Abstract 1768: Racial/ethnic differences in endometrioid endometrial cancer survival among cases identified through the National Cancer Database
Bibliographic record
Abstract
Abstract OBJECTIVES: Past research suggests that at the local level, Non-Hispanic whites (NHW) have better survival when diagnosed with endometrioid endometrial cancer (EEC) than non-Hispanic blacks (NHB), Hispanics, and American Indians; however, little is known about survival differences at a national level and among other minorities. This study examined whether racial and ethnic differences in 5-year survival are present in U.S. women (NHW, NHB, Hispanics, non-Hispanic Asians (NHA), non-Hispanic Pacific Islanders/Hawaiians (NHPI), non-Hispanic American Indians/Aleutians or Eskimos (NHAI/AN) and non-Hispanics Others (NHO). METHODS: EEC cases from the National Cancer Database were analyzed to evaluate racial/ethnic differences in 5-year survival among women diagnosed with EEC between 1998 and 2007. Chi-Square test was used to examine whether differences in demographic, clinical, institutional, and treatment variables varied by race/ethnicity. Multivariable Cox proportional hazard regression models were fit to estimate the adjusted hazard ratio (HR) and 95% confidence interval (95% CI) between race/ethnicity and survival. RESULTS: A total of 178,310 women were diagnosed with EEC between 1998 and 2007. Of these; 74.8% were NHW, 8.3% were NHB, 13.9% were Hispanic, 1.8% were NHA, 0.2% were NHPI, 0.2% were NHAI/AN and 0.8% were NHO. Adjusting for covariates, NHB (HR = 1.29; 95%CI 1.24-1.34) and NHPI (HR = 1.59; 95%CI 1.50-1.67) had poorer survival than NHW. Yet results show that NHA (HR = 0.83; 95%CI 0.74-0.92) and NHO (HR = 0.81; 95%CI 0.69-0.94) had a better survival when compared to NHW. No survival differences were detected between Hispanics, NHAI/AN and NHW. CONCLUSIONS: Results identify racial/ethnic differences in 5-year survival among women diagnosed with EEC cancer in the U.S. between 1998 and 2007. NHA and NHO had a better and NHB and NHPI had a poorer survival when compared to NHW. Citation Format: Anna B. Beckmeyer-Borowko, Caryn E. Peterson, Katherine C. Brewer, Mary O. Otoo, Faith G. Davis, Kent F. Hoskins, Charlotte E. Joslin. Racial/ethnic differences in endometrioid endometrial cancer survival among cases identified through the National Cancer Database. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1768.
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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 | 0.002 | 0.003 |
| 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".