Impact of ethnicity on the outcome of men with metastatic, hormone‐sensitive prostate cancer
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PCa) outcomes are impacted by socioeconomic and biologic factors. Ethnicity plays a role in the former, but little is known about the responsiveness of metastatic PCa to androgen-deprivation therapy (ADT) among races. METHODS: The Surveillance, Epidemiology, and End Results (SEER) registry was used to identify men who were diagnosed with distant, de novo, metastatic PCa from 2004 to 2012. Patterns of presentation, overall survival (OS), and PCa-specific mortality (PCSM) were determined for each race. E3805 clinical trial data also were retrospectively reviewed to assess outcomes of ADT and ADT plus docetaxel by race. RESULTS: Of all PCa diagnoses in SEER, distant, de novo, metastatic disease was diagnosed in 4.2% of non-Hispanic whites, 5.8% of Hispanic whites, 5.7% of blacks, 5.5% of Asians/Pacific Islanders, and 8.8% of American Indians/Alaska Natives (P < .001; chi-square test). The median OS differed by race, with superior OS observed among Asian men (30 months) than among men of other races (range, 24-25 months; P < .001). Asians also had a superior median PCSM (54 months) compared with the other races (range, 35-40 months; P < .001). In E3805, chemohormonal therapy was associated with a median OS of 58.1 months (95% confidence interval, 48.8-72.9 months) and 57.6 months (95% confidence interval, 27.7-57.6 months) in non-Hispanic whites and blacks, respectively. Few Asians participated in the E3805 trial. CONCLUSIONS: Asian men have superior median OS and PCSM for distant, de novo, metastatic PCa than men of other race. Non-Hispanic whites and blacks who receive treatment with ADT or chemohormonal therapy have comparable outcomes. Cancer 2017;123:1536-1544. © 2017 American Cancer Society.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".