Clinicopathologic patterns and survival patterns among prostate carcinosarcoma patients in the United States
Bibliographic record
Abstract
INTRODUCTION: Prostatic carcinosarcoma comprises <1% of all prostate neoplasms. The literature on this disease is limited to a few case studies, primarily due to the rarity of this malignancy. We aimed to investigate the demographic, clinical, and histologic factors, prognosis, and survival of prostatic carcinosarcoma. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients with prostatic carcinosarcoma from 2000-2018. Demographic and clinical data, including age, race, sex, tumor grade, stage, tumor size, lymph node status, metastasis, and treatment modalities, were recorded. RESULTS: Patients with prostatic carcinosarcoma had a median age of 72 years at diagnosis, most cases among White individuals (93%). When reported, the histologic grade comprised moderately differentiated (3.3%), poorly differentiated (56.7%), and undifferentiated/anaplastic (40%) subtypes. In patients with reported data, tumor size varied between 2-5 cm (15.8%) and >5 cm (84.2%). Distant metastasis most commonly occurred in the liver (12.5%) and lung (12.5%), followed by the bone (8.3%). The most common treatment performed was surgery with radiation (32.4%). The five-year overall survival was 11.9%. CONCLUSIONS: Prostatic carcinosarcoma affects men in the seventh decade of life. Regional and distant tumor stage is considered an indicator of survival. Prostate carcinosarcoma is rare; due to its aggressive nature, a deeper understanding, and an improved personalized therapeutic approach are necessary for improving patient outcomes in this challenging arena of oncology.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".