Adult Prostate Sarcoma: Demographics, Treatment Patterns, and Survival
Bibliographic record
Abstract
BACKGROUND: This study aimed to examine clinicopathologic characteristics, treatment patterns, and survival rates in a contemporary population-based cohort of adult prostate sarcoma patients. METHODS: In the Surveillance, Epidemiology, and End Results database (2004-2020), adult patients with prostate sarcoma were identified. Descriptive statistics, Kaplan-Meier analyses, smoothed cumulative incidence plots, and Cox regression models were used. RESULTS: Of 125 patients, 45 (36%) harbored leiomyosarcoma, 17 (14%) had rhabdomyosarcoma, 15 (12%) had stromal sarcoma, 17 (14%) had sarcoma not otherwise specified (NOS), and 31 (25%) had other sarcoma subtypes. Metastatic stage was most common in the rhabdomyosarcoma patients (44%) and least common in the leiomyosarcoma (21%) and stromal sarcoma (20%) patients. Most of the rhabdomyosarcoma patients received the combination of systemic and radiation therapy with (24%) or without radical surgery (35%), whereas most of the leiomyosarcoma and stromal sarcoma patients underwent radical surgery with (22 and 13%) or without (22 and 47%) radiation. In the overall population, the median overall survival was 27 months. The 5-years overall versus cancer-specific versus other-cause mortality rates were respectively 71 versus 58 versus 13%. In the multivariable Cox regression models, the highest overall mortality was exhibited by the patients with metastatic disease (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.55-5.31; p < 0.001) or unknown disease stage (HR 2.94; 95% CI 2.20-7.21; p = 0.019). Conversely, of all the histologic subtypes, only stromal sarcoma distinguished itself by lower overall mortality (HR 0.41; 95% CI 0.18-0.96; p = 0.039). CONCLUSIONS: Four major histologic subtypes were identified. Among most adult sarcoma patients, treatment patterns vary according to histology, from multimodal therapy to radical prostatectomy alone. These treatment differences reflect equally important heterogeneity in survival patterns.
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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 | 0.000 | 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 | 0.000 |
| 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".