The significance of circulating tumor cells in prostate cancer patients undergoing adjuvant or salvage radiation therapy
Bibliographic record
Abstract
BACKGROUND: Following radical prostatectomy, success of adjuvant and salvage radiation therapy (RT) is dependent on the absence of micrometastatic disease. However, reliable prognostic/predictive factors for determining this are lacking. Therefore, novel biomarkers are needed to assist with clinical decision-making in this setting. Enumeration of circulating tumor cells (CTCs) using the regulatory-approved CellSearch System (CSS) is prognostic in metastatic prostate cancer. We hypothesize that CTCs may also be prognostic in the post-prostatectomy setting. METHODS: Patient blood samples (n=55) were processed on the CSS to enumerate CTCs at 0, 6, 12 and 24 months after completion of RT. CTC values were correlated with predictive/prognostic factors and progression-free survival. RESULTS: CTC status (presence/absence) correlated significantly with positive margins (increased likelihood of CTC(neg) disease; P=0.032), and trended toward significance with the presence of seminal vesicle invasion (CTC(pos); P=0.113) and extracapsular extension (CTC(neg); P=0.116). Although there was a trend toward a decreased time to biochemical failure (BCF) in baseline CTC-positive patients (n=9), this trend was not significant (hazard ratio (HR)=0.3505; P=0.166). However, CTC-positive status at any point (n=16) predicted for time to BCF (HR=0.2868; P=0.0437). CONCLUSIONS: One caveat of this study is the small sample size utilized (n=55) and the low number of patients with CTC-positive disease (n=16). However, our results suggest that CTCs may be indicative of disseminated disease and assessment of CTCs during RT may be helpful in clinical decision-making to determine, which patients may benefit from RT versus those who may benefit more from systemic treatments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".