage<4060 (51-70) 78 (69-87) 0.014 age 40-4963 (56-70) 77 (71-82) 0.001 p value0.868 0.933 Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P6-06-04.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".