Real-world Clinical Outcomes and Prognostic Factors in Neuroendocrine Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: Neuroendocrine prostate cancer (NEPC) encompasses pure NEPC and tumors with mixed adenocarcinoma and neuroendocrine histology. While NEPC is thought to confer a poor prognosis, outcome data are sparse, making risk stratification and treatment decisions difficult for clinicians. METHODS: This retrospective study identified patients with morphological and/or immunohistochemical NEPC features on pathological review of high-grade prostate cancer cases. Median overall survival (OS) was calculated by stage and castration sensitivity. Prognostic factors were assessed via multivariate analysis. OS and progression-free survival on first-line metastatic systemic treatment were also evaluated. RESULTS: Of 135 NEPC cases, 25.9% had NEPC documented in the original pathological report. Mixed pathology was found in 91.9% of cases. Median OS from NEPC diagnosis was 59.2, 42.3, 14.3, 17.6 and 9.6 months for localized, nonmetastatic castration-sensitive, nonmetastatic castration-resistant, metastatic castration-sensitive and metastatic castration-resistant prostate cancer, respectively. Anemia (hazard ratio [HR]: 1.66; 95% CI 1.05-2.16; P = .031) and elevated neutrophil-lymphocyte ratio (NLR) (HR: 1.51; 95% CI 1.01-2.52; P = .045), were associated with increased risk of death on multivariate analysis. 67 patients received first-line metastatic treatment beyond androgen deprivation, with a median progression-free survival of 5.2 months and OS of 15 months. Of these, 50.7% received more than 1 line of systemic treatment. CONCLUSION: We observed underdiagnosis of NEPC in pathology specimens. NEPC is associated with poorer prognosis than would be expected in pure adenocarcinoma populations, with rapid progression on first-line metastatic treatment and sharp drop-off between subsequent treatment lines. Anemia and elevated NLR were associated with poor survival.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".