Abstract P3-07-25: 2 year survival analysis of triple negative breast cancer from SEER data
Bibliographic record
Abstract
Abstract Background Triple negative breast cancer (TNBC) is a heterogeneous disease characterized by the lack of receptor expression (ER, PR and Her 2/neu negative). Amongst breast cancer types TNBC has a less favourable prognosis. There is a higher incidence of TNBC in African-American women than Caucasian women. What has not been clearly elucidated is whether survival outcomes are different among women with TNBC from different ethnic background. Objective The objective of our study was to use population data to determine if significant differences exist in overall survival (OS) of TNBC patients across various ethnicities, including but not limited to–white, black, Hispanic and Asian. Methods Retrospective cohort study of patients with TNBC from 1973-2011 Surveillance, Epidemiology, and End-Results (SEER) database to examine differences in OS across ethnicities. For each case data was collected on age, race, disease stage, treatment, insurance status, time to death and cause of death. Descriptive statistics and survival analysis was carried out on the data. Multivariate analysis was carried out to take into account age, stage, treatments received. Results 12894 cases of TNBC across all ethnicities were reported in the SEER database. At two years follow-up, 720 patients (5.7%) had died of breast cancer. 9696 (78.77%) had early stage (stage 0 – II) disease, 1885 (15.31%) had locally advanced/stage III disease while 728 (5.9%) had stage IV disease. 12071 (95.53%) were insured, 11533 (91.27%) had surgery, and 5454 (43.17%) had radiation therapy. 7746 (61.53%) patients were white, 2429 (19.29%) black, 1548 (12.30%) were Hispanic and 490 (3.89%) were Asian. In multivariate analysis, increasing age, stage III or IV disease, lack of insurance, surgery or radiation all had significant hazard ratios. There was no significant survival difference found between any ethnicity compared with white patients when controlled for age, stage, insurance, surgery and radiation. Discussion After two-year follow-up of large cohort of TNBC patients no significant difference could be found between any ethnicity and the white population with this disease. While there is a large population of black and Hispanic patients in this study there are small numbers of other races. The small relatively small event rate could be masking potential differences given the majority if patients were early stage and are still alive. Longer follow-up is needed before conclusions can be made about differences between ethnic groups. if certain populations do worse will inform the medical oncology community of an area to focus greater research into how to optimize therapies for that patient group. Citation Format: Moira Rushton, Tinghua Zhang, Xinni Song. 2 year survival analysis of triple negative breast cancer from SEER data [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-07-25.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".