Rare histological prostate cancer subtypes: Cancer-specific and other-cause mortality
Bibliographic record
Abstract
BACKGROUND: To assess cancer-specific mortality (CSM) and other-cause mortality (OCM) rates in patients with rare histological prostate cancer subtypes. METHODS: Using the Surveillance, Epidemiology, and End Results database (2004-2020), we applied smoothed cumulative incidence plots and competing risks regression (CRR) models. RESULTS: Of 827,549 patients, 1510 (0.18%) harbored ductal, 952 (0.12%) neuroendocrine, 462 (0.06%) mucinous, and 95 (0.01%) signet ring cell carcinoma. In the localized stage, five-year CSM vs. OCM rates ranged from 2 vs. 10% in acinar and 3 vs. 8% in mucinous, to 55 vs. 19% in neuroendocrine carcinoma patients. In the locally advanced stage, five-year CSM vs. OCM rates ranged from 5 vs. 6% in acinar, to 14 vs. 16% in ductal, and to 71 vs. 15% in neuroendocrine carcinoma patients. In the metastatic stage, five-year CSM vs. OCM rates ranged from 49 vs. 15% in signet ring cell and 56 vs. 16% in mucinous, to 63 vs. 9% in ductal and 85 vs. 12% in neuroendocrine carcinoma. In multivariable CRR, localized neuroendocrine (HR 3.09), locally advanced neuroendocrine (HR 9.66), locally advanced ductal (HR 2.26), and finally metastatic neuroendocrine carcinoma patients (HR 3.57; all p < 0.001) exhibited higher CSM rates relative to acinar adenocarcinoma patients. CONCLUSIONS: Compared to acinar adenocarcinoma, patients with neuroendocrine carcinoma of all stages and locally advanced ductal carcinoma exhibit higher CSM rates. Conversely, CSM rates of mucinous and signet ring cell adenocarcinoma do not differ from those of acinar adenocarcinoma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".