Life expectancy in rare histological prostate cancer subtypes
Bibliographic record
Abstract
Survival differences in rare histological prostate cancer (PCa) subtypes relative to age-matched population-based controls are unknown. Within Surveillance, Epidemiology, and End Results database (2004-2020), newly diagnosed (2004-2015) PCa patients were identified. Relying on the Social Security Administration Life Tables (2004-2020) with 5 years of follow-up, age-matched population-based controls (Monte Carlo simulation) were simulated for each patient. Kaplan-Meier analyses addressed survival rates. Of 582,220 patients, 580,368 (99.68%) harbored acinar, 867 (0.15%) ductal, 534 (0.09%) neuroendocrine, 368 (0.07%) mucinous, and 83 (0.01%) signet ring cell carcinoma. The metastatic stage was most prevalent in neuroendocrine (62%). In the localized stage, the overall survival difference at 5 years of follow-up was greatest in neuroendocrine (22% vs. 72%), signet ring cell (78% vs. 84%), and ductal carcinoma (71% vs. 77%). In the locally advanced stage, overall survival difference was greatest in neuroendocrine (16% vs. 79%), signet ring cell (75% vs. 91%), ductal (78% vs. 84%), and mucinous carcinoma (84% vs. 90%). In the metastatic stage, the overall survival difference was greatest in neuroendocrine (3% vs. 81%), mucinous (26% vs. 84%), and acinar carcinoma (27% vs. 85%). Regardless of stage, neuroendocrine carcinoma patients exhibit the least favorable life expectancy compared with population-based controls. Conversely, all other rare histological PCa subtypes do not meaningfully affect life expectancy in localized or locally advanced stages, except for locally advanced signet ring cell adenocarcinoma.
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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 | 0.001 |
| 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".