Failure of Ploidy and Proliferative Fraction to Predict Long-Term Outcome After Prostatectomy
Bibliographic record
Abstract
BACKGROUND: Historically, ploidy and S phase percentage appeared to be promising predictors for prostate cancer recurrence. Lack of uniformity and consistency hampered their development. We evaluated ploidy and S phase for prostate cancer death in a cohort of patients with long-term follow-up. METHODS: We identified 127 patients that had ploidy and S phase determined at the time of their radical prostatectomy for prostate cancer. With 15 years of follow-up, we determined the risk of biochemical failure and risk of death from prostate cancer. We correlated the S phase and ploidy findings with standard pathology findings. RESULTS: A total of 107 (84%) had diploid and 20 (16%) had non-diploid cancers. The median S phase was 6.6%. There was no correlation of ploidy (P = 0.472) or S phase with preoperative PSA or Gleason score. On univariate analysis, EPE, margin positivity, seminal vesicle involvement, lymph node involvement, high Gleason score and PSA > 10 ng/mL were all predictive of biochemical failure. Ploidy and S phase were not. For prostate cancer death, only Gleason score was predictive. CONCLUSIONS: With long-term follow-up in our cohort, Gleason score was predictive of prostate cancer death. Ploidy and S phase were not predictive for biochemical failure or prostate cancer mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".