Influence of social demographics and African-American race on outcomes in testicular cancer: Analysis of 75,902 patients in the National Cancer database.
Bibliographic record
Abstract
391 Background: While there have been substantial advances in treatment and outcomes in testicular cancer, most of the data are derived from large institutionals or clinical trials. Testicular germ cell tumors are uncommon (8,000 new patients annually in US). The incidence among patients (pts) of African origins is extremely low. Most of the conclusions regarding outcomes are based on Caucasian pts from research institutions. Information about modern outcomes in non-Caucasian races is scant and little is known about the influence of various social demographic parameters on presentation patterns and survival. Using this population-based database available through the NCDB, we sought to better understand social and racial variations in outcomes. Methods: Within the NCDB, 75,902 testicular cancer pts were available for review. Tools available through the NCDB were utilized for analysis. Herein, we evaluated social demographics (insurance type, educational achievement, annual income, type of treating institution) and racial/ethnic characteristics as they pertained to stage at presentation and survival. Results: 75,902 pts were available from the timeframe of 1998 through 2011 for aggregation of social demographic features as well as racial/ethnic characteristics. Overall survival was available on 48573 pts through 2006. Racial-ethnic breakdown at presentation was 84.1% (n=63,867) Caucasian and African-American 2.7% (n=2,083). Overall, insurance type, education (% without high school degree), income (< $ 30000 to >$46,000) and type of treating hospital were analyzed using univariate and multivariate models. Full details will be presented. Conclusions: Unfavorable presentations and outcomes in testicular cancer are seen by race and social demographics. In depth analytics are being performed to characterize the variations as related to biological/genetic differences and/or differences in social demographics. In this very large cohort, the National Cancer database demonstrates a 2-fold risk increase in death in African American pts relative to Caucasian pts with similar stage at presentation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 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".